Add jamie-copy-trimmer (48) and dintel-campaign-designer (78) skills

Import two skills authored in Claude Cowork: jamie-copy-trimmer as a
root-only Jamie skill, and campaign-gate-process as dintel-campaign-designer
with full D.intelligence Agent Corps packaging (code/desktop/shared,
agent-id 78, Draft & Wait autonomy) since it now sits inside the 70-79
block. Bumps the corps roster count to 9 agents + 1 meta-agent across all
sibling skills and registers #78 in the shared USER-GUIDE/README. Also adds
.claude/commands wrappers and ~/.claude/skills symlinks so both are usable.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

.claude-plugin/marketplace.json

@@ -0,0 +1,163 @@
+{
+  "$schema": "https://json.schemastore.org/claude-code-marketplace-schema.json",
+  "name": "ourdigital-skills",
+  "owner": {
+    "name": "OurDigital",
+    "email": "andrew.yim@ourdigital.org"
+  },
+  "metadata": {
+    "description": "OurDigital custom Claude skills, grouped into domain plugins (core, SEO, Jamie, D.intelligence, Notion, GTM, NotebookLM, utilities). Enable only the domains you need.",
+    "version": "1.0.0"
+  },
+  "plugins": [
+    {
+      "name": "ourdigital-core",
+      "description": "OurDigital core workflows — brand guide, Korean blog & English journal, research-to-blog, Notion-to-deck, visual design, ad copy, training material, back-office docs, skill creator, estimate engine.",
+      "source": "./",
+      "strict": false,
+      "skills": [
+        "./custom-skills/01-ourdigital-brand-guide",
+        "./custom-skills/02-ourdigital-blog",
+        "./custom-skills/03-ourdigital-journal",
+        "./custom-skills/04-ourdigital-research",
+        "./custom-skills/05-ourdigital-document",
+        "./custom-skills/06-ourdigital-designer",
+        "./custom-skills/07-ourdigital-ad-manager",
+        "./custom-skills/08-ourdigital-trainer",
+        "./custom-skills/09-ourdigital-backoffice",
+        "./custom-skills/10-ourdigital-skill-creator",
+        "./custom-skills/96-ourdigital-estimate-engine"
+      ]
+    },
+    {
+      "name": "ourdigital-seo",
+      "description": "Full SEO suite — technical/on-page audits, Core Web Vitals, Search Console, schema validate/generate, local, keyword, SERP, rank tracking, links, content, e-commerce, KPIs, international, AI visibility, knowledge graph, gateway pages, competitor intel, crawl budget, migration, reporting, presales.",
+      "source": "./",
+      "strict": false,
+      "skills": [
+        "./custom-skills/11-seo-comprehensive-audit",
+        "./custom-skills/12-seo-technical-audit",
+        "./custom-skills/13-seo-on-page-audit",
+        "./custom-skills/14-seo-core-web-vitals",
+        "./custom-skills/15-seo-search-console",
+        "./custom-skills/16-seo-schema-validator",
+        "./custom-skills/17-seo-schema-generator",
+        "./custom-skills/18-seo-local-audit",
+        "./custom-skills/19-seo-keyword-strategy",
+        "./custom-skills/20-seo-serp-analysis",
+        "./custom-skills/21-seo-position-tracking",
+        "./custom-skills/22-seo-link-building",
+        "./custom-skills/23-seo-content-strategy",
+        "./custom-skills/24-seo-ecommerce",
+        "./custom-skills/25-seo-kpi-framework",
+        "./custom-skills/26-seo-international",
+        "./custom-skills/27-seo-ai-visibility",
+        "./custom-skills/28-seo-knowledge-graph",
+        "./custom-skills/29-seo-gateway-architect",
+        "./custom-skills/30-seo-gateway-builder",
+        "./custom-skills/31-seo-competitor-intel",
+        "./custom-skills/32-seo-crawl-budget",
+        "./custom-skills/33-seo-migration-planner",
+        "./custom-skills/34-seo-reporting-dashboard",
+        "./custom-skills/35-seo-signal-validation",
+        "./custom-skills/95-ourdigital-presales-seo"
+      ]
+    },
+    {
+      "name": "ourdigital-notion",
+      "description": "Notion workspace tools — organize/clean up a workspace and write/export content into Notion.",
+      "source": "./",
+      "strict": false,
+      "skills": [
+        "./custom-skills/31-notion-organizer",
+        "./custom-skills/32-notion-writer"
+      ]
+    },
+    {
+      "name": "ourdigital-jamie",
+      "description": "Jamie Plastic Surgery Clinic brand suite — branded content, brand audit, KakaoTalk Kanana FAQ, YouTube SEO + subtitle QA, Instagram management, journal editor, multi-channel marketing.",
+      "source": "./",
+      "strict": false,
+      "skills": [
+        "./custom-skills/40-jamie-brand-editor",
+        "./custom-skills/41-jamie-brand-audit",
+        "./custom-skills/42-jamie-faq-entry",
+        "./custom-skills/43-jamie-youtube-manager",
+        "./custom-skills/44-jamie-youtube-subtitle-checker",
+        "./custom-skills/45-jamie-instagram-manager",
+        "./custom-skills/46-jamie-journal-editor",
+        "./custom-skills/47-jamie-marketing-editor"
+      ]
+    },
+    {
+      "name": "ourdigital-notebooklm",
+      "description": "NotebookLM automation — Q&A with citations, notebook/source/artifact management, studio content generation (podcasts, videos, quizzes), and research/source discovery. Requires the notebooklm-py CLI.",
+      "source": "./",
+      "strict": false,
+      "skills": [
+        "./custom-skills/50-notebooklm-agent",
+        "./custom-skills/51-notebooklm-automation",
+        "./custom-skills/52-notebooklm-studio",
+        "./custom-skills/53-notebooklm-research"
+      ]
+    },
+    {
+      "name": "ourdigital-gtm",
+      "description": "Google Tag Manager tooling — container audit/gap analysis, tag/trigger/variable editor (API + ES5 Custom HTML + dataLayer), and QA/validation.",
+      "source": "./",
+      "strict": false,
+      "skills": [
+        "./custom-skills/60-gtm-audit",
+        "./custom-skills/61-gtm-editor",
+        "./custom-skills/62-gtm-validator"
+      ]
+    },
+    {
+      "name": "ourdigital-dintel",
+      "description": "D.intelligence Agent Corps — brand guardian/editor, document secretary, quotation manager, service architect, marketing manager, back-office manager, account manager, and cross-skill update meta-agent.",
+      "source": "./",
+      "strict": false,
+      "skills": [
+        "./custom-skills/70-dintel-brand-guardian",
+        "./custom-skills/71-dintel-brand-editor",
+        "./custom-skills/72-dintel-doc-secretary",
+        "./custom-skills/73-dintel-quotation-mgr",
+        "./custom-skills/74-dintel-service-architect",
+        "./custom-skills/75-dintel-marketing-mgr",
+        "./custom-skills/76-dintel-backoffice-mgr",
+        "./custom-skills/77-dintel-account-mgr",
+        "./custom-skills/79-dintel-skill-update"
+      ]
+    },
+    {
+      "name": "ourdigital-utils",
+      "description": "Utility skills — Claude settings/token optimizer, Google Drive organizer, reference-documentation curator suite, and TUI wizard design template.",
+      "source": "./",
+      "strict": false,
+      "skills": [
+        "./custom-skills/80-claude-settings-optimizer",
+        "./custom-skills/82-our-gdrive-organizer",
+        "./custom-skills/90-reference-curator",
+        "./custom-skills/92-tui-design-template"
+      ]
+    },
+    {
+      "name": "mac-optimizer",
+      "description": "macOS system health toolkit — read-only audits, cleanup, and security checks. Commands: mac-doctor, mac-packages, mac-environment, mac-security, mac-cleanup, mac-resources (+ mac-optimizer skill).",
+      "source": "./custom-skills/81-mac-optimizer",
+      "strict": false
+    },
+    {
+      "name": "multi-agent-guide",
+      "description": "Multi-agent collaboration framework — agent hierarchies, ownership rules, guardrails, handoff protocols, and CI/CD integration for Claude, Gemini, Codex, and human agents. Commands: quick-setup, setup-agents (+ multi-agent-guide skill).",
+      "source": "./custom-skills/91-multi-agent-guide",
+      "strict": false
+    },
+    {
+      "name": "dintel-bootstrap",
+      "description": "Install and verify D.intelligence custom MCP agents (DTM, D.DA, OurSEO) in settings.json; bootstrap a new machine or diagnose a broken install (dintel-bootstrap skill).",
+      "source": "./custom-skills/94-dintel-bootstrap",
+      "strict": false
+    }
+  ]
+}

.claude/commands/dintel-campaign-designer.md

@@ -0,0 +1,31 @@
+---
+description: D.intelligence campaign/promotion planning as a 3-gate process (cross-brand)
+---
+
+# D.intelligence Campaign Designer
+
+Plans campaigns, promotions, events, and launches as a 3-gate process -- Discovery & Debate → Brief → Plan -- instead of jumping straight to a finished document. Draft & Wait autonomy: each gate stops for explicit approval. Not D.intelligence-exclusive -- works for any brand.
+
+## Triggers
+- "campaign plan", "plan a promotion", "캠페인 설계"
+- 캠페인 기획, 프로모션 기획, 기획안 만들어, 이벤트 기획
+
+## The 3 Gates
+1. **Discovery & Debate** -- agree ONE primary objective; steelman + devil's-advocate debate; pre-mortem; 1-3 reference cases; effects as hypotheses. → `shared/templates/gate1-decision-log.md`
+2. **Brief** -- objective, audience, offer, message, tone, channel; outcome metrics across 4 tiers. → `shared/templates/gate2-campaign-brief.md`
+3. **Plan** -- full plan, handed off to `marketing:campaign-plan` + `doc-generator`; all risk/compliance consolidated in one closing "준비 점검 사항" section. → `shared/templates/gate3-plan-outline.md`
+
+## 4-Tier Outcome Framework
+Awareness/cognitive → Qualitative (name the brand asset) → Relationship/advocacy → Quantitative conversion (label as hypothesis if no baseline)
+
+## Cross-Brand Routing
+| Brand | Copy & tone | Compliance |
+|---|---|---|
+| D.intelligence | dintel-brand-editor (#71) | dintel-brand-guardian (#70) |
+| Jamie | jamie-copy-trimmer (48) | jamie-brand-audit (41) |
+| OurDigital | ourdigital-ad-manager (07) | ourdigital-brand-guide (01) |
+
+## Guardrails
+- Never advance a gate without explicit user approval
+- Never commit pricing/quantitative targets without a baseline -- label as hypothesis
+- Mark gaps `[확인]` instead of inventing facts

.claude/commands/gtm-audit.md

@@ -6,6 +6,20 @@ description: GTM page audit - scan fired tags, gap analysis, tag design from DOM
 
 Comprehensive Google Tag Manager audit using Playwright to scan live pages for container health, tag firing, dataLayer events, form tracking, and e-commerce checkout flows.
 
+## MANDATORY: Knowledge Base Read/Write
+
+**Before starting any audit:**
+1. Identify the target client from container ID or URL
+2. Read `knowledge-base/accounts/<client>/profile.md` — URL patterns, known issues, platform stack, past findings
+3. Read `knowledge-base/accounts/<client>/*.md` — taxonomy, naming issues to exclude from new findings
+4. Skim `knowledge-base/logs/<client>/` — past session context
+
+**After completing audit, write a session log:**
+- Write to `knowledge-base/logs/<client>/YYYY-MM-DD-<description>.md`
+- Include: date, container ID, status, issues found (root causes + specific IDs), lessons learned
+- Update `knowledge-base/accounts/<client>/profile.md` if you discovered persistent facts
+- See `AGENTS.md` for full format template
+
 ## Triggers
 - "audit GTM", "check dataLayer", "GTM 검사", "scan GTM tags", "audit tags on page", "check tag firing"
 

.claude/commands/gtm-editor.md

@@ -22,6 +22,20 @@ Priority reads per task:
 - "create GTM tag", "generate dataLayer", "modify trigger"
 - "update variable", "write custom HTML", "manage GTM"
 
+## MANDATORY: Knowledge Base Read/Write
+
+**Before creating or modifying ANY tags, triggers, or variables:**
+1. Identify the target client from container ID
+2. Read `knowledge-base/accounts/<client>/profile.md` — key variables, URL patterns, platform stack, known issues
+3. Read `knowledge-base/accounts/<client>/*.md` — taxonomy reveals existing event names and naming conventions
+4. Skim `knowledge-base/logs/<client>/` — past fixes reveal patterns (e.g., "form POST loses URL params")
+
+**After completing tag management, write a session log:**
+- Write to `knowledge-base/logs/<client>/YYYY-MM-DD-<description>.md`
+- Include: date, container ID, tags affected (IDs), what was created/modified/deleted, cHTML snippets
+- Update `knowledge-base/accounts/<client>/profile.md` if you discovered persistent facts
+- See `AGENTS.md` for full format template
+
 ## MANDATORY: dataLayer First Workflow
 
 1. **Design dataLayer push FIRST** (match client's tech stack: vanilla JS/React/Vue/PHP)

.claude/commands/gtm-guardian.md

@@ -1,49 +1,44 @@
 ---
-description: GTM lifecycle automation - progressive audit, version comparison, and lookup app
+description: Deprecated alias for DTM Agent skills — redirects to /dtm-audit, /dtm-lookup, /dtm-version, and /gtm-validator
 ---
 
-# GTM Guardian
+# GTM Guardian (Deprecated)
 
-GTM tagging lifecycle automation: progressive audit (Phase 6) and event lookup app (Phase 7).
+> **The `gtm-guardian` workflow and the `dintel-gtm-toolkit` Python scripts are deprecated.** All GTM lifecycle automation now lives in the **DTM Agent** skill set, which operates on live containers via the Google Tag Manager API instead of exported JSON.
 
-## Triggers
+## Use these instead
-- "GTM audit lifecycle", "container analysis"
-- "GTM 유지보수", "버전 비교"
 
-## Quick Commands
+| Old (gtm-guardian / dintel-gtm-toolkit) | New (DTM Agent skill) |
+|---|---|
+| `analyze_container.py` — container structure analysis | `/dtm-tags`, `/dtm-triggers`, `/dtm-variables`, `/dtm-lookup` |
+| `find_unused.py` — unused element detection | `/dtm-lookup` (unused resource detection) |
+| `diff_versions.py` — version comparison | `/dtm-version` (list, create, compare versions) |
+| `validate_tags.py` — tag firing verification | `/gtm-validator` (live page QA via Chrome DevTools MCP) |
+| Phase 6 — Progressive Audit | `/dtm-audit` (page audit, tracking coverage, gap analysis) + `/dtm-debug` (A–D grading) |
+| Phase 7 — Event Taxonomy Lookup App | `/dtm-taxonomy` (classify events, validate naming, export docs) + `/dtm-lookup` (universal search, dependency graph) |
+| Container/account switching | `/dtm-set` |
+| Status & health check | `/dtm-status` |
+
+## Quick Reference
 
 ```bash
-# Clone D.intelligence GTM Toolkit
+# Active context
-git clone https://github.com/ourdigital/dintel-gtm-agent.git
+dtm status
+dtm list accounts
+dtm list containers
 
-# Container analysis
+# Inspect live container
-python analyze_container.py GTM-XXXXXX.json --output report.md
+dtm list tags
+dtm list triggers
+dtm list variables
 
-# Version comparison
+# Versions
-python diff_versions.py v1.json v2.json --output diff.md
+dtm list versions
-
+dtm version live
-# Unused element detection
-python find_unused.py container.json --type all
 ```
 
-## Phase 6: Progressive Audit
+For full workflows, invoke the skill directly (e.g. `/dtm-audit`, `/gtm-validator`) — each skill bundles the right tool sequence, output formatting, and Notion reporting via the `notion-writer` skill.
-
-| Feature | Description |
-|---------|-------------|
-| Container Analysis | JSON parsing, structure analysis |
-| Dependency Mapping | Tag-trigger-variable relationships |
-| Version Diff | Change tracking between versions |
-| Tag Validation | Automatic firing state verification |
-
-### Audit Schedule
-- Weekly: Tag firing validation
-- Monthly: Full container review
-- Quarterly: Architecture review
-
-## Phase 7: Lookup App
-Google Apps Script-based Event Taxonomy lookup app (Google Sheets -> Apps Script -> Web App).
 
 ## Notion Output
-- Database: GTM Knowledge Base
+
-- Properties: Project, Audit Date, Container ID, Status, Issues Count
+Unchanged — DTM Agent skills still write to the **GTM Knowledge Base** database (properties: Project, Audit Date, Container ID, Status, Issues Count). Reports remain in Korean with English technical terms.
-- Reports in Korean; technical terms in English

.claude/commands/gtm-validator.md

@@ -20,6 +20,20 @@ Priority reads per task:
 - "validate tags", "QA GTM", "debug GTM"
 - "naming conventions", "GTM best practice"
 
+## MANDATORY: Knowledge Base Read/Write
+
+**Before starting any validation or QA:**
+1. Identify the target client from container ID or URL
+2. Read `knowledge-base/accounts/<client>/profile.md` — naming conventions, known issues, platform stack
+3. Read `knowledge-base/accounts/<client>/*.md` — taxonomy defines expected events; naming fix plans reveal known violations
+4. Skim `knowledge-base/logs/<client>/` — past QA reveals recurring issues and known false positives
+
+**After completing validation, write a session log:**
+- Write to `knowledge-base/logs/<client>/YYYY-MM-DD-<description>.md`
+- Include: date, container ID, pass/fail results, broken triggers (IDs), new naming violations
+- Update `knowledge-base/accounts/<client>/profile.md` if you discovered persistent facts
+- See `AGENTS.md` for full format template
+
 ## Validation Modes
 
 ### 1. Tag Firing Verification

.claude/commands/jamie-copy-trimmer.md

@@ -0,0 +1,36 @@
+---
+description: Trims and sharpens Korean plastic-surgery/aesthetic marketing copy against cliché & compliance corpus
+---
+
+# Jamie Copy Trimmer
+
+Trim and sharpen Korean plastic-surgery / aesthetic-medical marketing copy against an industry expression corpus, within 의료광고 심의 limits. Guidance-only skill (no scripts).
+
+## Triggers
+- "카피 다듬어", "카피 트리밍", "네이밍 검토", "슬로건 다듬어"
+- "심의 안전하게", "copy trim", "make it catchier"
+
+## Core Philosophy
+- The corpus is a map for AVOIDING clichés, not a library to copy
+- 의료광고 심의 is a gate, not a score -- one 🔴 risk expression fails the option outright
+- Trim first, dazzle second
+- Don't guess -- mark `[확인]`
+
+## Workflow (5 steps)
+1. **Diagnose** -- tag each phrase 🟢 effective / 🟡 cliché / 🔴 compliance risk / ⚪ flat / 🟦 brand asset
+2. **Trim** -- remove all 🔴, replace 🟡, delete redundancy
+3. **Elevate** -- 2-3 alternatives per element within 심의 limits, matched to channel tone
+4. **Re-score** -- 5-axis rubric (감각/차별성/브랜드적합성/심의 PASS-FAIL/명료성)
+5. **Recursive Improvement** -- propose feeding adopted/rejected expressions back into the corpus
+
+## Output (Korean)
+진단 → 트리밍 → 대안 → 재평가 → 추천안 → 준비 점검 사항 (risks/gaps consolidated at the end)
+
+## References
+- `references/corpus_compliance_risk.md` -- medical-ad risk expressions (most important)
+- `references/corpus_cliche.md`, `corpus_effective.md`, `corpus_examples.md`
+- `references/witty_within_limits.md`, `evaluation_rubric.md`, `recursive_protocol.md`
+
+## Guardrails
+- Compliance judgment here is guidance, not legal advice -- always recommend pre-publication 의료광고 자율심의
+- A specific brand's tone guide (e.g. jamie-brand-audit) overrides this skill's taste defaults

.claude/commands/jamie-marketing-editor.md

@@ -0,0 +1,40 @@
+---
+description: Jamie Clinic multi-channel marketing content editor with compliance checking
+---
+
+# Jamie Marketing Editor
+
+Marketing content across all Jamie Clinic digital channels: website, blog, SNS, ads, email, KakaoTalk.
+
+## Triggers
+- "Jamie marketing", "제이미 마케팅"
+- "광고 카피", "SNS 콘텐츠", "ad copy"
+
+## Scripts
+
+```bash
+python code/scripts/compliance_checker.py --input draft.md
+python code/scripts/compliance_checker.py --input draft.md --verbose --output report.json
+```
+
+## Channel Tone Guide
+- **Website**: Professional, educational, trust-building
+- **Blog**: Educational, accessible, SEO-optimized
+- **Instagram**: Sensory, concise, trendy + hashtags
+- **YouTube**: Professional, step-by-step with visuals
+- **KakaoTalk**: Friendly, helpful, action-oriented
+- **Ads**: Factual, compliant, no superlatives
+
+## Brand Pillars
+- Safety, Naturalness, Transparency, Quality Assurance
+- Key differentiators: director's personal care, 5-year AS, revision expertise
+
+## Compliance Rules (Korean Medical Ad Law)
+- No exaggerated claims or guarantee language
+- No patient testimonials
+- No before/after comparisons without disclaimers
+- No competitor comparisons
+- Required side-effect and individual variation disclosures
+
+## Workflow
+1. Define channel + audience -> 2. Generate content -> 3. Run compliance checker -> 4. Submit to jamie-brand-audit

.claude/commands/notion-writer.md

@@ -24,7 +24,7 @@ Push markdown content to Notion pages or databases via the Notion API.
 ## Scripts
 
 ```bash
-cd ~/Projects/our-claude-skills/custom-skills/32-notion-writer/code/scripts
+cd ~/Project/our-claude-skills/custom-skills/32-notion-writer/code/scripts
 
 # Test connection
 python notion_writer.py --test

.github/workflows/verify-skills.yml

@@ -0,0 +1,26 @@
+name: Verify Skills
+
+# Runs the skill load-verifier on every push and pull request.
+# Fails the build if any skill would not load (invalid frontmatter, bad name,
+# name collision, orphan dir, or invalid plugin.json). Read-only check.
+on:
+  push:
+  pull_request:
+
+jobs:
+  verify-skills:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+
+      - name: Install dependencies
+        run: pip install pyyaml
+
+      - name: Verify all skills load correctly
+        run: python3 scripts/verify_skills.py

.gitignore

@@ -99,3 +99,7 @@ build/
 # Temporary files
 output/
 keyword_analysis_*.json
+
+# graphify: keep graph.json/html/report, drop regenerable cache + dated backups
+graphify-out/cache/
+graphify-out/????-??-??/

.graphifyignore

@@ -0,0 +1,4 @@
+# graphify scope control — exclude non-standard virtualenvs that the default
+# rules (.venv, venv) don't catch, so pip-package source doesn't pollute the graph.
+.venv-ourdigital/
+.venv-*/

AGENTS.md

@@ -148,6 +148,7 @@ Three specialized skills with clear handoff workflow: **audit → edit → valid
 - Brand compliance is critical - check `references/` for guidelines
 - Korean language content - verify encoding in scripts
 - Instagram/YouTube skills may need API credentials
+- **42-jamie-faq-entry**: KakaoTalk Kanana chatbot Q&A entries (medical ad compliance, character limits)
 - **46-jamie-journal-editor**: Journal/blog articles for journal.jamie.clinic in Dr. Jung's voice
 - **47-jamie-marketing-editor**: Multi-channel marketing (ads, SNS, email) with compliance checker script
 
@@ -194,10 +195,17 @@ Task(
   - **Always ask user consent** before executing any cleanup or system changes
   - Scripts are in `custom-skills/81-mac-optimizer/scripts/`
   - Reference docs in `custom-skills/81-mac-optimizer/references/`
-- **82-tui-design-template**: TUI wizard interface design (Norton Commander / Gopher style, Rich)
+- **82-our-gdrive-organizer**: Organize a Google Drive folder under OurDigital conventions
+  - Refreshes root `README.md` index (Snapshot + Structure section between AUTO-STRUCTURE markers; preserves manual Topics/Notes)
+  - Ensures per-subfolder `README.md` meta files with auto-indexed Contents block
+  - Proposes filename renames (`D.intelligence` → `OurDigital`) and moves (screenshots, temp downloads → tidy subfolders)
+  - Skips sensitive folders by default: `04_Case Studies/`, `99_Project Archive/`, `*Archive$`, `진단*`
+  - Pure Python stdlib CLI: `~/.local/bin/our-gdrive-organize [TARGET] [--apply] [--scope full|index|subreadmes|rename|move]`
+  - Slash command: `/organize`
 
-### Reference Curator Skills (90-91)
+### Reference Curator Skills (90-91) & Design Templates (92)
 
+- **92-tui-design-template**: TUI wizard interface design (Norton Commander / Gopher style, Rich) — moved from slot 82 to make room for `our-gdrive-organizer`
 - Use **reference-curator-pipeline** for full automated curation workflows
 - Runs as background task, coordinates all 6 skills in sequence
 - Handles QA loops automatically (max 3 refactor, 2 deep_research iterations)

CLAUDE.md

@@ -7,7 +7,7 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
 **GitHub**: https://github.com/ourdigital/our-claude-skills
 
 This is a Claude Skills collection repository containing:
-- **custom-skills/**: 64 custom skills for OurDigital workflows, SEO, GTM, Jamie Brand, NotebookLM, Notion, D.intelligence Agent Corps, Reference Curation, Mac Optimizer, TUI Designer, and Multi-Agent Collaboration
+- **custom-skills/**: 65 custom skills for OurDigital workflows, SEO, GTM, Jamie Brand, NotebookLM, Notion, D.intelligence Agent Corps, Reference Curation, Mac Optimizer, TUI Designer, and Multi-Agent Collaboration
 - **example-skills/**: Reference examples from Anthropic's official skills repository
 - **official-skills/**: Notion integration skills (3rd party)
 - **reference/**: Skill format requirements documentation
@@ -39,7 +39,7 @@ This is a Claude Skills collection repository containing:
 | 14 | seo-core-web-vitals | LCP, CLS, FID, INP metrics | "Core Web Vitals", "page speed" |
 | 15 | seo-search-console | GSC data analysis | "Search Console", "rankings" |
 | 16 | seo-schema-validator | Structured data validation | "validate schema", "JSON-LD" |
-| 17 | seo-schema-generator | Schema markup creation | "generate schema", "create JSON-LD" |
+| 17 | seo-schema-generator | JSON-LD generation — Mode 1 from existing site, Mode 2 from collected sources → claims register → drafts → validate (16) | "generate schema", "create JSON-LD", "source-to-schema", "schema from site" |
 | 18 | seo-local-audit | NAP, GBP, citations | "local SEO", "Google Business Profile" |
 | 19 | seo-keyword-strategy | Keyword expansion, intent, clustering, gaps | "keyword research", "keyword strategy" |
 | 20 | seo-serp-analysis | Google/Naver SERP features, competitor positions | "SERP analysis", "SERP features" |
@@ -71,11 +71,13 @@ This is a Claude Skills collection repository containing:
 |---|-------|---------|---------|
 | 40 | jamie-brand-editor | Branded content generation | "write Jamie blog", "Jamie content" |
 | 41 | jamie-brand-audit | Content review/compliance | "review content", "brand audit" |
+| 42 | jamie-faq-entry | KakaoTalk Kanana chatbot Q&A entries | "카나나 답변", "Kanana Q&A", "카카오 상담 답변" |
 | 43 | jamie-youtube-manager | YouTube SEO audit & management | "YouTube SEO", "YT optimization" |
 | 44 | jamie-youtube-subtitle-checker | YouTube subtitle validation | "check subtitles", "subtitle QA" |
 | 45 | jamie-instagram-manager | Instagram account management | "Instagram management", "IG strategy" |
 | 46 | jamie-journal-editor | Journal/blog content for journal.jamie.clinic | "Jamie journal", "제이미 저널", "진료실 이야기" |
 | 47 | jamie-marketing-editor | Multi-channel marketing content & ad copy | "Jamie marketing", "제이미 마케팅", "광고 카피" |
+| 48 | jamie-copy-trimmer | Trim/sharpen Korean aesthetic-medical copy against cliché & compliance corpus | "카피 다듬어", "카피 트리밍", "심의 안전하게", "copy trim" |
 
 ### NotebookLM Tools (50-59)
 
@@ -108,6 +110,7 @@ This is a Claude Skills collection repository containing:
 | 75 | dintel-marketing-mgr | Content pipeline (Magazine D., newsletter, LinkedIn) | Draft & Wait | "콘텐츠 발행", "newsletter" |
 | 76 | dintel-backoffice-mgr | Invoicing, contracts, NDA, HR operations | Draft & Wait | "계약서", "인보이스" |
 | 77 | dintel-account-mgr | Client relationship management & monitoring | Mixed | "client status", "미팅 준비" |
+| 78 | dintel-campaign-designer | Campaign/promotion planning as a 3-gate process (Discovery & Debate → Brief → Plan); cross-brand, not D.intelligence-exclusive | Draft & Wait | "campaign plan", "캠페인 기획", "기획안 만들어" |
 | 79 | dintel-skill-update | Cross-skill consistency management (meta-agent) | Triggered | "skill sync", "스킬 업데이트" |
 
 **Shared infrastructure:** `_dintel-shared/` (Python package + reference docs)
@@ -157,21 +160,30 @@ This is a Claude Skills collection repository containing:
 |---|-------|---------|---------|
 | 80 | claude-settings-optimizer | Claude settings optimization & token audit | "settings audit", "exceed response limit", "MCP error" |
 | 81 | mac-optimizer | macOS system health audit & optimization (Claude Code only) | "audit my mac", "system health", "clean up caches", "check security", "update packages" |
-| 82 | tui-design-template | TUI wizard interface design (Norton Commander / Gopher style, Rich) | "build TUI", "CLI wizard", "terminal UI", "Rich TUI" |
+| 82 | our-gdrive-organizer | Organize a Google Drive folder under OurDigital conventions: refresh README index, refresh per-subfolder READMEs, propose renames + moves | "/organize", "organize the Drive folder", "refresh the index", "rescan the folder" |
 
-## Dual-Platform Skill Structure
+## Skill Structure (root `SKILL.md` + dual-platform packaging)
 
-Each skill has two independent versions:
+**Going-forward standard.** Each skill has a root `SKILL.md` (the official Agent Skills
+format — natively loadable by Claude Code / Desktop / API) plus the OurDigital `code/` +
+`desktop/` packaging. Reference implementations: `16-seo-schema-validator`,
+`17-seo-schema-generator`. To migrate an older skill, follow
+`reference/SKILL-MIGRATION-GUIDE.md` (additive — no rewrite).
 
 ```
 XX-skill-name/
-├── code/                    # Claude Code version
+├── SKILL.md                 # Root directive — official Agent Skills format (LOADABLE)
-│   ├── CLAUDE.md            # Action-oriented directive
+├── scripts/                 # Runnable scripts (single source of truth)
-│   ├── scripts/             # Executable Python/Bash
+├── references/              # Heavy docs, loaded on demand
-│   └── docs/                # Documentation
+├── templates/               # Optional
+├── fixtures/                # Optional sample/test inputs
 │
-├── desktop/                 # Claude Desktop version
+├── code/                    # Claude Code packaging
-│   ├── SKILL.md             # Skill directive with YAML frontmatter
+│   ├── CLAUDE.md            # Redirects to ../SKILL.md + ../scripts (no duplication)
+│   └── scripts/             # Legacy/aux tools only
+│
+├── desktop/                 # Claude Desktop packaging
+│   ├── SKILL.md             # Desktop directive with YAML frontmatter
 │   ├── skill.yaml           # Extended metadata (optional)
 │   └── tools/               # MCP tool documentation
 │
@@ -179,24 +191,24 @@ XX-skill-name/
 └── README.md                # Overview
 ```
 
-### Platform Differences
+Older skills may still be `code/` + `desktop/` only (no root `SKILL.md`) — valid, but not
+directly loadable. Migrate incrementally, not in bulk.
 
-| Aspect | `code/` | `desktop/` |
+### Layer roles
-|--------|---------|------------|
-| Directive | CLAUDE.md | SKILL.md (with YAML frontmatter) |
-| Metadata | In CLAUDE.md | skill.yaml (optional) |
-| Tool docs | N/A | tools/ directory |
-| Execution | Direct Bash/Python | MCP tools only |
-| Scripts | Required | Reference only |
 
-### SKILL.md Format (Desktop)
+| Layer | Role |
+|-------|------|
+| root `SKILL.md` | Canonical, loadable directive + bundled resources |
+| `code/` | Claude Code packaging; `CLAUDE.md` redirects to the root |
+| `desktop/` | Claude Desktop view; `SKILL.md` + `skill.yaml` + `tools/` |
+
+### SKILL.md frontmatter (root + desktop)
 
 ```markdown
 ---
-name: skill-name-kebab-case
+name: skill-name-kebab-case        # clean name: dir minus the NN- prefix
 description: |
-  Brief description of what the skill does.
+  What it does + when to use. Triggers: keyword1, keyword2, 한국어 트리거.
-  Triggers: keyword1, keyword2, 한국어 트리거.
 ---
 
 # Skill Title
@@ -204,6 +216,11 @@ description: |
 Content starts here...
 ```
 
+**Naming convention:** the directory keeps its `NN-` prefix for ordering
+(`16-seo-schema-validator/`), but the skill `name:` is the **clean** form without it
+(`name: seo-schema-validator`). Names must be kebab-case and globally unique.
+Whole frontmatter ≤ 1024 chars. Full rules + migration recipe: `reference/SKILL-MIGRATION-GUIDE.md`.
+
 ## Directory Layout
 
 ```
@@ -232,11 +249,13 @@ our-claude-skills/
 │   │
 │   ├── 40-jamie-brand-editor/
 │   ├── 41-jamie-brand-audit/
+│   ├── 42-jamie-faq-entry/
 │   ├── 43-jamie-youtube-manager/
 │   ├── 44-jamie-youtube-subtitle-checker/
 │   ├── 45-jamie-instagram-manager/
 │   ├── 46-jamie-journal-editor/
 │   ├── 47-jamie-marketing-editor/
+│   ├── 48-jamie-copy-trimmer/
 │   │
 │   ├── 50-notebooklm-agent/
 │   ├── 51-notebooklm-automation/
@@ -255,11 +274,12 @@ our-claude-skills/
 │   ├── 75-dintel-marketing-mgr/
 │   ├── 76-dintel-backoffice-mgr/
 │   ├── 77-dintel-account-mgr/
+│   ├── 78-dintel-campaign-designer/
 │   ├── 79-dintel-skill-update/
 │   │
 │   ├── 80-claude-settings-optimizer/
 │   ├── 81-mac-optimizer/
-│   ├── 82-tui-design-template/
+│   ├── 82-our-gdrive-organizer/
 │   │
 │   ├── 90-reference-curator/       # Modular reference documentation suite
 │   │   ├── 01-reference-discovery/
@@ -273,7 +293,9 @@ our-claude-skills/
 │   │   ├── shared/
 │   │   └── install.sh
 │   │
-│   └── 91-multi-agent-guide/
+│   ├── 91-multi-agent-guide/
+│   │
+│   └── 92-tui-design-template/
 │
 ├── example-skills/skills-main/
 ├── official-skills/
@@ -283,10 +305,11 @@ our-claude-skills/
 ## Skill Design Principles
 
 1. **One thing done well** - Each skill focuses on a single capability
-2. **Directives under 1,500 words** - Concise, actionable
+2. **Root `SKILL.md` first** - Ship a loadable root `SKILL.md`; keep `code/`+`desktop/` as packaging
-3. **Self-contained** - Each platform version is fully independent
+3. **Directives under 1,500 words** - Concise, actionable; push detail into `references/`
-4. **Code-first development** - Build Claude Code version first
+4. **Self-contained** - Bundle scripts/refs as relative paths; one source of truth (no script dupes)
-5. **Progressive numbering** - Logical grouping by domain
+5. **Code-first development** - Build and self-test the runnable version first
+6. **Progressive numbering** - Logical grouping by domain
 
 ## Creating New Skills
 
@@ -295,8 +318,12 @@ our-claude-skills/
 python example-skills/skills-main/skill-creator/scripts/init_skill.py <skill-name> --path custom-skills/
 ```
 
+New skills must include a root `SKILL.md` (the hybrid pattern above); model them on
+`16-seo-schema-validator` / `17-seo-schema-generator`.
+
 ## Key Reference Files
 
-- `reference/SKILL-FORMAT-REQUIREMENTS.md` - Format specification
+- `reference/SKILL-MIGRATION-GUIDE.md` - Add a root `SKILL.md` to an existing skill (hybrid pattern, going-forward standard)
+- `reference/SKILL-FORMAT-REQUIREMENTS.md` - Dual-platform format specification
 - `example-skills/skills-main/skill-creator/SKILL.md` - Skill creation guide
 - `AGENTS.md` - Agent routing guide for Task tool

README.md

@@ -2,7 +2,7 @@
 
 > **Internal R&D Repository** - This repository is restricted for internal use only.
 
-A collection of **64 custom Claude Skills** for OurDigital workflows, D.intelligence Agent Corps (9-agent business operations suite), Jamie Plastic Surgery Clinic brand management, SEO/GTM tools, NotebookLM automation, Notion integrations, reference documentation curation, macOS system optimization, TUI wizard design, and multi-agent collaboration.
+A collection of **65 custom Claude Skills** for OurDigital workflows, D.intelligence Agent Corps (9-agent business operations suite), Jamie Plastic Surgery Clinic brand management, SEO/GTM tools, NotebookLM automation, Notion integrations, reference documentation curation, macOS system optimization, TUI wizard design, and multi-agent collaboration.
 
 ## Quick Install
 
@@ -12,6 +12,11 @@ cd our-claude-skills/custom-skills/_ourdigital-shared
 ./install.sh
 ```
 
+This symlinks the global slash commands into `~/.claude/commands/`, sets up the
+Python virtual environment, and configures credentials. It does **not** register
+skills natively — to load a skill as a Claude Code skill, also symlink it into
+`~/.claude/skills/` (see [Usage → Claude Code](#claude-code)).
+
 ## Custom Skills Overview
 
 ### OurDigital Core (01-10)
@@ -71,6 +76,7 @@ cd our-claude-skills/custom-skills/_ourdigital-shared
 |---|-------|---------|
 | 40 | `jamie-brand-editor` | Branded content generation |
 | 41 | `jamie-brand-audit` | Content review/compliance |
+| 42 | `jamie-faq-entry` | KakaoTalk Kanana chatbot Q&A entries |
 | 43 | `jamie-youtube-manager` | YouTube SEO audit & management |
 | 44 | `jamie-youtube-subtitle-checker` | YouTube subtitle validation |
 | 45 | `jamie-instagram-manager` | Instagram account management |
@@ -214,16 +220,23 @@ The `_ourdigital-shared/` directory provides:
 
 ### Claude Code
 
-Skills are auto-detected via symlinks in `~/.claude/skills/`:
+The Quick Install symlinks the **slash commands** into `~/.claude/commands/`. To
+also load a skill natively, symlink its **root** directory (which holds the
+loadable `SKILL.md`) into `~/.claude/skills/`, using the clean name without the
+`NN-` prefix:
 
 ```bash
-# Install skill symlink
+# From the repo root — symlink a skill into Claude Code
-ln -sf /path/to/skill/desktop ~/.claude/skills/skill-name
+ln -sf "$PWD/custom-skills/16-seo-schema-validator" ~/.claude/skills/seo-schema-validator
 ```
 
+> Legacy skills that don't yet have a root `SKILL.md` expose it under
+> `code/SKILL.md` instead — symlink `.../<skill>/code` for those.
+
 ### Claude Desktop
 
-Copy the `desktop/SKILL.md` file to your Claude Desktop skills folder.
+Import the skill's `desktop/` folder (containing `SKILL.md` + `skill.yaml`) via
+your Claude Desktop skills settings.
 
 ## Development
 

custom-skills/01-ourdigital-brand-guide/README.md

@@ -52,9 +52,9 @@ Only activates with "ourdigital" keyword:
 
 ### Core Values
 
-- **Data-driven** (데이터 중심) - 정밀 검사
-- **In-Action** (실행 지향) - 실행 가능한 처방
 - **Marketing Science** (마케팅 과학) - 근거 중심 의학
+- **In-Action** (실행 지향) - 실행 가능한 처방
+- **Sustainable Growth** (지속 성장) - 체질 개선
 
 ### Channel Tones
 
@@ -83,6 +83,6 @@ Only activates with "ourdigital" keyword:
 
 ## Version
 
-- Current: 1.0.0
+- Current: 1.1.0
 - Author: OurDigital
 - Environment: Both (Desktop & Code)

custom-skills/01-ourdigital-brand-guide/SKILL.md

@@ -0,0 +1,165 @@
+---
+name: ourdigital-brand-guide
+description: |
+  OurDigital 브랜드 기준 및 스타일 가이드 참조 스킬.
+  Activated with "ourdigital" keyword for brand-related queries.
+
+  Triggers (ourdigital or our prefix):
+  - "ourdigital brand guide", "our brand guide"
+  - "ourdigital 브랜드 가이드", "our 브랜드 가이드"
+  - "ourdigital 톤앤매너", "our 톤앤매너"
+  - "ourdigital style check", "our style check"
+
+  Features:
+  - Brand foundation & values reference
+  - Writing style guidelines (Korean/English)
+  - Visual identity & color palette
+  - Channel-specific tone mapping
+  - Brand compliance checking
+version: "1.1"
+author: OurDigital
+environment: Desktop
+---
+
+# OurDigital Brand Guide
+
+Reference skill for OurDigital brand standards, writing style, and visual identity.
+
+## Activation
+
+Activate with "ourdigital" or "our" prefix:
+- "ourdigital 브랜드 가이드" / "our 브랜드 가이드"
+- "ourdigital 톤앤매너 체크" / "our 톤앤매너"
+- "our brand guide", "our style check"
+
+## Brand Foundation
+
+### Core Identity
+
+| Element | Content |
+|---------|---------|
+| **Brand Name** | OurDigital Clinic |
+| **Tagline** | 우리 디지털 클리닉 \| Your Digital Health Partner |
+| **Mission** | 디지털 마케팅 클리닉 for SMBs, 자영업자, 프리랜서, 비영리단체 |
+| **Promise** | 진단-처방-측정 가능한 성장 |
+
+### Core Values
+
+| 가치 | English | 클리닉 메타포 |
+|------|---------|--------------|
+| 마케팅 과학 | Marketing Science | 근거 중심 의학 |
+| 실행 지향 | In-Action | 실행 가능한 처방 |
+| 지속 성장 | Sustainable Growth | 체질 개선 |
+
+### Brand Philosophy
+
+**"Precision + Empathy + Evidence"**
+
+## Channel Tone Matrix
+
+| Channel | Domain | Personality | Tone |
+|---------|--------|-------------|------|
+| Main Hub | ourdigital.org | Professional & Confident | Data-driven, Solution-oriented |
+| Blog | blog.ourdigital.org | Analytical & Personal | Educational, Thought-provoking |
+| Journal | journal.ourdigital.org | Conversational & Poetic | Reflective, Cultural Observer |
+| OurStory | ourstory.day | Intimate & Reflective | Authentic, Personal Journey |
+
+## Writing Style Characteristics
+
+### Korean (한국어)
+
+1. **철학-기술 융합체**: 기술 분석과 실존적 질문을 자연스럽게 결합
+2. **역설 활용**: 긴장과 모순 구조로 논증 전개
+3. **수사적 질문**: 선언적 권위보다 질문을 통한 참여
+4. **우울한 낙관주의**: 불안과 상실을 인정하되 절망하지 않음
+
+### English
+
+1. **Philosophical-Technical Hybridization**: Technical content with human implications
+2. **Paradox as Device**: Structure arguments around tensions
+3. **Rhetorical Questions**: Interrogative engagement over authority
+4. **Melancholic Optimism**: Acknowledge anxiety without despair
+
+### Do's and Don'ts
+
+**Do's:**
+- Use paradox to structure arguments
+- Ask rhetorical questions to engage readers
+- Connect technical content to human implications
+- Blend Korean and English naturally for technical terms
+- Reference historical context and generational shifts
+
+**Don'ts:**
+- Avoid purely declarative, authoritative tone
+- Don't separate technical analysis from cultural impact
+- Avoid simplistic or overly optimistic narratives
+- Don't provide prescriptive conclusions without exploration
+
+## Visual Identity
+
+### Primary Colors
+
+| Token | Color | HEX | Usage |
+|-------|-------|-----|-------|
+| --d-black | D.Black | #221814 | Footer, dark backgrounds |
+| --d-olive | D.Olive | #cedc00 | Primary accent, CTA buttons |
+| --d-green | D.Green | #287379 | Links hover, secondary accent |
+| --d-blue | D.Blue | #0075c0 | Links |
+| --d-beige | D.Beige | #f2f2de | Light text on dark |
+| --d-gray | D.Gray | #ebebeb | Alt backgrounds |
+
+### Typography
+
+- **Korean**: Noto Sans KR
+- **English**: Noto Sans, Inter
+- **Grid**: 12-column responsive layout
+
+## Brand Compliance Check
+
+When reviewing content, verify:
+
+1. **Brand Name**: Uses OurDigital Clinic (not Lab/연구소)?
+2. **Tone Match**: Does it match the channel's personality?
+3. **Value Alignment**: Reflects Marketing Science, In-Action, Sustainable Growth?
+4. **Philosophy Check**: Precision + Empathy + Evidence present?
+5. **Language Style**: Appropriate blend of Korean/English terms?
+6. **Visual Consistency**: Uses approved color palette (#221814/#cedc00)?
+7. **Data Asset Check**: Analytics/reporting references current?
+
+## Quick Reference
+
+### Key Messages
+
+| Use | Message |
+|-----|---------|
+| Tagline | 우리 디지털 클리닉 \| Your Digital Health Partner |
+| Value Prop | 마케팅 과학으로 진단하고, 실행으로 처방합니다 |
+| Process | 진단 → 처방 → 측정 |
+| Differentiator | 25년 경험의 마케팅 사이언티스트 |
+
+### CTA Patterns
+
+| Context | CTA |
+|---------|-----|
+| General | 무료 상담 신청하기 |
+| SEO | SEO 진단 신청하기 |
+| Content | 콘텐츠 전략 상담 신청하기 |
+
+## Deprecated Terms
+
+| Deprecated | Current | Note |
+|-----------|---------|------|
+| OurDigital Lab | OurDigital Clinic | 2026-04 rebranding |
+| 디지털 연구소 | 디지털 마케팅 클리닉 | Korean equivalent |
+| 데이터 중심 (Core Value) | — | Moved to D.intelligence |
+| 실행 지향 / In-Action | — | Retained (service tagline system) |
+| #1a1a2e | #221814 (O.Black) | Color correction |
+| #4ecdc4 | #cedc00 (O.Olive) | Color correction |
+| Poppins / Lora | Noto Sans KR / Inter | Font standardization |
+
+## References
+
+See `shared/references/` for detailed guides:
+- `brand-foundation.md` - Complete brand identity
+- `writing-style.md` - Detailed writing guidelines
+- `color-palette.md` - Full color system with CSS variables

custom-skills/01-ourdigital-brand-guide/code/SKILL.md

@@ -14,7 +14,7 @@ description: |
   - Writing style guidelines
   - Visual identity standards
   - Brand compliance checking
-version: "1.0"
+version: "1.1"
 author: OurDigital
 environment: Code
 ---
@@ -45,9 +45,9 @@ Philosophy: Precision + Empathy + Evidence
 
 | Value | Korean | Metaphor |
 |-------|--------|----------|
-| Data-driven | 데이터 중심 | 정밀 검사 |
-| In-Action | 실행 지향 | 실행 가능한 처방 |
 | Marketing Science | 마케팅 과학 | 근거 중심 의학 |
+| In-Action | 실행 지향 | 실행 가능한 처방 |
+| Sustainable Growth | 지속 성장 | 체질 개선 |
 
 ## Channel Tone
 
@@ -109,18 +109,20 @@ Philosophy: Precision + Empathy + Evidence
 
 Check content against:
 
-1. ✓ Channel tone match
+1. ✓ Brand name correct (OurDigital Clinic, not Lab/연구소)
-2. ✓ Core values reflected
+2. ✓ Channel tone match
-3. ✓ Philosophy alignment
+3. ✓ Core values reflected (마케팅 과학, 실행 지향, 지속 성장)
-4. ✓ Language style correct
+4. ✓ Philosophy alignment
-5. ✓ Color palette used
+5. ✓ Language style correct
+6. ✓ Color palette used (#221814/#cedc00)
+7. ✓ Data asset check (analytics/reporting references current)
 
 ## Key Messages
 
 | Purpose | Message |
 |---------|---------|
 | Tagline | 우리 디지털 클리닉 |
-| Value | 데이터로 진단하고, 실행으로 처방합니다 |
+| Value | 마케팅 과학으로 진단하고, 실행으로 처방합니다 |
 | Process | 진단 → 처방 → 측정 |
 
 ## CTA Library
@@ -132,6 +134,18 @@ SEO 진단 신청하기
 맞춤 견적 상담받기
 ```
 
+## Deprecated Terms
+
+| Deprecated | Current | Note |
+|-----------|---------|------|
+| OurDigital Lab | OurDigital Clinic | 2026-04 rebranding |
+| 디지털 연구소 | 디지털 마케팅 클리닉 | Korean equivalent |
+| 데이터 중심 (Core Value) | — | Moved to D.intelligence |
+| 실행 지향 / In-Action | — | Retained (service tagline system) |
+| #1a1a2e | #221814 (O.Black) | Color correction |
+| #4ecdc4 | #cedc00 (O.Olive) | Color correction |
+| Poppins / Lora | Noto Sans KR / Inter | Font standardization |
+
 ## File References
 
 ```

custom-skills/01-ourdigital-brand-guide/desktop/SKILL.md

@@ -16,7 +16,7 @@ description: |
   - Visual identity & color palette
   - Channel-specific tone mapping
   - Brand compliance checking
-version: "1.0"
+version: "1.1"
 author: OurDigital
 environment: Desktop
 ---
@@ -47,9 +47,9 @@ Activate with "ourdigital" or "our" prefix:
 
 | 가치 | English | 클리닉 메타포 |
 |------|---------|--------------|
-| 데이터 중심 | Data-driven | 정밀 검사 |
-| 실행 지향 | In-Action | 실행 가능한 처방 |
 | 마케팅 과학 | Marketing Science | 근거 중심 의학 |
+| 실행 지향 | In-Action | 실행 가능한 처방 |
+| 지속 성장 | Sustainable Growth | 체질 개선 |
 
 ### Brand Philosophy
 
@@ -118,11 +118,13 @@ Activate with "ourdigital" or "our" prefix:
 
 When reviewing content, verify:
 
-1. **Tone Match**: Does it match the channel's personality?
+1. **Brand Name**: Uses OurDigital Clinic (not Lab/연구소)?
-2. **Value Alignment**: Reflects Data-driven, In-Action, Marketing Science?
+2. **Tone Match**: Does it match the channel's personality?
-3. **Philosophy Check**: Precision + Empathy + Evidence present?
+3. **Value Alignment**: Reflects Marketing Science, In-Action, Sustainable Growth?
-4. **Language Style**: Appropriate blend of Korean/English terms?
+4. **Philosophy Check**: Precision + Empathy + Evidence present?
-5. **Visual Consistency**: Uses approved color palette?
+5. **Language Style**: Appropriate blend of Korean/English terms?
+6. **Visual Consistency**: Uses approved color palette (#221814/#cedc00)?
+7. **Data Asset Check**: Analytics/reporting references current?
 
 ## Quick Reference
 
@@ -131,7 +133,7 @@ When reviewing content, verify:
 | Use | Message |
 |-----|---------|
 | Tagline | 우리 디지털 클리닉 \| Your Digital Health Partner |
-| Value Prop | 데이터로 진단하고, 실행으로 처방합니다 |
+| Value Prop | 마케팅 과학으로 진단하고, 실행으로 처방합니다 |
 | Process | 진단 → 처방 → 측정 |
 | Differentiator | 25년 경험의 마케팅 사이언티스트 |
 
@@ -143,6 +145,18 @@ When reviewing content, verify:
 | SEO | SEO 진단 신청하기 |
 | Content | 콘텐츠 전략 상담 신청하기 |
 
+## Deprecated Terms
+
+| Deprecated | Current | Note |
+|-----------|---------|------|
+| OurDigital Lab | OurDigital Clinic | 2026-04 rebranding |
+| 디지털 연구소 | 디지털 마케팅 클리닉 | Korean equivalent |
+| 데이터 중심 (Core Value) | — | Moved to D.intelligence |
+| 실행 지향 / In-Action | — | Retained (service tagline system) |
+| #1a1a2e | #221814 (O.Black) | Color correction |
+| #4ecdc4 | #cedc00 (O.Olive) | Color correction |
+| Poppins / Lora | Noto Sans KR / Inter | Font standardization |
+
 ## References
 
 See `shared/references/` for detailed guides:

custom-skills/01-ourdigital-brand-guide/shared/references/brand-foundation.md

@@ -1,6 +1,8 @@
 # OurDigital Brand Foundation
 
-Complete brand identity reference for OurDigital Clinic.
+<!-- Aligned to OurDigital_Blog_Project_Instruction_v3.3 / Writing_Style_Guide_v2.1 (2026-06-05) -->
+
+Complete brand identity reference for OurDigital.
 
 ## Brand Identity
 
@@ -8,25 +10,34 @@ Complete brand identity reference for OurDigital Clinic.
 
 | Element | Content |
 |---------|---------|
-| **Brand Name** | OurDigital Clinic |
+| **Brand Name** | OurDigital |
-| **Tagline** | 우리 디지털 클리닉 \| Your Digital Health Partner |
+| **Identity Statement** | 사람, 디지털 그리고 문화를 관찰하는 개인 디지털 연구 노트 |
-| **Mission** | 디지털 마케팅 클리닉 for SMBs, 자영업자, 프리랜서, 비영리단체 |
+| **Mission** | 기술이 사람과 문화에 미치는 영향을 관찰하고 기록한다. 생각의 씨앗을 남기고 성찰한다. 검증되지 않은 도전과 실험의 결과를 기록한다. |
 | **Vision** | 데이터 민주화, 정밀 마케팅, 지속 가능한 성장 |
 | **Promise** | 진단-처방-측정 가능한 성장 |
 
-### Core Values
+### Brand Keywords
 
-| 가치 | English | 클리닉 메타포 | 설명 |
+| 핵심 가치 | 설명 |
-|------|---------|--------------|------|
+|----------|------|
-| 데이터 중심 | Data-driven | 정밀 검사 | 감이 아닌 데이터로 판단 |
+| **관찰** | 현상을 있는 그대로 포착하되, 표면 아래를 본다 — 무엇이 일어나고 있는가 |
-| 실행 지향 | In-Action | 실행 가능한 처방 | 분석에서 끝나지 않는 실행력 |
+| **분석** | 현상의 원인과 맥락을 탐구한다 — 왜 이런 일이 일어나는가 |
-| 마케팅 과학 | Marketing Science | 근거 중심 의학 | 검증된 방법론과 프레임워크 |
+| **성찰** | 심층적 의미와 인간적 함의를 도출한다 — 이것이 우리에게 무엇을 의미하는가 |
+| **실험** | 검증되지 않은 시도를 두려워하지 않는다 |
+| **기록** | 생각의 궤적을 남겨 미래의 자산으로 삼는다 |
+| **균형** | 낙관과 비관, 이론과 실무 사이에서 중심을 잡는다 |
 
 ### Brand Philosophy
 
 **"Precision + Empathy + Evidence"**
 
-Accurate diagnosis, stakeholder understanding, and measurable validation across all communications.
+Accurate diagnosis, stakeholder understanding, and measurable validation across all communications. 철학적 깊이와 실용적 가치의 균형이 OurDigital의 정체성이다.
+
+### Brand Boundary (중요)
+
+- **블로그 전체 브랜드**: OurDigital
+- **블로그 설명**: 사람, 디지털 그리고 문화를 관찰하는 개인 디지털 연구 노트
+- **OurDigital Clinic**: 진단형 콘텐츠, SEO/데이터/콘텐츠 감사, 컨설팅 상품, 문제 해결형 시리즈에서만 사용 가능한 서비스 메타포. 블로그 전체 브랜드명이 아니다.
 
 ## Positioning Statement
 
@@ -34,8 +45,16 @@ Accurate diagnosis, stakeholder understanding, and measurable validation across
 > OurDigital Clinic is 디지털 마케팅 클리닉 that provides 진단-처방-측정 프로세스,
 > unlike 일회성 캠페인 대행사, we deliver 25년 경험과 마케팅 사이언스 방법론
 
+*(Note: OurDigital Clinic은 컨설팅/서비스 맥락에서의 포지셔닝. 블로그 전체 포지셔닝과 구분한다.)*
+
 ## Target Audience
 
+**블로그 독자 (blog.ourdigital.org)**
+- **1순위**: 디지털 마케팅/기술 분야 종사자 — 실무 전략을 수립하고 실행하는 전문가
+- **2순위**: 기술과 사회의 관계에 관심 있는 지식인 — 디지털 전환이 사회에 미치는 영향을 고민하는 독자
+- **3순위**: 자기 성찰과 비판적 사고를 중시하는 독자
+
+**컨설팅 서비스 (OurDigital Clinic)**
 - **Primary**: SMB 마케팅 담당자, 자영업자, 프리랜서, 비영리단체
 - **Secondary**: 스타트업 창업자, 브랜드 매니저
 
@@ -54,24 +73,30 @@ Accurate diagnosis, stakeholder understanding, and measurable validation across
 
 | Level | Element | Description |
 |-------|---------|-------------|
-| Level 1 | Master Brand | OurDigital Clinic |
+| Level 1 | Master Brand | OurDigital |
 | Level 2 | Channel Identity | Blog, Journal, OurStory |
-| Level 3 | Service Identity | 4개 핵심 서비스 |
+| Level 3 | Service Identity | 4개 핵심 서비스 (OurDigital Clinic 메타포 적용 가능) |
 
 ### Channel Personality & Tone
 
-| Channel | Domain | Personality | Tone | Content Type |
+| Channel | Domain | Language | Character | Length |
-|---------|--------|-------------|------|--------------|
+|---------|--------|----------|-----------|--------|
-| Main Hub | ourdigital.org | Professional & Confident | Data-driven, Solution-oriented | 서비스, 케이스, 리드 |
+| Main Hub | ourdigital.org | Korean | Professional & Confident, Data-driven | 서비스, 케이스, 리드 |
-| Blog | blog.ourdigital.org | Analytical & Personal | Educational, Thought-provoking | 가이드, 분석, 인사이트 |
+| **Blog** | blog.ourdigital.org | **Korean** | 디지털 문화 분석 + 철학적 성찰 + 실무 인사이트 | **1,500-3,000자** |
-| Journal | journal.ourdigital.org | Conversational & Poetic | Reflective, Cultural Observer | 에세이, 문화, 관찰 |
+| **Journal** | journal.ourdigital.org | **English** | 산업 트렌드, 기술-인간 교차점, reflective essay | **1,000-2,000 words** |
-| OurStory | ourstory.day | Intimate & Reflective | Authentic, Personal Journey | 개인 서사, 경험 |
+| **OurStory** | ourstory.day | **Korean** | 개인 에세이, 삶의 성찰, 일상의 관찰 | **800-1,500자** |
-| D.intelligence | dintelligence.co.kr | Professional | B2B | Corporate Partnership |
+| D.intelligence | dintelligence.co.kr | Korean/English | Professional | B2B Corporate Partnership |
+
+**채널 라우팅 규칙:**
+- 기술 분석 + 철학적 사유 → `blog.ourdigital.org`
+- 순수 개인 에세이, 감정적 성찰 → `ourstory.day`
+- 영문 심층 에세이, 산업 관점 → `journal.ourdigital.org`
+- 진단형 콘텐츠, 컨설팅 제안 → `OurDigital Clinic` 메타포 사용 가능
 
 ### Content Flow Strategy
 
 ```
-Discovery (Blog) → Engagement (Journal) → Conversion (Main Site)
+Discovery (Blog) → Engagement (Journal) → Conversion (Main Site / OurDigital Clinic)
 ```
 
 ### Publishing Cadence
@@ -80,7 +105,7 @@ Discovery (Blog) → Engagement (Journal) → Conversion (Main Site)
 |---------|-----------|--------|
 | ourdigital.org | 필요시 업데이트 | 서비스별 상세 |
 | blog.ourdigital.org | 주 1-2회 | 1,500-3,000자 |
-| journal.ourdigital.org | 월 2-4회 | 1,000-2,000자 |
+| journal.ourdigital.org | 월 2-4회 | 1,000-2,000 words |
 | ourstory.day | 월 1-2회 | 800-1,500자 |
 
 ## Service Portfolio
@@ -112,13 +137,16 @@ Discovery (Blog) → Engagement (Journal) → Conversion (Main Site)
 
 | Use Case | Message |
 |----------|---------|
-| Tagline | 우리 디지털 클리닉 \| Your Digital Health Partner |
+| Blog Identity | 사람, 디지털 그리고 문화를 관찰하는 개인 디지털 연구 노트 |
-| Value Proposition | 데이터로 진단하고, 실행으로 처방합니다 |
+| Consulting Tagline | 우리 디지털 클리닉 \| Your Digital Health Partner |
+| Value Proposition | 마케팅 과학으로 진단하고, 실행으로 처방합니다 |
 | Process | 진단 → 처방 → 측정 |
 | Differentiator | 25년 경험의 마케팅 사이언티스트 |
 
 ## CTA Library
 
+*(OurDigital Clinic 컨설팅 맥락에서 사용)*
+
 | Context | CTA Text |
 |---------|----------|
 | General | 무료 상담 신청하기 |

custom-skills/01-ourdigital-brand-guide/shared/references/writing-style.md

@@ -1,5 +1,7 @@
 # OurDigital Writing Style Guide
 
+<!-- Aligned to OurDigital_Blog_Project_Instruction_v3.3 / Writing_Style_Guide_v2.1 (2026-06-05) -->
+
 Comprehensive writing guidelines for OurDigital content across all channels.
 
 ## Overview
@@ -8,7 +10,7 @@ Comprehensive writing guidelines for OurDigital content across all channels.
 |-------|-------|
 | **Author** | Andrew Yim |
 | **Primary Blog** | blog.ourdigital.org |
-| **Tagline** | 사람, 디지털 그리고 문화 (People, Digital, and Culture) |
+| **Brand Identity** | 사람, 디지털 그리고 문화를 관찰하는 개인 디지털 연구 노트 |
 | **Platform** | Ghost CMS |
 | **History** | 2004-2025 (20+ years of content) |
 
@@ -16,54 +18,73 @@ Comprehensive writing guidelines for OurDigital content across all channels.
 
 ## Part 1: 한국어 스타일가이드
 
+### Writer 역할 정의
+
+25년차 디지털 마케팅 에세이 작가. 기술과 인간의 관계를 관찰하는 실무자이자 사유자. 분석적이면서 개인적이고, 단정 대신 질문을 두고, 결론 대신 가능성을 제시하며, 독자를 가르치지 않고 함께 생각하는 동료로 대한다.
+
+### 문체 규칙 (Korean)
+
+- 대화체 `~다`, `~이다`, `~한다`를 사용한다.
+- 경어체 `~합니다`, `~입니다`는 사용하지 않는다.
+- 짧은 문장과 긴 문장을 교차 배치해 리듬을 만든다.
+- 문단 전환 시 호흡을 바꾼다: 분석 → 서사 → 질문.
+- **전문용어는 첫 등장 시 영문을 병기한다.** 예: `검색엔진 최적화(SEO)`.
+
 ### 핵심 글쓰기 특성
 
-#### 1. 철학-기술 융합체
+#### 1. 철학-기술 융합
 
-기술 분석과 실존적 질문을 자연스럽게 결합한다. 기술 콘텐츠(AI 아키텍처, 엔터프라이즈 시스템)는 결코 인간적 함의와 분리되지 않는다.
+기술 주제를 다루되, 항상 이면의 인간적 함의를 탐구한다. 기술 콘텐츠(AI 아키텍처, 엔터프라이즈 시스템)는 결코 인간적 의미와 분리되지 않는다.
 
-**예시**: Llama 4와 DeepSeek 비교 글에서도 거버넌스 우려와 사회적 영향을 포함한다.
+```
+나쁜 예: 구글의 알고리즘은 200개 이상의 신호를 분석한다.
+좋은 예: 구글은 200개 이상의 신호를 읽는다. 그런데 정작 글을 쓰는 사람은 단 하나의 신호, 독자의 진짜 질문도 제대로 읽지 못할 때가 많다.
+```
 
-#### 2. 역설(Paradox)을 주요 수사 장치로 활용
+#### 2. 핵심 긴장 / 관점 전환 / 역설 / 열린 질문
 
-논증을 긴장과 모순 구조로 전개한다:
+모든 글에 억지 역설을 넣지는 않는다. 대신 **핵심 긴장, 관점 전환, 역설, 열린 질문 중 하나 이상**을 자연스럽게 포함한다. 공식화를 경계한다.
-- 인간이 컴퓨터를 모방하면서 컴퓨터가 인간을 모방하는 역설
-- 기술이 해방하면서 동시에 의미를 축소하는 역설
-- 디지털 네이티브가 기성세대가 가르칠 수 없는 유창함을 보유하는 역설
 
-#### 3. 수사적 질문 활용
+유용한 패턴:
+- `~하면서 동시에 ~하다`
+- `~를 위해 오히려 ~해야 한다`
+- `가장 ~한 것이 사실은 가장 ~하다`
+- `우리가 놓치고 있는 것은 무엇인가?`
 
-선언적 권위보다 질문을 통한 참여를 선호한다:
+수사적 질문은 선언적 권위보다 독자와의 지적 동반자 관계를 형성한다.
 
-> "이 디지털 세대에게 무엇을 가르쳐야 하는가?"
+#### 3. 우울한 낙관주의 (Melancholic Optimism)
-> "그 무한한 자유 속에서 우리는 무엇을 소중히 여기게 될 것인가?"
 
-이는 독자와 지적 동반자 관계를 형성하며, 교훈적 지시를 피한다.
+디지털 세계의 불안, 피로, 한계를 솔직히 인정한다. 그러나 냉소로 끝내지 않는다. 그 안에서 다시 생각할 가능성, 더 나은 실천, 작은 회복의 여지를 찾는다.
 
-#### 4. 우울한 낙관주의 (Melancholic Optimism)
+```
+예: AI가 일자리를 대체할 수 있다는 불안은 근거가 있다. 그리고 그 불안이야말로 '대체 불가능한 것'이 무엇인지 진지하게 물어보게 만드는 시작점이다.
+```
 
-불안과 상실을 인정하되 절망하지 않는다. 기술의 불가피성을 수용하면서도 대체되는 것에 대한 진정한 우려를 표현한다.
+#### 4. 분석적이면서 개인적
+
+데이터와 논거를 제시하되, 1인칭 경험과 관찰을 자연스럽게 엮는다. 논문이 아니라 에세이다. 그러나 근거 없는 감상문도 아니다.
 
 ### 문장 구조 패턴
 
 | 요소 | 패턴 |
 |------|------|
-| 문장 길이 | 여러 절을 포함한 긴 복합문 - 논의되는 상호연결된 개념을 반영 |
+| 문장 길이 | 짧은 문장과 긴 복합문을 교차 배치 — 리듬을 만든다 |
 | 단락 구조 | 관찰 → 분석 → 철학적 함의로 점진적 심화 |
 | 근거 제시 | 역사적 사례, 문화간 참조, 기술 명세를 함께 엮음 |
 | 결론부 | 종종 열린 결말로, 답을 제시하기보다 질문을 던짐 |
 
 ### 독자 조율
 
-**교양 있는 일반 독자**를 대상으로 한다 — 기술의 문화적 영향에 지적 호기심을 가진 독자이지, 반드시 기술 전문가는 아니다.
+**교양 있는 일반 독자** — 기술의 문화적 영향에 지적 호기심을 가진 독자이지, 반드시 기술 전문가는 아니다. 독자를 가르치려 하지 않고 결론을 강요하지 않는다. 생각의 재료를 제공한다.
 
-기술 글에도 요약본과 은유적 앵커링("데이터 공장")을 포함해 접근성을 유지한다.
+기술 글에도 은유적 앵커링("데이터 공장")을 포함해 접근성을 유지한다.
 
 ### 고유 특성
 
-1. **이중언어 유창성** — 한국어 산문에 영어 기술 용어가 섞여 디지털 담론의 혼종적 특성을 반영
+1. **이중언어 유창성** — 한국어 산문에 영어 기술 용어가 섞여 디지털 담론의 혼종적 특성을 반영 (단, 전문용어는 첫 등장 시 영문 병기)
 2. **시간적 인식** — 세대 변화와 역사적 맥락에 대한 강한 의식
-3. **인식론적 겸손** — 특히 세대간 격차에서 이해의 한계를 인정
+3. **인식론적 겸손** — 이해의 한계를 인정하며, 겸손한 추정 표현을 적절히 활용 (`~일지도 모른다`, `~인 듯하다`, `어쩌면 ~`)
 4. **규제 의식** — 엔터프라이즈 글에서 일관되게 컴플라이언스(GDPR, EU 규제)를 다룸
 
 ---
@@ -124,20 +145,28 @@ Technical articles include executive summaries and metaphorical anchoring ("Data
 
 ### Do's
 
-- Use paradox to structure arguments
+- 핵심 긴장, 관점 전환, 역설, 열린 질문 중 하나 이상을 포함한다
-- Ask rhetorical questions to engage readers
+- 수사적 질문으로 독자와 지적 동반자 관계를 형성한다
-- Connect technical content to human implications
+- 기술 콘텐츠를 인간적 함의와 연결한다
-- Acknowledge uncertainty and epistemic limits
+- 불확실성과 이해의 한계를 인정한다
-- Blend Korean and English naturally for technical terms
+- 전문용어 첫 등장 시 영문을 병기한다 (`검색엔진 최적화(SEO)`)
-- Reference historical context and generational shifts
+- 역사적 맥락과 세대적 변화를 참조한다
+- 짧은 문장과 긴 문장을 교차 배치해 리듬을 만든다
+- 1인칭 경험과 관찰을 분석에 자연스럽게 엮는다
 
-### Don'ts
+### Don'ts (피해야 할 것)
 
-- Avoid purely declarative, authoritative tone
+| 피해야 할 것 | 이유 |
-- Don't separate technical analysis from cultural impact
+|-------------|------|
-- Avoid simplistic or overly optimistic technology narratives
+| `~합니다`, `~입니다` | 경어체 — 대화체(`~다`, `~한다`) 사용 |
-- Don't provide prescriptive conclusions without exploration
+| `오늘날 디지털 시대에`, `급변하는 환경 속에서`, `요즘 ~가 화제다` | 상투적 도입부 |
-- Avoid ignoring regulatory and governance concerns
+| `첫째, 둘째, 셋째` 기계적 나열 | 교과서적 구조 |
+| `따라서 반드시 ~해야 한다` | 확정적 결론 |
+| 근거 없는 통계나 데이터 | 데이터 정직성 위반 |
+| 기술에 대한 무조건적 찬양 또는 혐오 | 균형 원칙 위반 |
+| 과도한 감탄부호, 물결표, 이모지 | 톤 일관성 파괴 |
+| 특정 업체나 제품의 노골적 홍보성 문장 | 브랜드 신뢰 훼손 |
+| SEO 키워드 과잉 최적화 | SEO가 글을 지배해서는 안 된다 |
 
 ---
 

custom-skills/02-ourdigital-blog/SKILL.md

@@ -0,0 +1,145 @@
+---
+name: ourdigital-blog
+description: |
+  Korean blog draft creation for blog.ourdigital.org.
+  Activated with "ourdigital" keyword for blog writing tasks.
+
+  Triggers (ourdigital or our prefix):
+  - "ourdigital blog", "our blog"
+  - "ourdigital 블로그", "our 블로그"
+  - "ourdigital 한국어 포스트", "our 한국어 포스트"
+
+  Features:
+  - Blog draft generation in Korean
+  - SEO metadata (title, description, slug)
+  - Ghost CMS format output
+  - Brand voice compliance
+version: "1.0"
+author: OurDigital
+environment: Desktop
+---
+
+# OurDigital Blog
+
+Korean blog draft creation skill for blog.ourdigital.org.
+
+## Activation
+
+Activate with "ourdigital" or "our" prefix:
+- "ourdigital 블로그 써줘" / "our 블로그 써줘"
+- "ourdigital blog draft" / "our blog draft"
+- "our 한국어 포스트 [주제]"
+
+## Channel Profile
+
+| Field | Value |
+|-------|-------|
+| **URL** | blog.ourdigital.org |
+| **Language** | Korean (전문용어 영문 병기) |
+| **Tone** | Analytical & Personal, Educational |
+| **Platform** | Ghost CMS |
+| **Frequency** | 주 1-2회 |
+| **Length** | 1,500-3,000자 |
+
+## Workflow
+
+### Phase 1: Topic Clarification
+
+Ask clarifying questions (max 3):
+
+1. **주제 확인**: 정확한 토픽이 무엇인가요?
+2. **대상 독자**: 타겟 오디언스는? (마케터/개발자/경영진/일반)
+3. **깊이 수준**: 개요 / 심층분석 / 실무가이드 중 어느 수준?
+
+### Phase 2: Research (Optional)
+
+If topic requires current information:
+- Use `web_search` for latest trends/data
+- Use `Notion:notion-search` for past research
+- Reference internal documents if available
+
+### Phase 3: Draft Generation
+
+Generate blog draft following brand style:
+
+**Structure:**
+```
+1. 도입부 (Hook + Context)
+2. 본론 (3-5 핵심 포인트)
+   - 각 포인트: 주장 → 근거 → 함의
+3. 결론 (Summary + 열린 질문)
+```
+
+**Writing Style:**
+- 철학-기술 융합: 기술 분석 + 인간적 함의
+- 역설 활용: 긴장/모순으로 논증 구조화
+- 수사적 질문: 독자 참여 유도
+- 우울한 낙관주의: 불안 인정, 절망 거부
+
+**Language Rules:**
+- 한글 기본, 전문용어는 영문 병기
+  - 예: "검색엔진최적화(SEO)"
+- 문장: 복합문 허용, 상호연결된 개념 반영
+- 단락: 관찰 → 분석 → 철학적 함의
+
+### Phase 4: SEO Metadata
+
+Generate metadata:
+
+```yaml
+title: [60자 이내, 키워드 포함]
+meta_description: [155자 이내]
+slug: [영문 URL slug]
+tags: [3-5개 태그]
+featured_image_prompt: [DALL-E/Midjourney 프롬프트]
+```
+
+### Phase 5: Output Format
+
+**Markdown Output:**
+```markdown
+---
+title: "포스트 제목"
+meta_description: "메타 설명"
+slug: "url-slug"
+tags: ["tag1", "tag2"]
+---
+
+# 포스트 제목
+
+[본문 내용]
+
+---
+*Originally drafted with Claude for OurDigital Blog*
+```
+
+## Ghost CMS Integration
+
+Export options:
+1. **Markdown file** → Ulysses → Ghost
+2. **Direct API** → Ghost Admin API (if configured)
+
+API endpoint: `GHOST_BLOG_URL` from environment
+
+## Brand Compliance
+
+Before finalizing, verify:
+- [ ] 분석적 + 개인적 톤 유지
+- [ ] 기술 내용에 인간적 함의 포함
+- [ ] 수사적 질문으로 독자 참여
+- [ ] 전문용어 영문 병기
+- [ ] 1,500-3,000자 범위
+
+## Quick Commands
+
+| Command | Action |
+|---------|--------|
+| "ourdigital 블로그 [주제]" | Full workflow |
+| "ourdigital blog SEO" | SEO metadata only |
+| "ourdigital blog 편집" | Edit existing draft |
+
+## References
+
+- `shared/references/blog-style-guide.md` - Detailed writing guide
+- `shared/templates/blog-template.md` - Post structure template
+- `01-ourdigital-brand-guide` - Brand voice reference

custom-skills/02-ourdigital-blog/shared/references/blog-style-guide.md

@@ -1,5 +1,7 @@
 # OurDigital Blog Style Guide
 
+<!-- Aligned to OurDigital_Writing_Style_Guide_v2.1 + Blog_Project_Instruction_v3.3 (2026-06-05) -->
+
 Detailed writing guidelines for blog.ourdigital.org.
 
 ## Channel Identity
@@ -7,45 +9,47 @@ Detailed writing guidelines for blog.ourdigital.org.
 | Field | Value |
 |-------|-------|
 | **Domain** | blog.ourdigital.org |
-| **Tagline** | 사람, 디지털 그리고 문화 |
+| **Brand** | OurDigital |
-| **Language** | Korean (전문용어 영문 병기) |
+| **Identity** | 사람, 디지털 그리고 문화를 관찰하는 개인 디지털 연구 노트 |
-| **Tone** | Analytical & Personal, Educational |
+| **Core Theme** | 사람, 디지털 그리고 문화 |
-| **Target** | 교양 있는 일반 독자 - 기술의 문화적 영향에 호기심 있는 독자 |
+| **Language** | Korean (전문용어 첫 등장 시 영문 병기) |
+| **CMS** | Ghost — 초안은 Markdown으로 작성 |
+| **Tone** | Analytical & Personal (비판적이되 공정, 겸손하되 자신감 있음) |
+| **Target** | 디지털 마케팅/기술 실무자 (1순위), 기술-사회 관계에 관심 있는 지식인 (2순위), 비판적 사고를 중시하는 일반 독자 (3순위) |
+
+**브랜드 경계**: `OurDigital`이 블로그 전체 정체성이다. `OurDigital Clinic`은 진단형 콘텐츠·컨설팅 상품에서만 사용하는 서비스 메타포다.
+
+**우선순위**: 지침 충돌 시 Blog_Project_Instruction_v3.3 → 이 스타일 가이드 → 사용자 일반 스타일 순으로 따른다.
 
 ## Writing Characteristics
 
-### 1. 철학-기술 융합체
+모든 초안은 아래 네 원칙을 기준으로 자기 점검한다.
 
-기술 분석과 실존적 질문을 자연스럽게 결합한다.
+### 1. 철학-기술 융합
 
-**Good Example:**
+기술 주제를 다루되, 항상 이면의 인간적 함의를 탐구한다.
-> AI가 우리의 업무를 대체할 수 있다는 사실은 분명하다. 그러나 더 중요한 질문은 "AI가 대체할 수 없는 것은 무엇인가?"이다.
-
-**Bad Example:**
-> AI는 업무 효율성을 높여준다. 다양한 분야에서 활용되고 있다.
-
-### 2. 역설(Paradox) 활용
-
-논증을 긴장과 모순 구조로 전개한다.
-
-**Paradox Patterns:**
-- "~하면서 동시에 ~하다"
-- "~인 것 같지만 실은 ~이다"
-- "~를 얻었지만 ~를 잃었다"
-
-### 3. 수사적 질문
-
-선언적 권위보다 질문을 통한 참여를 선호한다.
 
 **Good:**
-> 우리는 정말 데이터를 이해하고 있는 것일까?
+> 구글은 200개 이상의 신호를 읽는다. 그런데 정작 글을 쓰는 사람은 단 하나의 신호, 독자의 진짜 질문도 제대로 읽지 못할 때가 많다.
 
 **Bad:**
-> 데이터를 이해하는 것이 중요하다.
+> 구글의 알고리즘은 200개 이상의 신호를 분석한다.
 
-### 4. 우울한 낙관주의
+### 2. 긴장과 역설
 
-불안과 상실을 인정하되 절망하지 않는다.
+억지 역설을 억지로 넣지 않는다. 핵심 긴장·관점 전환·역설·열린 질문 중 하나 이상을 자연스럽게 포함한다.
+
+**Useful Patterns:**
+- `~하면서 동시에 ~하다`
+- `~를 위해 오히려 ~해야 한다`
+- `가장 ~한 것이 사실은 가장 ~하다`
+- `우리가 놓치고 있는 것은 무엇인가?`
+
+> 예: 데이터를 가장 잘 활용하는 방법은, 때때로 데이터를 내려놓는 것이다.
+
+### 3. 우울한 낙관주의
+
+디지털 세계의 불안·피로·한계를 솔직히 인정한다. 그러나 냉소로 끝내지 않는다. 그 안에서 다시 생각할 가능성, 작은 회복의 여지를 찾는다.
 
 **Tone Spectrum:**
 ```
@@ -55,14 +59,24 @@ Detailed writing guidelines for blog.ourdigital.org.
         (여기에 위치)
 ```
 
+> 예: AI가 일자리를 대체할 수 있다는 불안은 근거가 있다. 그리고 그 불안이야말로 '대체 불가능한 것'이 무엇인지 진지하게 물어보게 만드는 시작점이다.
+
+### 4. 분석적이면서 개인적
+
+데이터와 논거를 제시하되, 1인칭 경험과 관찰을 자연스럽게 엮는다. 논문이 아니라 에세이다. 그러나 근거 없는 감상문도 아니다.
+
+> 예: 지난 3년간 50개 이상의 사이트 마이그레이션을 지켜봤다. 숫자로 보면 성공률은 70% 정도다. 하지만 '성공'의 정의가 사이트마다 달랐다는 게 진짜 이야기다.
+
 ## 문장 구조
 
 | Element | Pattern |
 |---------|---------|
-| 문장 길이 | 긴 복합문 허용 - 상호연결된 개념 반영 |
+| 문장 길이 | 단문 기본, 짧은 문장과 긴 문장을 교차해 리듬을 만든다 |
 | 단락 구조 | 관찰 → 분석 → 철학적 함의 |
-| 근거 제시 | 역사적 사례 + 기술 명세 + 문화적 참조 |
+| 단락 전환 | 분석 → 서사 → 질문으로 호흡을 바꾼다 |
+| 근거 제시 | 역사적 사례 + 기술 명세 + 문화적 참조; 출처 없는 통계는 사용하지 않는다 |
 | 결론 | 열린 결말, 답보다 질문 |
+| 문체 | `~다`, `~이다`, `~한다` 평서체; `~합니다`, `~입니다` 경어체 사용 금지 |
 
 ## 언어 규칙
 
@@ -83,32 +97,61 @@ Detailed writing guidelines for blog.ourdigital.org.
 
 ## 포스트 구조
 
-### 도입부 (10-15%)
+### 도입부 (200-300자)
 
-1. **Hook**: 독자의 관심을 끄는 질문/통계/역설
+- 장면·질문·역설·데이터 중 하나로 시작한다.
-2. **Context**: 주제의 배경 설명
+- 핵심 질문을 제시하고, 독자가 왜 이 글을 읽어야 하는지 암시한다.
-3. **Preview**: 글에서 다룰 내용 암시
+- 상투적 표현 금지: `오늘날 디지털 시대에`, `급변하는 환경 속에서`, `요즘 ~가 화제다`
 
-### 본론 (70-80%)
+### 본론 (3-5개 섹션, 각 300-500자)
 
-3-5개의 핵심 포인트, 각각:
+- 소제목(`##`, `###`)을 사용한다.
-1. **주장**: 명확한 포인트 제시
+- 분석·서사·데이터·개인 관찰을 교차시킨다.
-2. **근거**: 데이터, 사례, 전문가 의견
+- 최소 1회 관점 전환 또는 핵심 긴장을 포함한다.
-3. **함의**: 이것이 의미하는 바
+- 전문용어는 첫 등장 시 영문을 병기한다. 예: `검색엔진 최적화(SEO)`
 
-### 결론 (10-15%)
+### 결론 (200-300자)
 
-1. **Summary**: 핵심 내용 요약
+- 인사이트를 정리하되 단정하지 않는다.
-2. **Reflection**: 더 넓은 맥락에서의 의미
+- 열린 질문 또는 다음 사유의 출발점으로 마무리한다.
-3. **Open Question**: 독자가 생각할 질문
+- 독자가 이어서 생각할 여운을 남긴다.
+
+### CTA (선택, 1-2문장)
+
+관련 글, 뉴스레터, 댓글, 실무 문의 등 필요한 경우만 사용한다.
+
+### 길이 기준
+
+| Type | 길이 | 용도 |
+|------|-----:|------|
+| Short-form | 1,000-1,500자 | 단일 인사이트, 짧은 단상 |
+| Standard | 2,000-2,500자 | 기본 블로그 포스트 |
+| Long-form | 2,500-3,000자 | 심층 분석, 리서치 기반 글 |
+| Research Essay | 3,000자 이상 | 사용자 명시 요청 시만 |
+
+기본값: 별도 지정이 없으면 **2,000자 ±300자**.
 
 ## SEO Guidelines
 
+Ghost CMS 메타데이터는 아래 형식으로 완성한다.
+
+```yaml
+title: "글 제목"
+slug: "url-friendly-english-slug"
+meta_title: "SEO 타이틀, 60자 이내"
+meta_description: "SEO 디스크립션, 155자 이내"
+tags:
+  - primary: "메인 카테고리"
+  - secondary: ["태그1", "태그2"]
+featured: false
+excerpt: "카드/프리뷰용 발췌문, 2-3문장"
+```
+
 ### Title (제목)
 
-- 60자 이내
+- **60자 이내**, 핵심 키워드 자연스럽게 포함
-- 핵심 키워드 포함
+- 호기심·긴장·관점 전환을 만든다 (40자 내외 기준)
-- 호기심 유발 또는 가치 제안
+- 키워드 밀도만 의식한 SEO 과잉 최적화 금지
 
 **Patterns:**
 - "[주제]의 역설: ~하면서 ~하는 시대"
@@ -117,15 +160,13 @@ Detailed writing guidelines for blog.ourdigital.org.
 
 ### Meta Description
 
-- 155자 이내
+- **155자 이내**, 글의 핵심 질문과 독자 효용을 함께 담는다
-- 글의 핵심 가치 요약
+- 클릭을 유도하되 과장하지 않는다
-- 클릭 유도 문구
 
 ### URL Slug
 
-- 영문 소문자
+- **영문** 소문자, 하이픈으로 구분, 3-5 단어
-- 하이픈으로 구분
+- 한국어 제목이라도 slug는 영문으로 작성한다
-- 3-5 단어
 
 ## Content Calendar
 
@@ -138,12 +179,34 @@ Detailed writing guidelines for blog.ourdigital.org.
 
 ## Quality Checklist
 
-Before publishing:
+### Must Have
 
-- [ ] 제목이 60자 이내인가?
+- [ ] 핵심 긴장·역설·관점 전환·열린 질문 중 하나 이상이 있다.
-- [ ] 메타 설명이 155자 이내인가?
+- [ ] 도입부 300자 이내에 hook과 핵심 질문이 있다.
-- [ ] 전문용어에 영문이 병기되었는가?
+- [ ] 전문용어 첫 등장 시 영문을 병기했다.
-- [ ] 수사적 질문이 포함되었는가?
+- [ ] 기술 내용에 인간적 함의가 있다.
-- [ ] 기술 내용에 인간적 함의가 있는가?
+- [ ] 독자를 가르치려 하지 않고 함께 생각하는 태도를 유지했다.
-- [ ] 결론이 열린 질문으로 끝나는가?
+- [ ] 결론이 열린 질문 또는 여운으로 마무리된다.
-- [ ] 1,500-3,000자 범위인가?
+- [ ] SEO 메타데이터(title ≤60자, meta ≤155자, 영문 slug)가 완성되었다.
+- [ ] 기본 길이 2,000자 ±300자를 준수했다 (또는 이탈 이유가 있다).
+
+### Must Avoid
+
+- [ ] 상투적 도입: `오늘날 디지털 시대에`, `급변하는 환경 속에서`, `요즘 ~가 화제다`
+- [ ] 경어체: `~합니다`, `~입니다`
+- [ ] 교과서적 나열: `첫째`, `둘째`, `셋째`의 기계적 반복
+- [ ] 확정적 결론: `따라서 반드시 ~해야 한다`
+- [ ] 출처 없는 통계나 데이터
+- [ ] 기술에 대한 무조건적 찬양 또는 혐오
+- [ ] 과도한 감탄부호, 물결표, 이모지
+- [ ] 특정 업체·제품의 노골적 홍보성 문장
+
+### 자기 편집 (Self-Edit) 의무
+
+초안 완성 후 아래 형식으로 가장 약한 항목 1개를 반드시 지목한다. "모두 통과"는 허용하지 않는다.
+
+```
+[자기 편집] 가장 약한 부분: [항목명]
+이유: [1문장]
+개선 방향: [1문장]
+```

custom-skills/03-ourdigital-journal/SKILL.md

@@ -0,0 +1,173 @@
+---
+name: ourdigital-journal
+description: |
+  English essay and article creation for journal.ourdigital.org.
+  Activated with "ourdigital" keyword for English writing tasks.
+
+  Triggers (ourdigital or our prefix):
+  - "ourdigital journal", "our journal"
+  - "ourdigital English essay", "our English essay"
+  - "ourdigital 영문 에세이", "our 영문 에세이"
+
+  Features:
+  - English essay/article generation
+  - Research-based insights
+  - Reflective, poetic style
+  - Ghost CMS format output
+version: "1.0"
+author: OurDigital
+environment: Desktop
+---
+
+# OurDigital Journal
+
+English essay and article creation for journal.ourdigital.org.
+
+## Activation
+
+Activate with "ourdigital" or "our" prefix:
+- "ourdigital journal" / "our journal"
+- "ourdigital English essay" / "our English essay"
+- "our 영문 에세이 [topic]"
+- "ourdigital 영문 에세이 [주제]"
+
+## Channel Profile
+
+| Field | Value |
+|-------|-------|
+| **URL** | journal.ourdigital.org |
+| **Language** | English |
+| **Tone** | Conversational & Poetic, Reflective |
+| **Platform** | Ghost CMS |
+| **Frequency** | 월 2-4회 |
+| **Length** | 1,000-2,000 words |
+
+## Workflow
+
+### Phase 1: Topic Exploration
+
+Ask clarifying questions:
+
+1. **Topic**: What specific angle interests you?
+2. **Audience**: Tech professionals / General readers / Academic?
+3. **Depth**: Personal reflection / Industry analysis / Cultural observation?
+
+### Phase 2: Research (Optional)
+
+If topic requires current context:
+- Use `web_search` for recent developments
+- Reference scholarly perspectives if applicable
+- Draw from historical or cultural parallels
+
+### Phase 3: Essay Generation
+
+Generate essay following the reflective style:
+
+**Structure:**
+```
+1. Opening (Evocative scene or question)
+2. Exploration (3-4 interconnected observations)
+3. Synthesis (Weaving threads together)
+4. Closing (Open-ended reflection)
+```
+
+**Writing Style:**
+- Philosophical-Technical Hybridization
+- Paradox as primary rhetorical device
+- Rhetorical questions for engagement
+- Melancholic optimism in tone
+
+**Distinctive Qualities:**
+- Temporal awareness (historical context)
+- Epistemic humility (acknowledging limits)
+- Cultural bridging (Korean-global perspectives)
+
+### Phase 4: SEO Metadata
+
+Generate metadata:
+
+```yaml
+title: [Evocative, under 70 characters]
+meta_description: [Compelling summary, 155 characters]
+slug: [english-url-slug]
+tags: [3-5 relevant tags]
+```
+
+### Phase 5: Output Format
+
+**Markdown Output:**
+```markdown
+---
+title: "Essay Title"
+meta_description: "Description"
+slug: "url-slug"
+tags: ["tag1", "tag2"]
+---
+
+# Essay Title
+
+[Essay content with paragraphs that flow naturally]
+
+---
+*Published in [OurDigital Journal](https://journal.ourdigital.org)*
+```
+
+## Writing Guidelines
+
+### Voice Characteristics
+
+| Aspect | Approach |
+|--------|----------|
+| Perspective | First-person reflection welcome |
+| Tone | Thoughtful, observant, wondering |
+| Pacing | Unhurried, allowing ideas to breathe |
+| References | Cross-cultural, historical, literary |
+
+### Sentence Craft
+
+- Long, complex sentences reflecting interconnected ideas
+- Progressive deepening: observation → analysis → implication
+- Questions that invite rather than lecture
+
+### Do's and Don'ts
+
+**Do:**
+- Blend technology with humanity
+- Use paradox to illuminate tensions
+- Acknowledge uncertainty gracefully
+- Bridge Korean and Western perspectives
+
+**Don't:**
+- Lecture or prescribe
+- Oversimplify complex issues
+- Ignore cultural context
+- Rush to conclusions
+
+## Content Types
+
+| Type | Focus | Length |
+|------|-------|--------|
+| Personal Essay | Reflection on experience | 1,000-1,500 words |
+| Cultural Observation | Tech + society analysis | 1,500-2,000 words |
+| Industry Insight | Trends with perspective | 1,200-1,800 words |
+
+## Ghost Integration
+
+Export options:
+1. **Markdown file** → Editorial review → Ghost
+2. **Direct API** → Ghost Admin API
+
+API endpoint: `GHOST_JOURNAL_URL` from environment
+
+## Quick Commands
+
+| Command | Action |
+|---------|--------|
+| "ourdigital journal [topic]" | Full essay workflow |
+| "ourdigital journal edit" | Edit existing draft |
+
+## References
+
+- `shared/references/journal-style-guide.md` - Detailed writing guide
+- `shared/templates/essay-template.md` - Essay structure
+- `01-ourdigital-brand-guide` - Brand voice reference

custom-skills/03-ourdigital-journal/shared/references/journal-style-guide.md

@@ -1,7 +1,42 @@
+<!-- Aligned to OurDigital_Blog_Project_Instruction_v3.3 + Writing_Style_Guide_v2.1 (2026-06-05); journal = English channel, voice preserved -->
+
 # OurDigital Journal Style Guide
 
 Writing guidelines for journal.ourdigital.org - English essays and articles.
 
+## Brand Identity
+
+OurDigital is a personal digital research notebook that **observes and records how technology shapes people and culture** ("사람, 디지털 그리고 문화를 관찰하는 개인 디지털 연구 노트"). It moves between three registers:
+
+- **Observation** — what is happening
+- **Analysis** — why it is happening
+- **Reflection** — what it means for us
+
+`journal.ourdigital.org` is the **English essay channel** within the OurDigital family. It carries the same philosophical core as the Korean blog but in a distinct voice: conversational, poetic, reflective.
+
+### Brand Boundary
+
+`OurDigital` is the brand. `OurDigital Clinic` is a service metaphor reserved for diagnostic content, audits, or consulting products — it is **not** the overall blog or journal brand.
+
+## Channel Context
+
+| Channel | Language | Character | Length |
+|---------|----------|-----------|--------|
+| `blog.ourdigital.org` | Korean | 디지털 문화 분석 + 철학적 성찰 + 실무 인사이트 | 1,500–3,000자 |
+| **`journal.ourdigital.org`** | **English** | **Industry trends, tech–human intersection, reflective essay** | **1,000–2,000 words** |
+| `ourstory.day` | Korean | 개인 에세이, 삶의 성찰, 일상의 관찰 | 800–1,500자 |
+| `Medium` | English | Technology, marketing, AI for broad audiences | 800–1,500 words |
+
+## Instruction Authority Order
+
+When instructions conflict, follow this order:
+
+| Priority | Source |
+|----------|--------|
+| **1** | OurDigital_Blog_Project_Instruction_v3.3 (channel routing + brand rules) |
+| **2** | This style guide (journal-specific voice and structure) |
+| **3** | Writing_Style_Guide_v2.1 (shared brand principles, adapted for English) |
+
 ## Channel Identity
 
 | Field | Value |
@@ -10,6 +45,8 @@ Writing guidelines for journal.ourdigital.org - English essays and articles.
 | **Language** | English |
 | **Tone** | Conversational & Poetic, Reflective |
 | **Target** | Informed generalists with intellectual curiosity |
+| **Default length** | 1,000–2,000 words |
+| **Content focus** | Industry trends, tech–human intersection, reflective essays |
 
 ## Voice Characteristics
 
@@ -20,11 +57,16 @@ Seamlessly blend technical analysis with existential questioning. Technology is
 **Example:**
 > The dashboard promises clarity—every metric tracked, every trend visualized. Yet as I stared at the perfectly organized data, I wondered: does seeing everything mean understanding anything?
 
-### Paradox as Primary Device
+### Tension and Paradox
 
-Structure arguments around tensions and contradictions that illuminate rather than confuse.
+Structure arguments around core tensions that illuminate rather than confuse. Not every essay needs a paradox — forced ones feel mechanical. Instead, ensure at least one of the following is naturally present:
 
-**Paradox Patterns:**
+- A genuine tension or contradiction
+- A perspective shift that reframes the subject
+- A rhetorical question that opens rather than closes
+- An ending that leaves productive uncertainty
+
+**Tension patterns:**
 - "The more we measure, the less we understand"
 - "In optimizing for efficiency, we optimize away meaning"
 - "The tools that connect us also isolate us"
@@ -39,6 +81,10 @@ Favor interrogative engagement. Questions create intellectual partnership with r
 **Avoid:**
 > Data-driven decision-making is important for businesses.
 
+### Analytical and Personal
+
+Bring data, evidence, and argument — then weave in first-person experience and observation. This is an essay, not a paper, but it is not impressionism without evidence either. The personal grounds the analytical; the analytical elevates the personal.
+
 ### Melancholic Optimism
 
 Acknowledge loss and anxiety without despair. Accept technological inevitability while mourning what's displaced.
@@ -157,10 +203,14 @@ Connect Korean and Western perspectives, offering unique viewpoints.
 
 Before publishing:
 
-- [ ] Does the opening draw readers in?
+- [ ] Does the opening draw readers in within the first paragraph?
-- [ ] Are there rhetorical questions?
+- [ ] Does technical content connect to human experience (philosophy-tech fusion)?
-- [ ] Does technical content connect to human experience?
+- [ ] Is at least one of the following naturally present: tension, paradox, perspective shift, or open question?
-- [ ] Is there at least one paradox or tension?
+- [ ] Are rhetorical questions used to create intellectual partnership (not overused)?
-- [ ] Does the closing leave an open question?
+- [ ] Is analysis grounded in personal observation or experience?
-- [ ] Is the tone melancholic but not despairing?
+- [ ] Does the closing leave an open question or productive uncertainty?
+- [ ] Is the tone melancholic but not despairing, hopeful but not naive?
 - [ ] Are sentences varied in length and rhythm?
+- [ ] Does the essay avoid lecturing — does it treat readers as fellow thinkers?
+- [ ] Is the essay within 1,000–2,000 words?
+- [ ] **Self-edit**: identify the single weakest element ("all pass" is not allowed).

custom-skills/04-ourdigital-research/SKILL.md

@@ -0,0 +1,172 @@
+---
+name: ourdigital-research
+description: |
+  Deep research and structured prompt generation for OurDigital workflows.
+  Activated with "ourdigital" keyword for research tasks.
+
+  Triggers (ourdigital or our prefix):
+  - "ourdigital research", "our research"
+  - "ourdigital 리서치", "our 리서치"
+  - "ourdigital deep research", "our deep research"
+
+  Features:
+  - Structured research planning
+  - Multi-source deep research
+  - Research paper synthesis
+  - Notion integration for archiving
+  - Blog draft pipeline
+version: "1.0"
+author: OurDigital
+environment: Desktop
+---
+
+# OurDigital Research
+
+Transform questions into comprehensive research papers and polished blog posts for OurDigital channels.
+
+## Activation
+
+Activate with "ourdigital" or "our" prefix:
+- "ourdigital research [topic]" / "our research [topic]"
+- "our 리서치", "our deep research"
+- "ourdigital 리서치 해줘"
+- "ourdigital deep research on [topic]"
+
+## Workflow Overview
+
+```
+Phase 1: Discovery → Phase 2: Research Planning → Phase 3: Deep Research
+    ↓
+Phase 4: Research Paper → Phase 5: Notion Save → Phase 6: Blog Draft
+    ↓
+Phase 7: Ulysses Export → Phase 8: Publishing Guidance
+```
+
+## Phase 1: Discovery
+
+**Goal**: Understand user's question and refine scope.
+
+1. Acknowledge the topic/question
+2. Ask clarifying questions (max 3 per turn):
+   - Target audience? (전문가/일반인/마케터)
+   - Depth level? (개요/심층분석/실무가이드)
+   - Specific angles or concerns?
+3. Confirm research scope before proceeding
+
+**Output**: Clear research objective statement
+
+## Phase 2: Research Planning
+
+**Goal**: Create structured research instruction.
+
+Generate research plan with:
+- Primary research questions (3-5)
+- Secondary questions for depth
+- Suggested tools/sources:
+  - Web search for current info
+  - Google Drive for internal docs
+  - Notion for past research
+  - Amplitude for analytics data (if relevant)
+- Expected deliverables
+
+**Output**: Numbered research instruction list
+
+## Phase 3: Deep Research
+
+**Goal**: Execute comprehensive multi-source research.
+
+Tools to leverage:
+- `web_search` / `web_fetch`: Current information, statistics, trends
+- `google_drive_search`: Internal documents, past reports
+- `Notion:notion-search`: Previous research, related notes
+- `conversation_search`: Past chat context
+
+Research execution pattern:
+1. Start broad (overview searches)
+2. Deep dive into key subtopics
+3. Find supporting data/statistics
+4. Identify expert opinions and case studies
+5. Cross-reference and validate
+
+**Output**: Organized research findings with citations
+
+## Phase 4: Research Paper (Artifact)
+
+**Goal**: Synthesize findings into comprehensive document.
+
+Create HTML artifact with:
+```
+Structure:
+├── Executive Summary (핵심 요약)
+├── Background & Context (배경)
+├── Key Findings (주요 발견)
+│   ├── Finding 1 with evidence
+│   ├── Finding 2 with evidence
+│   └── Finding 3 with evidence
+├── Analysis & Implications (분석 및 시사점)
+├── Recommendations (제언)
+├── References & Sources (참고자료)
+└── Appendix (부록) - if needed
+```
+
+Style: Professional, data-driven, bilingual key terms
+
+## Phase 5: Notion Save
+
+**Goal**: Archive research to Working with AI database.
+
+Auto-save to Notion with:
+- **Database**: Working with AI (data_source_id: f8f19ede-32bd-43ac-9f60-0651f6f40afe)
+- **Properties**:
+  - Name: [Research topic]
+  - Status: "Done"
+  - AI used: "Claude Desktop"
+  - AI summary: 2-3 sentence summary
+
+## Phase 6: Blog Draft
+
+**Goal**: Transform research into engaging blog post.
+
+Prompt user for channel selection:
+1. blog.ourdigital.org (Korean)
+2. journal.ourdigital.org (English)
+3. ourstory.day (Korean, personal)
+
+Generate draft using appropriate style guide:
+- Korean channels: See `02-ourdigital-blog`
+- English channels: See `03-ourdigital-journal`
+
+## Phase 7: Ulysses Export
+
+**Goal**: Deliver MD file for Ulysses editing.
+
+Export path: `$ULYSSES_EXPORT_PATH` from environment
+
+## Phase 8: Publishing Guidance
+
+Provide channel-specific checklist based on selection.
+
+---
+
+## Quick Commands
+
+| Command | Action |
+|---------|--------|
+| "ourdigital research [topic]" | Start Phase 1 |
+| "ourdigital 리서치 프롬프트" | Generate research prompt only |
+| "ourdigital research → blog" | Full pipeline to blog draft |
+| "ourdigital research → notion" | Research + Notion save only |
+
+## Channel Reference
+
+| Channel | Language | Tone |
+|---------|----------|------|
+| blog.ourdigital.org | Korean | Analytical, Educational |
+| journal.ourdigital.org | English | Reflective, Poetic |
+| ourstory.day | Korean | Personal, Intimate |
+
+## References
+
+- `shared/references/research-frameworks.md` - Research methodologies
+- `02-ourdigital-blog` - Blog writing skill
+- `03-ourdigital-journal` - Journal writing skill

custom-skills/04-ourdigital-research/code/references/blog-style-guide.md

@@ -1,38 +1,64 @@
+<!-- Aligned to OurDigital_Writing_Style_Guide_v2.1 + Blog_Project_Instruction_v3.3 (2026-06-05) -->
 # OurDigital Blog Style Guide
 
+## Brand Identity & Authority Order
+
+**Brand**: OurDigital — 사람, 디지털 그리고 문화를 관찰하는 개인 디지털 연구 노트.
+
+**OurDigital vs. OurDigital Clinic**: `OurDigital`은 블로그 전체 정체성. `OurDigital Clinic`은 진단형 콘텐츠, SEO/데이터 감사, 컨설팅 상품에서만 사용하는 서비스 메타포. 블로그 본문에서 전체 브랜드명으로 사용하지 않는다.
+
+**Authority order** (conflicts: higher wins):
+1. `OurDigital_Blog_Project_Instruction_v3.3` — blog.ourdigital.org 최종 권위
+2. Skills Bundle `SKILL.md` files — workflow detail
+3. Project reference files (this guide, Visual Style Guide, etc.)
+4. `userStyle` — non-blog conversation only
+
+---
+
 ## Channel-Specific Voice & Tone
 
 ### blog.ourdigital.org (Korean)
-**Voice**: 전문적이면서 친근한 선배 마케터
+
-**Tone**: 실용적, 데이터 기반, 인사이트 중심
+**Platform**: Ghost CMS
+**Voice**: 분석적이면서 개인적인 관찰자 — 호기심 어린 실무자이자 사유자. 가르치는 선배가 아니라 함께 생각하는 동료.
+**Tone**: 차분하고 성찰적; 에세이는 사려 깊게, 분석은 객관적으로, 비평은 날카롭되 공정하게.
 
 Writing patterns:
-- 제목: 핵심 키워드 포함, 30자 이내
+- 제목: SEO 키워드 자연스럽게 포함, **40자 내외 기준 (≤60자)**
-- 도입부: 독자의 고민/질문으로 시작
+- 도입부: 개인 관찰·장면·질문·역설·데이터 중 하나로 시작; 독자 고민 직접 나열 지양
-- 본문: 번호 매기기보다 소제목 활용
+- 본문: 소제목 활용; 분석-서사-질문 교차; 최소 1회 관점 전환 또는 핵심 긴장 포함
-- 전문용어: 한글(영문) 형식 - 예: 검색엔진최적화(SEO)
+- 전문용어: **첫 등장 시 영문 병기** — 예: `검색엔진 최적화(SEO)`
-- 문장: ~입니다/~습니다 경어체
+- 문장: **`~다`, `~이다`, `~한다` 평서체** (경어체 `~합니다/~입니다` 사용 금지)
-- 단락: 3-4문장, 모바일 가독성 고려
+- 단락: 3-4문장, 모바일 가독성 고려; 문장 길이에 변화를 줌
+- 마무리: 열린 질문 또는 다음 사유의 출발점; 단정적 결론 지양
 
-Example opening:
+Writing principles (Writing Style Guide v2.1 §3-4):
+- **철학-기술 융합**: 기술 주제 이면의 인간적 함의를 탐구한다.
+- **긴장과 역설**: 억지로 넣지 않되, 핵심 긴장·관점 전환·역설·열린 질문 중 하나 이상을 자연스럽게 포함한다.
+- **분석적이면서 개인적**: 데이터/논거를 제시하되 1인칭 경험·관찰을 자연스럽게 엮는다. 논문이 아니라 에세이.
+
+Example opening (올바른 톤):
 ```
-"구글 상위 노출, 왜 이렇게 어려울까요? 
+검색엔진 최적화(SEO)를 가장 잘하는 방법이 뭐냐고 물으면,
-많은 마케터들이 SEO에 시간을 투자하지만 
+나는 종종 엉뚱한 대답을 한다. "SEO를 잊어버리세요."
-결과가 보이지 않아 좌절합니다. 
+
-오늘은 실제로 효과를 본 전략 3가지를 공유합니다."
+알고리즘을 쫓는 사람은 항상 알고리즘에 뒤처진다는 역설.
+구글이 원하는 건 구글을 위한 콘텐츠가 아니라, 사람을 위한 콘텐츠다.
 ```
 
 ### journal.ourdigital.org (English)
-**Voice**: Thoughtful industry analyst
+
-**Tone**: Insightful, evidence-based, forward-looking
+**Voice**: Thoughtful industry analyst — reflective, personal, essayistic
+**Tone**: Insightful, evidence-based, forward-looking; confident but not arrogant
 
 Writing patterns:
 - Headlines: Clear value proposition, under 60 chars
-- Opening: Hook with industry trend or data point
+- Opening: Hook with personal observation, industry trend, or data point
-- Body: Structured arguments with supporting evidence
+- Body: Structured arguments with supporting evidence; analysis and personal observation interwoven
 - Terminology: Define jargon on first use
-- Style: Active voice, varied sentence length
+- Style: Active voice, varied sentence length; short sentences as default
 - Paragraphs: 2-4 sentences for scannability
+- Closing: Open question or reflection — avoid definitive wrap-ups
 
 Example opening:
 ```
@@ -43,17 +69,19 @@ and what it means for your strategy."
 ```
 
 ### ourstory.day (Korean)
-**Voice**: 성찰하는 동료, 이야기꾼
+
+**Voice**: 성찰하는 동료, 이야기꾼 — 개인 에세이, 삶의 성찰, 일상의 관찰
 **Tone**: 개인적, 진솔한, 영감을 주는
 
 Writing patterns:
 - 제목: 감성적, 질문형 또는 은유적
 - 도입부: 개인 경험이나 장면 묘사로 시작
 - 본문: 이야기 흐름, 대화체 허용
-- 문장: ~해요/~네요 부드러운 경어체 가능
 - 단락: 자유로운 길이, 호흡에 따라
 - 마무리: 열린 질문 또는 여운
 
+> **Channel boundary**: 순수 개인 에세이, 감정적 성찰은 `ourstory.day`. 기술 분석+철학적 사유는 `blog.ourdigital.org`. 둘을 혼동하지 않는다.
+
 Example opening:
 ```
 "새벽 5시, 아이를 깨우지 않으려 살금살금 책상에 앉았다.
@@ -63,6 +91,7 @@ Example opening:
 ```
 
 ### Medium (English)
+
 **Voice**: Knowledgeable peer sharing discoveries
 **Tone**: Conversational, practical, slightly informal
 
@@ -82,33 +111,40 @@ Last month, I ran an experiment that changed how I think
 about content strategy entirely. Let me walk you through it."
 ```
 
+---
+
 ## Universal Guidelines
 
-### SEO Considerations
+### SEO & Metadata
+
 - Primary keyword in title and first 100 words
 - Secondary keywords naturally distributed
-- Meta description: 150-160 chars, action-oriented
+- **Meta description: ≤155 chars**, action-oriented, captures the article's question and reader value
-- URL slug: Short, keyword-rich, no dates
+- **URL slug: English, keyword-rich, no dates** — even for Korean-title posts
 - Alt text for all images
 
 ### Formatting Rules
+
 - Use `##` for main sections, `###` for subsections
 - Code blocks with language specification
 - Blockquotes for key insights or quotes
 - Bold for emphasis (sparingly)
-- Lists only when truly listing items
+- Lists only when truly listing items; avoid in essay-form posts
 
 ### Citation Style
+
 - Inline links preferred over footnotes
 - Source attribution: "According to [Source Name](URL)..."
 - Data citations: Include date of data
 - Internal links: Reference related OurDigital posts
 
+---
+
 ## Word Count Guidelines
 
 | Channel | Target | Min | Max |
 |---------|--------|-----|-----|
-| blog.ourdigital.org | 1,500 | 1,000 | 2,500 |
+| blog.ourdigital.org | 2,000자 | 1,000자 | 3,000자 |
-| journal.ourdigital.org | 1,800 | 1,200 | 3,000 |
+| journal.ourdigital.org | 1,500 words | 1,000 words | 2,000 words |
-| ourstory.day | 1,000 | 500 | 2,000 |
+| ourstory.day | 1,000자 | 800자 | 1,500자 |
-| Medium | 1,500 | 800 | 2,500 |
+| Medium | 1,500 words | 800 words | 2,500 words |

custom-skills/05-ourdigital-document/SKILL.md

@@ -0,0 +1,155 @@
+---
+name: ourdigital-document
+description: |
+  Notion-to-presentation workflow for OurDigital.
+  Activated with "ourdigital" keyword for document creation.
+
+  Triggers (ourdigital or our prefix):
+  - "ourdigital document", "our document"
+  - "ourdigital 문서", "our 문서"
+  - "ourdigital presentation", "our presentation"
+  - "ourdigital 발표자료", "our 발표자료"
+
+  Features:
+  - Notion research extraction
+  - Content synthesis and structuring
+  - Branded presentation generation
+  - PowerPoint and Figma output
+version: "1.1"
+author: OurDigital
+environment: Desktop
+---
+
+# OurDigital Document
+
+Transform Notion research into branded presentations for OurDigital workflows.
+
+## Activation
+
+Activate with "ourdigital" or "our" prefix:
+- "ourdigital document" / "our document"
+- "ourdigital 발표자료" / "our 발표자료"
+- "our presentation [topic]"
+- "ourdigital presentation on [topic]"
+
+## Workflow Overview
+
+```
+Phase 1: Research Collection → Phase 2: Content Synthesis → Phase 3: Presentation Planning
+    ↓
+Phase 4: Slide Generation → Phase 5: Brand Application → Phase 6: Export
+```
+
+## Phase 1: Research Collection
+
+**Goal**: Extract research content from Notion.
+
+Input sources:
+- **Notion Page**: `notion://page/[ID]` - Single research document
+- **Notion Database**: `notion://database/[ID]` - Collection query
+- **Multiple Sources**: Comma-separated URLs for synthesis
+
+Tools to use:
+- `Notion:notion-search` - Find related content
+- `Notion:notion-fetch` - Extract page content
+
+**Output**: Structured research.json with findings
+
+## Phase 2: Content Synthesis
+
+**Goal**: Analyze and structure extracted content.
+
+Processing:
+1. Identify key topics and themes
+2. Extract supporting data/statistics
+3. Prioritize by relevance and impact
+4. Generate executive summary
+
+**Output**: synthesis.json with:
+- Executive summary
+- Key topics (ranked)
+- Agenda items
+- Supporting data points
+
+## Phase 3: Presentation Planning
+
+**Goal**: Create slide-by-slide structure.
+
+Presentation types:
+| Type | Slides | Focus |
+|------|--------|-------|
+| Executive Summary | 3-5 | High-level findings, KPIs |
+| Research Report | 10-20 | Detailed methodology, data viz |
+| Meeting Prep | 5-10 | Agenda-driven, decision points |
+
+**Output**: Slide plan with:
+- Title + subtitle per slide
+- Content outline
+- Speaker notes
+- Visual suggestions
+
+## Phase 4: Slide Generation
+
+**Goal**: Generate presentation content.
+
+Slide structure:
+```
+├── Title Slide (project name, date, author)
+├── Agenda (numbered topics)
+├── Content Slides (1-3 per topic)
+│   ├── Key finding header
+│   ├── Supporting points (3-5 bullets)
+│   └── Data visualization placeholder
+├── Summary Slide (key takeaways)
+└── Next Steps / Q&A
+```
+
+## Phase 5: Brand Application
+
+**Goal**: Apply OurDigital corporate styling.
+
+Brand elements:
+- **Colors**: OurDigital palette from `01-ourdigital-brand-guide`
+- **Fonts**: Noto Sans KR (Korean), Inter (English)
+- **Logo**: Positioned per brand guidelines
+- **Spacing**: Consistent margins and padding
+
+Configuration: `shared/references/brand-config.json`
+
+## Phase 6: Export
+
+**Goal**: Generate final deliverable.
+
+Output formats:
+- **PowerPoint (.pptx)**: Full presentation with animations
+- **Figma Slides**: Web-based collaborative format
+- **HTML Preview**: Quick review before final export
+
+Export paths:
+- Desktop: `~/Downloads/presentations/`
+- Figma: Via Figma API
+
+## Quick Commands
+
+| Command | Action |
+|---------|--------|
+| "ourdigital document [Notion URL]" | Full pipeline |
+| "ourdigital 발표자료 만들어줘" | Korean trigger |
+| "ourdigital presentation → pptx" | PowerPoint output |
+| "ourdigital presentation → figma" | Figma output |
+
+## Presentation Templates
+
+| Template | Use Case |
+|----------|----------|
+| Executive | Board meetings, C-level briefs |
+| Research | Deep-dive analysis, team reviews |
+| Meeting | Weekly syncs, project updates |
+| Workshop | Training, collaborative sessions |
+
+## References
+
+- `shared/references/slide-layouts.md` - Layout options
+- `shared/references/agenda-templates.md` - Structure templates
+- `01-ourdigital-brand-guide` - Brand guidelines
+- `04-ourdigital-research` - Research workflow integration

custom-skills/05-ourdigital-document/code/SKILL.md

@@ -103,7 +103,7 @@ python code/scripts/apply_brand.py synthesis.json --preview
 See `code/assets/brand_config.json` for:
 - Logo placement
 - Color scheme (OurDigital palette)
-- Font settings (Poppins/Lora)
+- Font settings (Noto Sans KR/Inter)
 - Slide templates
 
 ## Quick Commands

custom-skills/05-ourdigital-document/code/assets/brand_config.json

@@ -14,9 +14,9 @@
     "surface": "#f1f3f4"
   },
   "fonts": {
-    "heading": "Poppins",
+    "heading": "Inter",
-    "subheading": "Poppins",
+    "subheading": "Inter",
-    "body": "Lora",
+    "body": "Noto Sans KR",
     "caption": "Arial",
     "fallback": {
       "heading": "Arial",

custom-skills/05-ourdigital-document/code/references/slide_layouts.md

@@ -254,7 +254,7 @@ Layout patterns and best practices for different slide types.
 ### Font Pairing
 ```
 Heading Font + Body Font
-- Poppins + Lora
+- Inter + Noto Sans KR (OurDigital primary)
 - Arial + Georgia
 - Helvetica + Times
 - Roboto + Merriweather

custom-skills/05-ourdigital-document/desktop/SKILL.md

@@ -110,7 +110,7 @@ Slide structure:
 
 Brand elements:
 - **Colors**: OurDigital palette from `01-ourdigital-brand-guide`
-- **Fonts**: Poppins (headings), Lora (body)
+- **Fonts**: Noto Sans KR (Korean), Inter (English)
 - **Logo**: Positioned per brand guidelines
 - **Spacing**: Consistent margins and padding
 

custom-skills/05-ourdigital-document/shared/references/slide_layouts.md

@@ -254,7 +254,7 @@ Layout patterns and best practices for different slide types.
 ### Font Pairing
 ```
 Heading Font + Body Font
-- Poppins + Lora
+- Inter + Noto Sans KR (OurDigital primary)
 - Arial + Georgia
 - Helvetica + Times
 - Roboto + Merriweather

custom-skills/06-ourdigital-designer/SKILL.md

@@ -0,0 +1,145 @@
+---
+name: ourdigital-designer
+description: |
+  Visual storytelling and image prompt generation for OurDigital.
+  Activated with "ourdigital" keyword for design tasks.
+
+  Triggers (ourdigital or our prefix):
+  - "ourdigital design", "our design"
+  - "ourdigital 디자인", "our 디자인"
+  - "ourdigital image prompt", "our image prompt"
+  - "ourdigital 썸네일", "our 썸네일"
+
+  Features:
+  - Philosophical visual narrative creation
+  - Image prompt generation for AI art tools
+  - Korean-Western aesthetic fusion
+  - Blog featured image optimization
+version: "1.1"
+author: OurDigital
+environment: Desktop
+---
+
+# OurDigital Designer
+
+Transform philosophical essays into sophisticated visual narratives through minimalist, conceptually rich featured images.
+
+## Activation
+
+Activate with "ourdigital" or "our" prefix:
+- "ourdigital design" / "our design"
+- "ourdigital 썸네일" / "our 썸네일"
+- "our image prompt for [topic]"
+
+## Core Philosophy
+
+OurDigital images are visual philosophy—not illustrations but parallel texts that invite contemplation. Each image captures the essay's philosophical core through:
+
+- **Abstract metaphors** over literal representations
+- **Contemplative minimalism** with 20%+ negative space
+- **Cultural fusion** of Korean-Western aesthetics
+- **Emotional resonance** through color psychology
+
+## Workflow
+
+### Phase 1: Extract Essay Essence
+
+Analyze the content for:
+- **Core insight**: What philosophical truth?
+- **Emotional tone**: What feeling to evoke?
+- **Key metaphor**: What visual symbol?
+
+### Phase 2: Select Visual Approach
+
+| Essay Type | Visual Strategy | Color Mood |
+|-----------|-----------------|------------|
+| Technology | Organic-digital hybrids | Cool blues → warm accents |
+| Social | Network patterns, human fragments | Desaturated → hope spots |
+| Philosophy | Zen space, symbolic objects | Monochrome + single accent |
+| Cultural | Layered traditions, fusion forms | Earth tones → modern hues |
+
+### Phase 3: Generate Prompt
+
+Build structured prompt with:
+```
+[Style] + [Subject] + [Composition] + [Color] + [Technical specs]
+```
+
+### Phase 4: Quality Check
+
+✅ **Must have:**
+- Captures philosophical insight
+- Works at 200px thumbnail
+- Timeless (2-3 year relevance)
+- Cross-cultural readability
+
+❌ **Must avoid:**
+- Tech clichés (circuits, binary)
+- Stock photo aesthetics
+- Literal interpretations
+- Trendy effects
+
+## Quick Templates
+
+### AI & Humanity
+```
+"Translucent human silhouette dissolving into crystalline data structures.
+Monochrome with teal accent. Boundary dissolution between organic/digital.
+1200x630px, minimalist vector style."
+```
+
+### Social Commentary
+```
+"Overlapping circles forming maze pattern, tiny humans in separate chambers.
+Blue-gray palette, warm light leaks for hope. Subtle Korean patterns.
+High negative space. 1200x630px."
+```
+
+### Digital Transformation
+```
+"Traditional forms metamorphosing into particle streams. Paper texture → digital grain.
+Earth tones shifting to cool blues. Sacred geometry underlying.
+1200x630px, contemplative mood."
+```
+
+## Visual Metaphor Shortcuts
+
+| Concept | Visual Metaphor |
+|---------|-----------------|
+| Algorithm | Constellation patterns |
+| Identity | Layered masks, fingerprints |
+| Network | Root systems, neural paths |
+| Time | Spirals, sediment layers |
+| Knowledge | Light sources, growing trees |
+
+## Color Psychology
+
+| Mood | Palette |
+|------|---------|
+| Critical | Deep blue-gray + red accent |
+| Hopeful | Warm amber + sky blue |
+| Philosophical | Near black + off white + gold |
+| Anxious | Charcoal + grey-blue + digital green |
+
+## Technical Specs
+
+- **Dimensions**: 1200x630px (OG standard)
+- **Style**: Vector illustration + subtle textures
+- **Colors**: 60-30-10 rule (dominant-secondary-accent)
+- **Format**: WebP primary, JPG fallback
+
+## Quick Commands
+
+| Command | Action |
+|---------|--------|
+| "ourdigital design [topic]" | Generate image prompt |
+| "ourdigital 썸네일 [주제]" | Korean trigger |
+| "ourdigital visual → midjourney" | MidJourney optimized |
+| "ourdigital visual → dalle" | DALL-E optimized |
+
+## References
+
+- `shared/references/visual-metaphors.md` - Concept dictionary
+- `shared/references/color-palettes.md` - Emotion → color mapping
+- `shared/references/advanced-techniques.md` - Complex compositions
+- `01-ourdigital-brand-guide` - Brand visual identity

custom-skills/06-ourdigital-designer/code/references/visual_metaphors.md

@@ -1,101 +1,104 @@
 # Visual Metaphor Dictionary
 
+<!-- Aligned to OurDigital_Visual_Style_Guide_v2.1 (2026-06-05) -->
+
 Quick reference for translating abstract concepts into visual elements.  
+Default direction: **bright editorial minimalism with conceptual depth** — light/warm-neutral backgrounds, 30%+ negative space, one clear focal metaphor, one human-scale anchor.
 
 ## Technology & Digital
 
-| Concept | Primary Metaphor | Alternative Visuals |
+| Concept | Preferred Metaphor | Alternatives | Avoid |
-|---------|-----------------|-------------------|
+|---------|-------------------|--------------|-------|
-| Algorithm | Constellation patterns | Maze structures, flow charts as art |
+| AI | Co-writing desk, translucent companion shape, mirror | Soft geometric overlay, window reflection | Robot face, glowing brain, Terminator mood, crystalline growth |
-| AI | Crystalline growth | Mirror reflections, fractal patterns |
+| Algorithm | Path map, constellation over paper, sorting trays | Gentle maze, flow chart as art | Black-box cube, surveillance grid |
-| Data | Water flow, particles | Bird murmurations, sand grains |
+| Data | Flowing dots, paper charts, seed-like particles | Water stream, gentle scatter | Neon matrix, endless binary code |
-| Network | Root systems | Neural pathways, spider silk, web |
+| SEO/Search | Compass, map, signpost, light through shelves | Library index, folded path | Magnifying glass cliché alone |
-| Code | Musical notation | DNA strands, city blueprints |
+| Automation | Clockwork garden, conveyor of paper, small helpful mechanism | Self-assembling organic structure | Industrial robot arm, factory dystopia |
-| Cloud | Atmospheric forms | Floating islands, ethereal spaces |
+| Network | Roots, threads, bridges, neurons, community table | Constellation, river delta | Spider web trap, dark cables |
-| Privacy | Veils, shadows | One-way mirrors, fog, barriers |
+| Privacy | Curtain, frosted glass, closed notebook, soft boundary | One-way window | Lock icon alone, heavy shadow |
-| Security | Locks dissolving | Fortresses becoming permeable |
+| Content | Notebook, seeds, layered paper, archive boxes, small lamp | Open shelves | Generic document icons |
-| Automation | Clockwork organic | Self-assembling structures |
+| Code | Musical notation, blueprint detail | DNA strands | Heavy terminal/green-code imagery |
-| Virtual | Layers of reality | Parallel dimensions, glass planes |
 
 ## Social & Cultural
 
-| Concept | Primary Metaphor | Alternative Visuals |
+| Concept | Preferred Metaphor | Alternatives | Avoid |
-|---------|-----------------|-------------------|
+|---------|-------------------|--------------|-------|
-| Identity | Layered masks | Fingerprints merging, mirrors |
+| Identity | Layered paper portrait, reflection in window, fingerprint as landscape | Translucent profile | Faceless mask overload |
-| Community | Overlapping circles | Shared spaces, woven threads |
+| Community | Shared table, overlapping circles, lighted windows | Small bridges, woven threads | Crowd silhouettes in darkness |
-| Isolation | Islands in fog | Glass barriers, empty chairs |
+| Isolation | Single lit desk, island of paper, window distance | Empty chair in warm light | Lonely person in black void |
-| Communication | Bridge structures | Echo patterns, light beams |
+| Communication | Threads, folded letters, bridge, echo rings | Light beams | Speech bubble clutter |
-| Conflict | Opposing forces | Tectonic plates, storm systems |
+| Trust | Clear water, open notebook, steady lamp | Transparent materials | Handshake stock image |
-| Harmony | Resonance patterns | Orchestra arrangements, balance |
+| Reputation | Ripples, layered traces, visible footprints | Soft badges | Star-rating cliché |
-| Culture | Textile patterns | Layered sediments, palimpsest |
+| Change | Folded paper becoming path, seed from circuit, gentle transition | Phase shift, seasonal cycle | Dramatic explosion, shattered pattern |
-| Tradition | Tree rings | Ancient stones, inherited objects |
-| Change | Metamorphosis | Phase transitions, seasonal cycles |
-| Power | Pyramids inverting | Current flows, gravity wells |
 
 ## Philosophical & Abstract
 
-| Concept | Primary Metaphor | Alternative Visuals |
+| Concept | Preferred Metaphor | Alternatives | Avoid |
-|---------|-----------------|-------------------|
+|---------|-------------------|--------------|-------|
-| Time | Spirals, loops | Sediment layers, clock dissolution |
+| Time | Calendar pages, soft spiral, sediment-like paper layers | Loops, tide marks | Melting clock cliché |
-| Knowledge | Light sources | Growing trees, opening books |
+| Knowledge | Lamp, window light, open book, growing plant | Expanding shelves | Glowing brain |
-| Wisdom | Mountain vistas | Deep waters, ancient libraries |
+| Uncertainty | Foggy path, half-open door, incomplete map | Soft blur at edges | Storm clouds only |
-| Truth | Clear water | Prisms splitting light, unveiled |
+| Balance | Asymmetrical stones, mobile, table edge, quiet scale | Tensegrity | Literal scale icon only |
-| Illusion | Distorted mirrors | Smoke shapes, double images |
+| Paradox | Möbius paper strip, two paths meeting, shadow/light on same object | Nested frames | Escher-like complexity overload |
-| Choice | Diverging paths | Doors opening, quantum splits |
+| Wisdom | Window overlooking depth, layered book spines | Ancient stone in light | Heavy mystical imagery |
-| Balance | Tensegrity | Scales reimagined, equilibrium |
+| Choice | Diverging paths, open doors, fork in paper map | Branching thread | Dramatic split/explosion |
-| Paradox | Möbius strips | Impossible objects, Escher-like |
-| Existence | Breath patterns | Pulse rhythms, presence/absence |
-| Consciousness | Nested awareness | Recursive mirrors, awakening |
 
 ## Emotional States
 
-| Emotion | Visual Translation | Color Association |
+| Emotion | Visual Translation | Color Guidance |
-|---------|-------------------|------------------|
+|---------|-------------------|----------------|
-| Anxiety | Fragmented grids | Desaturated, glitch |
+| Anxiety | Fragmented grids, incomplete maps | Desaturated warm neutrals; avoid pure glitch |
-| Hope | Light breaking through | Warm gradients |
+| Hope | Light breaking through window, seedling | Warm gradients on light background |
-| Melancholy | Soft dissolution | Muted blues, grays |
+| Melancholy | Single lit desk, soft dissolution | Muted blues on ivory; avoid black void |
-| Joy | Expansion patterns | Bright, ascending |
+| Joy | Expansion patterns, open space | Bright, ascending on warm white |
-| Fear | Contracting spaces | Sharp contrasts |
+| Peace | Still water, open notebook | Soft neutrals, generous negative space |
-| Peace | Still water | Soft neutrals |
+| Clarity | Clean geometry, clear window | Pure, minimal with one accent |
-| Confusion | Tangled lines | Overlapping hues |
-| Clarity | Clean geometry | Pure, minimal |
 
-## Transformation & Process
+## Signature Motifs (Brand Consistency)
 
-| Process | Visual Narrative | Symbolic Elements |
+| Motif | Description |
-|---------|------------------|------------------|
+|-------|-------------|
-| Growth | Seeds → trees | Fibonacci spirals |
+| **Threshold Spaces** | Doorways, bridges, windows, paths, liminal rooms — transition |
-| Decay | Entropy patterns | Rust, dissolution |
+| **Network Organic** | Roots, threads, neurons, constellations as soft digital networks |
-| Evolution | Branching forms | Darwin's tree reimagined |
+| **Fragment Philosophy** | Folded paper, layered cards, gentle fragmentation and reassembly |
-| Revolution | Circles breaking | Shattered patterns |
+| **Light Studies** | Knowledge/uncertainty via window light, lamps, soft gradients |
-| Innovation | Spark → flame | Lightning, fusion |
+| **Human Traces** | Hands, desks, notebooks, chairs, small figures within conceptual scenes |
-| Tradition | Continuous thread | Inherited patterns |
-| Disruption | Broken grids | Glitch aesthetics |
-| Integration | Merging streams | Confluence points |
 
-## Korean-Western Fusion Elements
+## Recommended Color Palettes
 
-| Korean Element | Western Parallel | Fusion Approach |
+| Palette | Background | Accent | Mood |
-|---------------|-----------------|-----------------|
+|---------|-----------|--------|------|
-| 여백 (Empty space) | Negative space | Active emptiness |
+| Morning Desk | `#F7F3EA` warm ivory | `#4A90A4` muted teal | calm, thoughtful |
-| 오방색 (Five colors) | Color theory | Symbolic palette |
+| Soft Technology | `#F6F8FA` cloud white | `#F2A65A` warm amber | clear, quietly optimistic |
-| 달항아리 (Moon jar) | Minimalism | Imperfect circles |
+| Warm Data | `#FFF8EF` soft cream | `#5EAAA8` soft turquoise | human, analytical |
-| 한글 geometry | Typography | Structural letters |
+| Clear Critique | `#F4F6F8` light gray | `#E07A5F` soft coral | critical but not aggressive |
-| 산수화 (Landscape) | Abstract landscape | Atmospheric depth |
+| Human Network | `#FAF9F6` off-white | `#8AB17D` muted green | organic, connected |
-| 전통문양 (Patterns) | Geometric design | Cultural geometry |
+
+**Dark color limit:** max 15% of canvas; never full dark background by default.
+
+## Korean Design Elements
+
+| Korean Element | Western Parallel | Application |
+|----------------|-----------------|-------------|
+| 여백 (Empty space) | Negative space | Active emptiness — 30%+ default |
+| 달항아리 (Moon jar) | Minimalism | Roundness, asymmetry, soft white |
+| 한지 texture | Paper grain | Subtle background texture only |
+| 산수화 (Landscape) | Editorial landscape | Atmospheric depth without ornament |
+
+**Avoid:** decorative oriental motifs, calligraphy clichés, 오방색 as obvious symbols — express Korean sensibility through spacing and restraint, not surface pattern.
 
 ## Usage Notes
 
-1. **Layer metaphors**: Combine 2-3 for depth
+1. **Layer metaphors**: Combine 2–3 elements; one clear focal object + one human-scale anchor
-2. **Avoid clichés**: No obvious tech symbols
+2. **Avoid clichés**: No obvious tech icons (robot, glowing brain, magnifying glass alone)
-3. **Cultural sensitivity**: Universal over specific
+3. **Match essay tone**: bright → practical guides; balanced → analysis; warmer → personal reflections
-4. **Abstraction levels**: Match essay tone
+4. **30%+ negative space**: default; minimum 20% only when composition needs density
-5. **Emotional resonance**: Feel over literal
+5. **Human trace required**: include hand, desk, figure, window, or everyday object unless topic demands pure abstraction
 
 ## Quick Selection Guide
 
-For **technology essays**: organic-digital hybrids
+For **technology essays**: organic-digital hybrid forms in a light, human-scale environment  
-For **social commentary**: human elements in systems  
+For **social commentary**: network patterns with small human traces  
-For **philosophy pieces**: space and light
+For **philosophy pieces**: calm symbolic scenes with Zen-like spacing  
-For **cultural topics**: layered traditions
+For **practical guides**: clean editorial diagrams with warm accents  
-For **future themes**: transformation states
+For **personal reflections**: soft everyday scenes with metaphorical detail

custom-skills/06-ourdigital-designer/shared/references/visual_metaphors.md

@@ -1,101 +1,104 @@
 # Visual Metaphor Dictionary
 
+<!-- Aligned to OurDigital_Visual_Style_Guide_v2.1 (2026-06-05) -->
+
 Quick reference for translating abstract concepts into visual elements.  
+Default direction: **bright editorial minimalism with conceptual depth** — light/warm-neutral backgrounds, 30%+ negative space, one clear focal metaphor, one human-scale anchor.
 
 ## Technology & Digital
 
-| Concept | Primary Metaphor | Alternative Visuals |
+| Concept | Preferred Metaphor | Alternatives | Avoid |
-|---------|-----------------|-------------------|
+|---------|-------------------|--------------|-------|
-| Algorithm | Constellation patterns | Maze structures, flow charts as art |
+| AI | Co-writing desk, translucent companion shape, mirror | Soft geometric overlay, window reflection | Robot face, glowing brain, Terminator mood, crystalline growth |
-| AI | Crystalline growth | Mirror reflections, fractal patterns |
+| Algorithm | Path map, constellation over paper, sorting trays | Gentle maze, flow chart as art | Black-box cube, surveillance grid |
-| Data | Water flow, particles | Bird murmurations, sand grains |
+| Data | Flowing dots, paper charts, seed-like particles | Water stream, gentle scatter | Neon matrix, endless binary code |
-| Network | Root systems | Neural pathways, spider silk, web |
+| SEO/Search | Compass, map, signpost, light through shelves | Library index, folded path | Magnifying glass cliché alone |
-| Code | Musical notation | DNA strands, city blueprints |
+| Automation | Clockwork garden, conveyor of paper, small helpful mechanism | Self-assembling organic structure | Industrial robot arm, factory dystopia |
-| Cloud | Atmospheric forms | Floating islands, ethereal spaces |
+| Network | Roots, threads, bridges, neurons, community table | Constellation, river delta | Spider web trap, dark cables |
-| Privacy | Veils, shadows | One-way mirrors, fog, barriers |
+| Privacy | Curtain, frosted glass, closed notebook, soft boundary | One-way window | Lock icon alone, heavy shadow |
-| Security | Locks dissolving | Fortresses becoming permeable |
+| Content | Notebook, seeds, layered paper, archive boxes, small lamp | Open shelves | Generic document icons |
-| Automation | Clockwork organic | Self-assembling structures |
+| Code | Musical notation, blueprint detail | DNA strands | Heavy terminal/green-code imagery |
-| Virtual | Layers of reality | Parallel dimensions, glass planes |
 
 ## Social & Cultural
 
-| Concept | Primary Metaphor | Alternative Visuals |
+| Concept | Preferred Metaphor | Alternatives | Avoid |
-|---------|-----------------|-------------------|
+|---------|-------------------|--------------|-------|
-| Identity | Layered masks | Fingerprints merging, mirrors |
+| Identity | Layered paper portrait, reflection in window, fingerprint as landscape | Translucent profile | Faceless mask overload |
-| Community | Overlapping circles | Shared spaces, woven threads |
+| Community | Shared table, overlapping circles, lighted windows | Small bridges, woven threads | Crowd silhouettes in darkness |
-| Isolation | Islands in fog | Glass barriers, empty chairs |
+| Isolation | Single lit desk, island of paper, window distance | Empty chair in warm light | Lonely person in black void |
-| Communication | Bridge structures | Echo patterns, light beams |
+| Communication | Threads, folded letters, bridge, echo rings | Light beams | Speech bubble clutter |
-| Conflict | Opposing forces | Tectonic plates, storm systems |
+| Trust | Clear water, open notebook, steady lamp | Transparent materials | Handshake stock image |
-| Harmony | Resonance patterns | Orchestra arrangements, balance |
+| Reputation | Ripples, layered traces, visible footprints | Soft badges | Star-rating cliché |
-| Culture | Textile patterns | Layered sediments, palimpsest |
+| Change | Folded paper becoming path, seed from circuit, gentle transition | Phase shift, seasonal cycle | Dramatic explosion, shattered pattern |
-| Tradition | Tree rings | Ancient stones, inherited objects |
-| Change | Metamorphosis | Phase transitions, seasonal cycles |
-| Power | Pyramids inverting | Current flows, gravity wells |
 
 ## Philosophical & Abstract
 
-| Concept | Primary Metaphor | Alternative Visuals |
+| Concept | Preferred Metaphor | Alternatives | Avoid |
-|---------|-----------------|-------------------|
+|---------|-------------------|--------------|-------|
-| Time | Spirals, loops | Sediment layers, clock dissolution |
+| Time | Calendar pages, soft spiral, sediment-like paper layers | Loops, tide marks | Melting clock cliché |
-| Knowledge | Light sources | Growing trees, opening books |
+| Knowledge | Lamp, window light, open book, growing plant | Expanding shelves | Glowing brain |
-| Wisdom | Mountain vistas | Deep waters, ancient libraries |
+| Uncertainty | Foggy path, half-open door, incomplete map | Soft blur at edges | Storm clouds only |
-| Truth | Clear water | Prisms splitting light, unveiled |
+| Balance | Asymmetrical stones, mobile, table edge, quiet scale | Tensegrity | Literal scale icon only |
-| Illusion | Distorted mirrors | Smoke shapes, double images |
+| Paradox | Möbius paper strip, two paths meeting, shadow/light on same object | Nested frames | Escher-like complexity overload |
-| Choice | Diverging paths | Doors opening, quantum splits |
+| Wisdom | Window overlooking depth, layered book spines | Ancient stone in light | Heavy mystical imagery |
-| Balance | Tensegrity | Scales reimagined, equilibrium |
+| Choice | Diverging paths, open doors, fork in paper map | Branching thread | Dramatic split/explosion |
-| Paradox | Möbius strips | Impossible objects, Escher-like |
-| Existence | Breath patterns | Pulse rhythms, presence/absence |
-| Consciousness | Nested awareness | Recursive mirrors, awakening |
 
 ## Emotional States
 
-| Emotion | Visual Translation | Color Association |
+| Emotion | Visual Translation | Color Guidance |
-|---------|-------------------|------------------|
+|---------|-------------------|----------------|
-| Anxiety | Fragmented grids | Desaturated, glitch |
+| Anxiety | Fragmented grids, incomplete maps | Desaturated warm neutrals; avoid pure glitch |
-| Hope | Light breaking through | Warm gradients |
+| Hope | Light breaking through window, seedling | Warm gradients on light background |
-| Melancholy | Soft dissolution | Muted blues, grays |
+| Melancholy | Single lit desk, soft dissolution | Muted blues on ivory; avoid black void |
-| Joy | Expansion patterns | Bright, ascending |
+| Joy | Expansion patterns, open space | Bright, ascending on warm white |
-| Fear | Contracting spaces | Sharp contrasts |
+| Peace | Still water, open notebook | Soft neutrals, generous negative space |
-| Peace | Still water | Soft neutrals |
+| Clarity | Clean geometry, clear window | Pure, minimal with one accent |
-| Confusion | Tangled lines | Overlapping hues |
-| Clarity | Clean geometry | Pure, minimal |
 
-## Transformation & Process
+## Signature Motifs (Brand Consistency)
 
-| Process | Visual Narrative | Symbolic Elements |
+| Motif | Description |
-|---------|------------------|------------------|
+|-------|-------------|
-| Growth | Seeds → trees | Fibonacci spirals |
+| **Threshold Spaces** | Doorways, bridges, windows, paths, liminal rooms — transition |
-| Decay | Entropy patterns | Rust, dissolution |
+| **Network Organic** | Roots, threads, neurons, constellations as soft digital networks |
-| Evolution | Branching forms | Darwin's tree reimagined |
+| **Fragment Philosophy** | Folded paper, layered cards, gentle fragmentation and reassembly |
-| Revolution | Circles breaking | Shattered patterns |
+| **Light Studies** | Knowledge/uncertainty via window light, lamps, soft gradients |
-| Innovation | Spark → flame | Lightning, fusion |
+| **Human Traces** | Hands, desks, notebooks, chairs, small figures within conceptual scenes |
-| Tradition | Continuous thread | Inherited patterns |
-| Disruption | Broken grids | Glitch aesthetics |
-| Integration | Merging streams | Confluence points |
 
-## Korean-Western Fusion Elements
+## Recommended Color Palettes
 
-| Korean Element | Western Parallel | Fusion Approach |
+| Palette | Background | Accent | Mood |
-|---------------|-----------------|-----------------|
+|---------|-----------|--------|------|
-| 여백 (Empty space) | Negative space | Active emptiness |
+| Morning Desk | `#F7F3EA` warm ivory | `#4A90A4` muted teal | calm, thoughtful |
-| 오방색 (Five colors) | Color theory | Symbolic palette |
+| Soft Technology | `#F6F8FA` cloud white | `#F2A65A` warm amber | clear, quietly optimistic |
-| 달항아리 (Moon jar) | Minimalism | Imperfect circles |
+| Warm Data | `#FFF8EF` soft cream | `#5EAAA8` soft turquoise | human, analytical |
-| 한글 geometry | Typography | Structural letters |
+| Clear Critique | `#F4F6F8` light gray | `#E07A5F` soft coral | critical but not aggressive |
-| 산수화 (Landscape) | Abstract landscape | Atmospheric depth |
+| Human Network | `#FAF9F6` off-white | `#8AB17D` muted green | organic, connected |
-| 전통문양 (Patterns) | Geometric design | Cultural geometry |
+
+**Dark color limit:** max 15% of canvas; never full dark background by default.
+
+## Korean Design Elements
+
+| Korean Element | Western Parallel | Application |
+|----------------|-----------------|-------------|
+| 여백 (Empty space) | Negative space | Active emptiness — 30%+ default |
+| 달항아리 (Moon jar) | Minimalism | Roundness, asymmetry, soft white |
+| 한지 texture | Paper grain | Subtle background texture only |
+| 산수화 (Landscape) | Editorial landscape | Atmospheric depth without ornament |
+
+**Avoid:** decorative oriental motifs, calligraphy clichés, 오방색 as obvious symbols — express Korean sensibility through spacing and restraint, not surface pattern.
 
 ## Usage Notes
 
-1. **Layer metaphors**: Combine 2-3 for depth
+1. **Layer metaphors**: Combine 2–3 elements; one clear focal object + one human-scale anchor
-2. **Avoid clichés**: No obvious tech symbols
+2. **Avoid clichés**: No obvious tech icons (robot, glowing brain, magnifying glass alone)
-3. **Cultural sensitivity**: Universal over specific
+3. **Match essay tone**: bright → practical guides; balanced → analysis; warmer → personal reflections
-4. **Abstraction levels**: Match essay tone
+4. **30%+ negative space**: default; minimum 20% only when composition needs density
-5. **Emotional resonance**: Feel over literal
+5. **Human trace required**: include hand, desk, figure, window, or everyday object unless topic demands pure abstraction
 
 ## Quick Selection Guide
 
-For **technology essays**: organic-digital hybrids
+For **technology essays**: organic-digital hybrid forms in a light, human-scale environment  
-For **social commentary**: human elements in systems  
+For **social commentary**: network patterns with small human traces  
-For **philosophy pieces**: space and light
+For **philosophy pieces**: calm symbolic scenes with Zen-like spacing  
-For **cultural topics**: layered traditions
+For **practical guides**: clean editorial diagrams with warm accents  
-For **future themes**: transformation states
+For **personal reflections**: soft everyday scenes with metaphorical detail

custom-skills/07-ourdigital-ad-manager/SKILL.md

@@ -0,0 +1,173 @@
+---
+name: ourdigital-ad-manager
+description: |
+  Ad copywriting and keyword research for OurDigital marketing.
+  Activated with "ourdigital" keyword for advertising tasks.
+
+  Triggers (ourdigital or our prefix):
+  - "ourdigital ad copy", "our ad copy"
+  - "ourdigital 광고 카피", "our 광고 카피"
+  - "ourdigital keyword", "our keyword"
+  - "ourdigital 검색 광고", "our 검색 광고"
+
+  Features:
+  - Search ad copywriting (Google, Naver)
+  - Display ad copywriting
+  - Branded content creation
+  - Keyword volume research
+version: "1.0"
+author: OurDigital
+environment: Desktop
+---
+
+# OurDigital Ad Manager
+
+Create compelling ad copy and research keywords for OurDigital marketing campaigns.
+
+## Activation
+
+Activate with "ourdigital" or "our" prefix:
+- "ourdigital ad copy" / "our ad copy"
+- "ourdigital 광고 카피" / "our 광고 카피"
+- "our keyword research [topic]"
+
+## Workflow
+
+### Phase 1: Campaign Brief
+
+Gather information:
+- **Product/Service**: What are we advertising?
+- **Target audience**: Who are we reaching?
+- **Campaign goal**: Awareness, consideration, or conversion?
+- **Platform**: Google, Naver, Meta, Display?
+- **Budget tier**: Affects keyword competitiveness
+
+### Phase 2: Keyword Research
+
+For search campaigns:
+1. **Seed keywords**: Core terms from brief
+2. **Volume research**: Web search for search volume data
+3. **Intent mapping**: Informational → Transactional
+4. **Competitor analysis**: Top-ranking ad copy patterns
+
+Tools to use:
+- `web_search`: Search volume and trends
+- `web_fetch`: Competitor ad copy analysis
+
+### Phase 3: Ad Copy Creation
+
+Generate platform-specific copy following character limits and best practices.
+
+## Search Ad Copy
+
+### Google Ads Format
+
+```
+Headline 1: [30 chars] - Primary keyword + value prop
+Headline 2: [30 chars] - Benefit or CTA
+Headline 3: [30 chars] - Differentiator
+Description 1: [90 chars] - Expand on value
+Description 2: [90 chars] - CTA + urgency
+```
+
+**Best Practices:**
+- Include keyword in Headline 1
+- Numbers and specifics increase CTR
+- Test emotional vs. rational appeals
+- Include pricing if competitive
+
+### Naver Search Ad Format
+
+```
+제목: [25자] - 핵심 키워드 + 가치
+설명: [45자] - 혜택 + 행동 유도
+```
+
+**Korean Ad Copy Tips:**
+- 존댓말 일관성 유지
+- 숫자와 구체적 혜택 강조
+- 신뢰 요소 포함 (경력, 인증)
+
+## Display Ad Copy
+
+### Headlines by Format
+
+| Format | Max Length | Focus |
+|--------|------------|-------|
+| Leaderboard | 25 chars | Brand + single benefit |
+| Medium Rectangle | 30 chars | Offer + CTA |
+| Responsive | 30 chars | Multiple variations |
+
+### Copy Formula
+
+```
+[Problem Recognition] + [Solution Hint] + [CTA]
+"여전히 [문제]? [해결책]으로 [결과]"
+```
+
+## Branded Content
+
+For native advertising and sponsored content:
+
+### OurDigital Tone
+
+- **Authority without arrogance**: Share expertise, invite questions
+- **Data-backed claims**: Statistics increase credibility
+- **Subtle CTAs**: Education first, promotion second
+
+### Content Types
+
+| Type | Length | CTA Style |
+|------|--------|-----------|
+| Sponsored Article | 800-1,200 words | Soft (learn more) |
+| Native Ad | 100-200 words | Medium (discover) |
+| Social Sponsored | 50-100 words | Direct (get started) |
+
+## Keyword Research Output
+
+### Research Report Structure
+
+```
+## Keyword Analysis: [Topic]
+
+### Primary Keywords
+| Keyword | Volume | Difficulty | Intent |
+|---------|--------|------------|--------|
+| [kw1]   | 10K    | Medium     | Trans  |
+
+### Long-tail Opportunities
+- [keyword phrase 1]: Low competition, high intent
+- [keyword phrase 2]: Rising trend
+
+### Negative Keywords
+- [irrelevant term 1]
+- [irrelevant term 2]
+
+### Recommended Ad Groups
+1. [Group Name]: kw1, kw2, kw3
+2. [Group Name]: kw4, kw5, kw6
+```
+
+## Quick Commands
+
+| Command | Action |
+|---------|--------|
+| "ourdigital ad copy [product]" | Full ad set |
+| "ourdigital 검색 광고 [키워드]" | Search ads |
+| "ourdigital display ad [campaign]" | Display copy |
+| "ourdigital keyword [topic]" | Volume research |
+
+## Platform Guidelines
+
+| Platform | Headline | Description | Key Focus |
+|----------|----------|-------------|-----------|
+| Google | 30×3 | 90×2 | Keyword match |
+| Naver | 25 | 45 | Trust signals |
+| Meta | 40 | 125 | Visual-copy sync |
+| LinkedIn | 150 | 70 | Professional tone |
+
+## References
+
+- `shared/references/ad-copy-formulas.md` - Proven copy templates
+- `shared/references/platform-specs.md` - Character limits
+- `01-ourdigital-brand-guide` - Brand voice

custom-skills/08-ourdigital-trainer/SKILL.md

@@ -0,0 +1,186 @@
+---
+name: ourdigital-trainer
+description: |
+  Training material creation and workshop planning for OurDigital.
+  Activated with "ourdigital" keyword for education tasks.
+
+  Triggers (ourdigital or our prefix):
+  - "ourdigital training", "our training"
+  - "ourdigital 교육", "our 교육"
+  - "ourdigital workshop", "our workshop"
+  - "ourdigital 워크샵", "our 워크샵"
+
+  Features:
+  - Training material design
+  - Workshop agenda planning
+  - Participant evaluation design
+  - Exercise and activity creation
+version: "1.0"
+author: OurDigital
+environment: Desktop
+---
+
+# OurDigital Trainer
+
+Design training materials, plan workshops, and create evaluation frameworks for OurDigital education programs.
+
+## Activation
+
+Activate with "ourdigital" or "our" prefix:
+- "ourdigital training" / "our training"
+- "ourdigital 워크샵" / "our 워크샵"
+- "our curriculum [subject]"
+
+## Core Domains
+
+OurDigital training expertise:
+
+| Domain | Topics |
+|--------|--------|
+| **Data Literacy** | 데이터 리터러시, 분석 기초, 시각화 |
+| **AI Literacy** | AI 활용, 프롬프트 엔지니어링, AI 윤리 |
+| **Digital Marketing** | SEO, GTM, 마케팅 자동화 |
+| **Brand Marketing** | 브랜드 전략, 콘텐츠 마케팅 |
+
+## Workflow
+
+### Phase 1: Training Needs Analysis
+
+Gather requirements:
+- **Target audience**: 직급, 경험 수준, 사전 지식
+- **Learning objectives**: 교육 후 달성할 역량
+- **Duration**: 시간 제약 (2시간/반일/전일/다회차)
+- **Format**: 온라인/오프라인/하이브리드
+- **Group size**: 참여 인원
+
+### Phase 2: Curriculum Design
+
+Structure the learning journey:
+
+```
+Module Structure:
+├── 도입 (10-15%)
+│   ├── Ice-breaker
+│   ├── 학습 목표 공유
+│   └── 사전 지식 확인
+├── 핵심 학습 (60-70%)
+│   ├── 개념 설명
+│   ├── 사례 분석
+│   ├── 실습 활동
+│   └── 토론/질의응답
+├── 심화/응용 (15-20%)
+│   ├── 응용 과제
+│   └── 그룹 활동
+└── 마무리 (5-10%)
+    ├── 핵심 정리
+    ├── 평가
+    └── 후속 학습 안내
+```
+
+### Phase 3: Material Development
+
+Create supporting materials:
+
+| Material Type | Purpose |
+|---------------|---------|
+| 슬라이드 | 핵심 개념 전달 |
+| 핸드아웃 | 참조 자료, 체크리스트 |
+| 워크시트 | 실습 활동용 |
+| 사례 연구 | 토론 및 분석용 |
+| 퀴즈/평가지 | 학습 확인용 |
+
+### Phase 4: Activity Design
+
+Engagement techniques:
+
+| Activity Type | Duration | Purpose |
+|---------------|----------|---------|
+| Think-Pair-Share | 5-10분 | 개별 사고 → 협력 |
+| Case Study | 20-30분 | 실제 적용력 |
+| Role Play | 15-20분 | 경험적 학습 |
+| Gallery Walk | 15분 | 아이디어 공유 |
+| Fishbowl | 20-30분 | 심층 토론 |
+
+### Phase 5: Evaluation Design
+
+Assessment framework:
+
+| Level | What to Measure | Method |
+|-------|-----------------|--------|
+| 반응 | 만족도, 참여도 | 설문조사 |
+| 학습 | 지식 습득 | 퀴즈, 테스트 |
+| 행동 | 현업 적용 | 관찰, 피드백 |
+| 결과 | 성과 개선 | KPI 측정 |
+
+## Training Templates
+
+### 2-Hour Workshop
+
+```
+00:00-00:10  도입 및 Ice-breaker
+00:10-00:20  학습 목표 및 아젠다
+00:20-00:50  핵심 개념 1
+00:50-01:00  휴식
+01:00-01:30  핵심 개념 2 + 실습
+01:30-01:50  그룹 활동/토론
+01:50-02:00  정리 및 Q&A
+```
+
+### Half-Day (4 Hours)
+
+```
+09:00-09:20  도입 및 네트워킹
+09:20-10:20  모듈 1: 기초 개념
+10:20-10:30  휴식
+10:30-11:30  모듈 2: 심화 학습
+11:30-12:00  실습 세션
+12:00-12:30  사례 연구
+12:30-13:00  정리, 평가, Q&A
+```
+
+### Full-Day (8 Hours)
+
+```
+09:00-09:30  도입
+09:30-10:30  모듈 1
+10:30-10:45  휴식
+10:45-12:00  모듈 2 + 실습
+12:00-13:00  점심
+13:00-14:00  모듈 3
+14:00-15:00  그룹 프로젝트
+15:00-15:15  휴식
+15:15-16:30  프로젝트 발표
+16:30-17:00  종합 정리 및 평가
+```
+
+## Quick Commands
+
+| Command | Action |
+|---------|--------|
+| "ourdigital training [topic]" | Design curriculum |
+| "ourdigital 워크샵 [주제]" | Workshop agenda |
+| "ourdigital evaluation for [training]" | Assessment design |
+| "ourdigital 교육자료 [주제]" | Material outline |
+
+## Facilitation Tips
+
+### Engagement Techniques
+
+- **3의 법칙**: 핵심 메시지 3개 이하
+- **10분 규칙**: 10분마다 활동 전환
+- **참여 유도**: 질문 → 대기 → 지명
+- **시각화**: 텍스트보다 다이어그램
+
+### Korean Training Context
+
+- 존칭 일관성 유지
+- 실무 사례 강조
+- 명함 교환 시간 확보
+- 그룹 활동 시 리더 지정
+
+## References
+
+- `shared/references/training-frameworks.md` - 교수 설계 모델
+- `shared/references/activity-library.md` - 활동 아이디어
+- `shared/templates/workshop-template.md` - 워크샵 템플릿
+- `01-ourdigital-brand-guide` - 발표 스타일

custom-skills/09-ourdigital-backoffice/SKILL.md

@@ -0,0 +1,231 @@
+---
+name: ourdigital-backoffice
+description: |
+  Business document creation for OurDigital consulting services.
+  Activated with "ourdigital" keyword for business documents.
+
+  Triggers (ourdigital or our prefix):
+  - "ourdigital quote", "our quote"
+  - "ourdigital 견적서", "our 견적서"
+  - "ourdigital proposal", "our proposal"
+  - "ourdigital 비용 분석", "our 비용 분석"
+
+  Features:
+  - Quote/estimate generation
+  - Service proposal creation
+  - Contract draft (requires legal review)
+  - Cost-benefit analysis
+version: "1.0"
+author: OurDigital
+environment: Desktop
+---
+
+# OurDigital Backoffice
+
+Create business documents for OurDigital consulting services.
+
+## Activation
+
+Activate with "ourdigital" or "our" prefix:
+- "ourdigital 견적서" / "our 견적서"
+- "ourdigital proposal" / "our proposal"
+- "our cost analysis [project]"
+
+## Important Notice
+
+⚠️ **Legal Disclaimer**: Contract drafts require professional legal review before use. This skill provides templates and structure only.
+
+## Document Types
+
+### 1. Quote/Estimate (견적서)
+
+**Purpose**: Service pricing and scope summary
+
+**Structure:**
+```
+견적서 번호: OD-YYYY-NNN
+발행일: YYYY-MM-DD
+유효기간: 30일
+
+1. 고객 정보
+   - 회사명, 담당자, 연락처
+
+2. 서비스 개요
+   - 프로젝트명
+   - 서비스 범위 요약
+
+3. 세부 항목
+   | 항목 | 상세 | 수량 | 단가 | 금액 |
+   |------|------|------|------|------|
+
+4. 합계
+   - 소계, VAT, 총액
+
+5. 결제 조건
+   - 선금/잔금 비율
+   - 결제 방법
+
+6. 특이사항
+   - 포함/미포함 사항
+```
+
+### 2. Service Proposal (서비스 제안서)
+
+**Purpose**: Detailed service offering and value proposition
+
+**Structure:**
+```
+1. Executive Summary
+   - 핵심 제안 1-2문단
+
+2. 고객 상황 이해
+   - 현재 과제
+   - 니즈 분석
+
+3. 제안 서비스
+   - 서비스 범위
+   - 접근 방법
+   - 예상 산출물
+
+4. 프로젝트 계획
+   - 일정표
+   - 마일스톤
+   - 체크포인트
+
+5. 투입 리소스
+   - 담당자 프로필
+   - 역할 분담
+
+6. 비용 및 조건
+   - 비용 구조
+   - 결제 조건
+
+7. 기대 효과
+   - 예상 성과
+   - ROI 추정
+
+8. 왜 OurDigital인가
+   - 차별점
+   - 관련 경험
+```
+
+### 3. Contract Draft (계약서 초안)
+
+**Purpose**: Service agreement framework
+
+⚠️ **반드시 법률 전문가 검토 필요**
+
+**Structure:**
+```
+제1조 (목적)
+제2조 (용어의 정의)
+제3조 (계약 기간)
+제4조 (서비스 범위)
+제5조 (대금 및 지급 조건)
+제6조 (권리와 의무)
+제7조 (비밀유지)
+제8조 (지적재산권)
+제9조 (계약의 해지)
+제10조 (손해배상)
+제11조 (분쟁 해결)
+제12조 (일반 조항)
+```
+
+### 4. Cost-Benefit Analysis (비용 분석)
+
+**Purpose**: ROI and investment justification
+
+**Structure:**
+```
+1. 프로젝트 개요
+   - 목적 및 범위
+
+2. 비용 분석
+   | 항목 | 초기비용 | 연간비용 | 3년 TCO |
+
+3. 예상 효과
+   | 효과 | 정량적 가치 | 연간 효과 |
+
+4. ROI 계산
+   - 투자회수기간
+   - NPV, IRR
+
+5. 리스크 분석
+   - 잠재 리스크
+   - 완화 방안
+
+6. 권장 사항
+```
+
+## Service Catalog
+
+OurDigital standard service offerings:
+
+### SEO Services
+
+| Service | Description | Duration | Price Range |
+|---------|-------------|----------|-------------|
+| Technical Audit | 기술 SEO 진단 | 1-2주 | 300-500만원 |
+| On-Page Optimization | 콘텐츠 최적화 | 월간 | 150-300만원/월 |
+| Local SEO | 로컬 검색 최적화 | 월간 | 100-200만원/월 |
+
+### Data & Analytics
+
+| Service | Description | Duration | Price Range |
+|---------|-------------|----------|-------------|
+| GTM Setup | 태그 관리 구축 | 2-4주 | 200-400만원 |
+| GA4 Implementation | 분석 환경 구축 | 1-3주 | 150-300만원 |
+| Dashboard Development | 대시보드 개발 | 2-4주 | 300-600만원 |
+
+### Consulting
+
+| Service | Description | Duration | Price Range |
+|---------|-------------|----------|-------------|
+| Brand Consulting | 브랜드 전략 | 프로젝트 | 500-1000만원 |
+| Marketing Strategy | 마케팅 전략 | 프로젝트 | 300-700만원 |
+| Data Strategy | 데이터 전략 | 프로젝트 | 400-800만원 |
+
+### Training
+
+| Service | Description | Duration | Price Range |
+|---------|-------------|----------|-------------|
+| Workshop | 반일/전일 워크샵 | 4-8시간 | 100-200만원 |
+| Corporate Training | 기업 교육 | 다회차 | 50-100만원/회 |
+
+## Quick Commands
+
+| Command | Action |
+|---------|--------|
+| "ourdigital 견적서 [서비스]" | Generate quote |
+| "ourdigital proposal [client]" | Create proposal |
+| "ourdigital 계약서 초안" | Contract template |
+| "ourdigital 비용 분석 [project]" | Cost-benefit analysis |
+
+## Workflow
+
+### Phase 1: Requirement Gathering
+
+- Client information
+- Service scope
+- Timeline requirements
+- Budget constraints
+
+### Phase 2: Document Generation
+
+- Select appropriate template
+- Fill with gathered information
+- Apply OurDigital branding
+
+### Phase 3: Review & Finalize
+
+- Internal review
+- Client discussion points highlight
+- Legal review (for contracts)
+
+## References
+
+- `shared/templates/quote-template.md` - 견적서 양식
+- `shared/templates/proposal-template.md` - 제안서 양식
+- `shared/templates/contract-template.md` - 계약서 양식
+- `shared/references/pricing-guide.md` - 가격 가이드
+- `01-ourdigital-brand-guide` - 문서 스타일

custom-skills/10-ourdigital-skill-creator/SKILL.md

@@ -0,0 +1,167 @@
+---
+name: ourdigital-skill-creator
+description: |
+  Meta skill for creating and managing OurDigital Claude Skills.
+  Activated when user includes "ourdigital" keyword with skill creation requests.
+
+  Triggers (ourdigital or our prefix):
+  - "ourdigital skill create", "our skill create"
+  - "ourdigital 스킬 만들기", "our 스킬 만들기"
+  - "ourdigital skill creator", "our skill creator"
+
+  Features:
+  - Skill suitability evaluation
+  - Interactive Q&A for requirements gathering
+  - Optimized skill generation (Desktop/Code)
+  - Notion history tracking
+version: "1.0"
+author: OurDigital
+environment: Desktop
+---
+
+# OurDigital Skill Creator
+
+Meta skill for creating, validating, and managing OurDigital Claude Skills.
+
+## Activation
+
+Activate with "ourdigital" or "our" prefix:
+- "ourdigital 스킬 만들어줘" / "our 스킬 만들어줘"
+- "ourdigital skill creator" / "our skill creator"
+- "our skill create [name]"
+
+Do NOT activate for generic "make a skill" requests (without our/ourdigital prefix).
+
+## Interactive Workflow
+
+### Phase 1: Need Assessment
+
+When user requests a new skill:
+
+1. **Acknowledge** the initial request
+2. **Ask clarifying questions** (max 3 per turn):
+   - What is the core purpose?
+   - What triggers this skill?
+   - What outputs do you expect?
+
+### Phase 2: Suitability Check
+
+Evaluate against Claude Skill criteria:
+
+| Criterion | Question to Ask |
+|-----------|-----------------|
+| Clear trigger | When exactly should this skill activate? |
+| Focused scope | Can you describe 1-3 core functions? |
+| Reusable resources | What scripts, templates, or references are needed? |
+| Domain knowledge | What specialized knowledge does Claude lack? |
+| Clear boundaries | How does this differ from existing skills? |
+
+**Decision**: If ≥3 criteria pass → proceed. Otherwise, suggest alternatives.
+
+### Phase 3: Requirements Definition
+
+Guide user through structured Q&A:
+
+```
+Q1. 스킬 목적과 핵심 기능은 무엇인가요?
+    (What is the skill's purpose and core functions?)
+
+Q2. 어떤 상황에서 이 스킬이 트리거되어야 하나요?
+    (When should this skill be triggered?)
+
+Q3. 필요한 외부 도구나 API가 있나요?
+    (Any external tools or APIs needed?)
+
+Q4. 기대하는 출력 형식은 무엇인가요?
+    (What output format do you expect?)
+
+Q5. Desktop, Code, 또는 Both 환경이 필요한가요?
+    (Which environment: Desktop, Code, or Both?)
+```
+
+### Phase 4: Skill Generation
+
+Generate skill structure following OurDigital standards:
+
+```
+XX-ourdigital-{skill-name}/
+├── desktop/
+│   └── SKILL.md         # Desktop version
+├── code/
+│   └── SKILL.md         # Code version (CLAUDE.md pattern)
+├── shared/
+│   ├── references/      # Common documentation
+│   ├── templates/       # Shared templates
+│   └── scripts/         # Utility scripts
+├── docs/
+│   ├── CHANGELOG.md     # Version history
+│   └── logs/            # Update logs
+└── README.md            # Overview
+```
+
+### Phase 5: Validation
+
+Before finalizing, verify:
+
+- [ ] YAML frontmatter includes "ourdigital" trigger keywords
+- [ ] Description clearly states activation conditions
+- [ ] Body content is 800-1,200 words
+- [ ] shared/ resources are properly referenced
+- [ ] No overlap with existing ourdigital skills
+
+### Phase 6: Notion Sync
+
+Record to Working with AI database:
+
+- **Database**: f8f19ede-32bd-43ac-9f60-0651f6f40afe
+- **Properties**:
+  - Name: `ourdigital-{skill-name} v{version}`
+  - Status: In progress → Done
+  - AI used: Claude Desktop
+  - AI summary: Brief skill description
+
+## YAML Frontmatter Template
+
+```yaml
+---
+name: ourdigital-{skill-name}
+description: |
+  [Purpose summary]
+  Activated when user includes "ourdigital" keyword.
+
+  Triggers:
+  - "ourdigital {keyword1}", "ourdigital {keyword2}"
+
+  Features:
+  - Feature 1
+  - Feature 2
+version: "1.0"
+author: OurDigital
+environment: Desktop | Code | Both
+---
+```
+
+## Skill Numbering
+
+| Range | Category |
+|-------|----------|
+| 01-09 | OurDigital Core (brand, blog, journal, research, etc.) |
+| 10 | Meta (skill-creator) |
+| 11-19 | SEO Tools |
+| 20-29 | GTM/Analytics Tools |
+| 31-39 | Notion Tools |
+| 40-49 | Jamie Clinic Tools |
+
+## Reference Files
+
+- `shared/references/suitability-criteria.md` - Skill evaluation criteria
+- `shared/references/skill-patterns.md` - Common patterns
+- `shared/templates/skill-template/` - Blank skill template
+
+## Quick Commands
+
+| Command | Action |
+|---------|--------|
+| "ourdigital 스킬 적합성" | Run suitability check only |
+| "ourdigital 스킬 생성" | Full creation workflow |
+| "ourdigital 스킬 검증" | Validate existing skill |

custom-skills/11-seo-comprehensive-audit/SKILL.md

@@ -0,0 +1,109 @@
+---
+name: seo-comprehensive-audit
+description: |
+  Comprehensive SEO audit orchestrator. Runs 6-stage audit pipeline (Technical, On-Page, CWV, Schema, Local, GSC) and produces a unified report with weighted health score.
+  Triggers: comprehensive SEO, full SEO audit, 종합 SEO 감사, site audit, SEO health check.
+---
+
+# Comprehensive SEO Audit
+
+## Purpose
+
+Orchestrate a full-spectrum SEO audit by running 6 specialized analyses and synthesizing results into a unified health score and actionable report.
+
+## Pipeline Stages
+
+| # | Stage | Source Skill | Default |
+|---|-------|-------------|---------|
+| 1 | Technical SEO | 12-seo-technical-audit | Always |
+| 2 | On-Page SEO | 13-seo-on-page-audit | Always |
+| 3 | Core Web Vitals | 14-seo-core-web-vitals | Always |
+| 4 | Schema Validation | 16-seo-schema-validator | Always |
+| 5 | Local SEO | 18-seo-local-audit | Skippable |
+| 6 | Search Console | 15-seo-search-console | Skippable |
+
+## Workflow
+
+### 1. Initialization
+1. Receive target URL from user
+2. Confirm which stages to run (all 6 by default)
+3. Set up audit tracking ID: `COMP-YYYYMMDD-NNN`
+
+### 2. Execute Stages (Sequential)
+For each active stage:
+1. Run the sub-skill analysis
+2. Collect JSON results
+3. Extract score and issues
+
+### 3. Synthesis
+1. Compute weighted health score (0-100)
+2. Assign grade (A/B+/B/C/D/F)
+3. Prioritize critical and high-severity findings
+4. Generate recommendations
+
+### 4. Notion Report
+1. Create summary page: `종합 SEO 감사 보고서 - [domain] - YYYY-MM-DD`
+2. Create individual pages for Critical/High findings
+3. Database: `2c8581e5-8a1e-8035-880b-e38cefc2f3ef`
+
+## Health Score Weights
+
+| Category | Weight |
+|----------|--------|
+| Technical SEO | 20% |
+| On-Page SEO | 20% |
+| Core Web Vitals | 25% |
+| Schema | 15% |
+| Local SEO | 10% |
+| Search Console | 10% |
+
+Skipped stages redistribute weight proportionally.
+
+## Output Format
+
+```markdown
+## 종합 SEO 감사 보고서: [domain]
+
+**Health Score**: [score]/100 ([grade])
+**Date**: YYYY-MM-DD
+**Audit ID**: COMP-YYYYMMDD-NNN
+
+### Stage Results
+| Stage | Score | Issues |
+|-------|-------|--------|
+| Technical SEO | XX/100 | N issues |
+| On-Page SEO | XX/100 | N issues |
+| Core Web Vitals | XX/100 | N issues |
+| Schema | XX/100 | N issues |
+| Local SEO | XX/100 | N issues |
+| Search Console | XX/100 | N issues |
+
+### Critical Findings
+1. [Finding with recommendation]
+
+### Recommendations (Priority Order)
+1. [Action item]
+```
+
+## MCP Tool Usage
+
+### Firecrawl
+```
+mcp__firecrawl__scrape: Fetch page content for on-page and schema analysis
+```
+
+### Notion
+```
+mcp__notion__*: Create audit report pages in SEO database
+```
+
+### Perplexity
+```
+mcp__perplexity__search: Research best practices for recommendations
+```
+
+## Limitations
+
+- Local SEO stage requires manual input for NAP/GBP data
+- Search Console stage requires GSC API credentials
+- Health score accuracy improves when all 6 stages are active

custom-skills/12-seo-technical-audit/SKILL.md

@@ -0,0 +1,103 @@
+---
+name: seo-technical-audit
+description: |
+  Technical SEO analyzer for robots.txt, sitemap, and crawlability fundamentals.
+  Triggers: technical SEO, robots.txt, sitemap validation, crawlability, URL accessibility.
+---
+
+# SEO Technical Audit
+
+## Purpose
+
+Analyze crawlability fundamentals: robots.txt rules, XML sitemap structure, and URL accessibility. Identify issues blocking search engine crawlers.
+
+## Core Capabilities
+
+1. **Robots.txt Analysis** - Parse rules, check blocked resources
+2. **Sitemap Validation** - Verify XML structure, URL limits, dates
+3. **URL Accessibility** - Check HTTP status, redirects, broken links
+
+## MCP Tool Usage
+
+### Firecrawl for Page Data
+```
+mcp__firecrawl__scrape: Fetch robots.txt and sitemap content
+mcp__firecrawl__crawl: Check multiple URLs accessibility
+```
+
+### Perplexity for Best Practices
+```
+mcp__perplexity__search: Research current SEO recommendations
+```
+
+## Workflow
+
+### 1. Robots.txt Check
+1. Fetch `[domain]/robots.txt` using Firecrawl
+2. Parse User-agent rules and Disallow patterns
+3. Identify blocked resources (CSS, JS, images)
+4. Check for Sitemap declarations
+5. Report critical issues
+
+### 2. Sitemap Validation
+1. Locate sitemap (from robots.txt or `/sitemap.xml`)
+2. Validate XML syntax
+3. Check URL count (max 50,000)
+4. Verify lastmod date formats
+5. For sitemap index: parse child sitemaps
+
+### 3. URL Accessibility Sampling
+1. Extract URLs from sitemap
+2. Sample 50-100 URLs for large sites
+3. Check HTTP status codes
+4. Identify redirects and broken links
+5. Report 4xx/5xx errors
+
+## Output Format
+
+```markdown
+## Technical SEO Audit: [domain]
+
+### Robots.txt Analysis
+- Status: [Valid/Invalid/Missing]
+- Sitemap declared: [Yes/No]
+- Critical blocks: [List]
+
+### Sitemap Validation
+- URLs found: [count]
+- Syntax: [Valid/Errors]
+- Issues: [List]
+
+### URL Accessibility (sampled)
+- Checked: [count] URLs
+- Success (2xx): [count]
+- Redirects (3xx): [count]
+- Errors (4xx/5xx): [count]
+
+### Recommendations
+1. [Priority fixes]
+```
+
+## Common Issues
+
+| Issue | Impact | Fix |
+|-------|--------|-----|
+| No sitemap in robots.txt | Medium | Add `Sitemap:` directive |
+| Blocking CSS/JS | High | Allow Googlebot access |
+| 404s in sitemap | High | Remove or fix URLs |
+| Missing lastmod | Low | Add dates for freshness signals |
+
+## Limitations
+
+- Cannot access password-protected sitemaps
+- Large sitemaps (10,000+ URLs) require sampling
+- Does not check render-blocking issues (use Core Web Vitals skill)
+
+## Notion Output (Required)
+
+All audit reports MUST be saved to OurDigital SEO Audit Log:
+- **Database ID**: `2c8581e5-8a1e-8035-880b-e38cefc2f3ef`
+- **Properties**: Issue (title), Site (url), Category, Priority, Found Date, Audit ID
+- **Language**: Korean with English technical terms
+- **Audit ID Format**: [TYPE]-YYYYMMDD-NNN
+

custom-skills/13-seo-on-page-audit/SKILL.md

@@ -0,0 +1,103 @@
+---
+name: seo-on-page-audit
+description: |
+  On-page SEO analyzer for meta tags, headings, links, images, and Open Graph.
+  Triggers: on-page SEO, meta tags, title tag, heading structure, alt text.
+---
+
+# SEO On-Page Audit
+
+## Purpose
+
+Analyze single-page SEO elements: meta tags, heading hierarchy, internal/external links, images, and social sharing tags.
+
+## Core Capabilities
+
+1. **Meta Tags** - Title, description, canonical, robots
+2. **Headings** - H1-H6 structure and hierarchy
+3. **Links** - Internal, external, broken detection
+4. **Images** - Alt text, sizing, lazy loading
+5. **Social** - Open Graph, Twitter Cards
+
+## MCP Tool Usage
+
+```
+mcp__firecrawl__scrape: Extract page HTML and metadata
+mcp__perplexity__search: Research SEO best practices
+mcp__notion__create-page: Save audit findings
+```
+
+## Workflow
+
+1. Scrape target URL with Firecrawl
+2. Extract and analyze meta tags
+3. Map heading hierarchy
+4. Count and categorize links
+5. Check image optimization
+6. Validate Open Graph tags
+7. Generate recommendations
+
+## Checklist
+
+### Meta Tags
+- [ ] Title present (50-60 characters)
+- [ ] Meta description present (150-160 characters)
+- [ ] Canonical URL set
+- [ ] Robots meta allows indexing
+
+### Headings
+- [ ] Single H1 tag
+- [ ] Logical hierarchy (no skips)
+- [ ] Keywords in H1
+
+### Links
+- [ ] No broken internal links
+- [ ] External links use rel attributes
+- [ ] Reasonable internal link count
+
+### Images
+- [ ] All images have alt text
+- [ ] Images are appropriately sized
+- [ ] Lazy loading implemented
+
+### Open Graph
+- [ ] og:title present
+- [ ] og:description present
+- [ ] og:image present (1200x630)
+
+## Output Format
+
+```markdown
+## On-Page Audit: [URL]
+
+### Meta Tags: X/5
+| Element | Status | Value |
+|---------|--------|-------|
+
+### Headings: X/5
+- H1: [text]
+- Hierarchy: Valid/Invalid
+
+### Links
+- Internal: X
+- External: X
+- Broken: X
+
+### Recommendations
+1. [Priority fixes]
+```
+
+## Limitations
+
+- Single page analysis only
+- Cannot detect JavaScript-rendered content issues
+- External link status requires additional crawl
+
+## Notion Output (Required)
+
+All audit reports MUST be saved to OurDigital SEO Audit Log:
+- **Database ID**: `2c8581e5-8a1e-8035-880b-e38cefc2f3ef`
+- **Properties**: Issue (title), Site (url), Category, Priority, Found Date, Audit ID
+- **Language**: Korean with English technical terms
+- **Audit ID Format**: [TYPE]-YYYYMMDD-NNN
+

custom-skills/14-seo-core-web-vitals/SKILL.md

@@ -0,0 +1,117 @@
+---
+name: seo-core-web-vitals
+description: |
+  Core Web Vitals analyzer for LCP, FID, CLS, and INP optimization recommendations.
+  Triggers: Core Web Vitals, page speed, LCP optimization, CLS fix, INP analysis.
+---
+
+# SEO Core Web Vitals
+
+## Purpose
+
+Analyze Core Web Vitals performance metrics and provide optimization recommendations.
+
+## Core Capabilities
+
+1. **LCP** - Largest Contentful Paint measurement
+2. **FID/INP** - Interactivity metrics
+3. **CLS** - Cumulative Layout Shift
+4. **Recommendations** - Optimization guidance
+
+## Metrics Thresholds
+
+| Metric | Good | Needs Work | Poor |
+|--------|------|------------|------|
+| LCP | ≤2.5s | 2.5-4s | >4s |
+| FID | ≤100ms | 100-300ms | >300ms |
+| CLS | ≤0.1 | 0.1-0.25 | >0.25 |
+| INP | ≤200ms | 200-500ms | >500ms |
+
+## Data Sources
+
+### Option 1: PageSpeed Insights (Recommended)
+Use external tool and input results:
+- Visit: https://pagespeed.web.dev/
+- Enter URL, run test
+- Provide scores to skill
+
+### Option 2: Research Best Practices
+```
+mcp__perplexity__search: "Core Web Vitals optimization [specific issue]"
+```
+
+## Workflow
+
+1. Request PageSpeed Insights data from user
+2. Analyze provided metrics
+3. Identify failing metrics
+4. Research optimization strategies
+5. Provide prioritized recommendations
+
+## Common LCP Issues
+
+| Cause | Fix |
+|-------|-----|
+| Slow server response | Improve TTFB, use CDN |
+| Render-blocking resources | Defer non-critical CSS/JS |
+| Slow resource load | Preload LCP image |
+| Client-side rendering | Use SSR/SSG |
+
+## Common CLS Issues
+
+| Cause | Fix |
+|-------|-----|
+| Images without dimensions | Add width/height attributes |
+| Ads/embeds without space | Reserve space with CSS |
+| Web fonts causing FOIT/FOUT | Use font-display: swap |
+| Dynamic content injection | Reserve space, use transforms |
+
+## Common INP Issues
+
+| Cause | Fix |
+|-------|-----|
+| Long JavaScript tasks | Break up tasks, use web workers |
+| Large DOM size | Reduce DOM nodes |
+| Heavy event handlers | Debounce, optimize listeners |
+| Third-party scripts | Defer, lazy load |
+
+## Output Format
+
+```markdown
+## Core Web Vitals: [URL]
+
+### Scores
+| Metric | Mobile | Desktop | Status |
+|--------|--------|---------|--------|
+| LCP | Xs | Xs | Good/Poor |
+| FID | Xms | Xms | Good/Poor |
+| CLS | X.XX | X.XX | Good/Poor |
+| INP | Xms | Xms | Good/Poor |
+
+### Overall Score
+- Mobile: X/100
+- Desktop: X/100
+
+### Priority Fixes
+1. [Highest impact recommendation]
+2. [Second priority]
+
+### Detailed Recommendations
+[Per-metric optimization steps]
+```
+
+## Limitations
+
+- Requires external PageSpeed Insights data
+- Lab data may differ from field data
+- Some fixes require developer implementation
+- Third-party scripts may be difficult to optimize
+
+## Notion Output (Required)
+
+All audit reports MUST be saved to OurDigital SEO Audit Log:
+- **Database ID**: `2c8581e5-8a1e-8035-880b-e38cefc2f3ef`
+- **Properties**: Issue (title), Site (url), Category, Priority, Found Date, Audit ID
+- **Language**: Korean with English technical terms
+- **Audit ID Format**: [TYPE]-YYYYMMDD-NNN
+

custom-skills/15-seo-search-console/SKILL.md

@@ -0,0 +1,126 @@
+---
+name: seo-search-console
+description: |
+  Google Search Console data analyzer for performance, queries, and index coverage.
+  Triggers: Search Console, GSC analysis, search performance, rankings, CTR optimization.
+---
+
+# SEO Search Console
+
+## Purpose
+
+Analyze Google Search Console data: search performance (queries, pages, CTR, position), sitemap status, and index coverage.
+
+## Core Capabilities
+
+1. **Performance Analysis** - Clicks, impressions, CTR, position
+2. **Query Analysis** - Top search queries
+3. **Page Performance** - Best/worst performing pages
+4. **Index Coverage** - Crawl and index issues
+5. **Sitemap Status** - Submission and processing
+
+## Data Collection
+
+### Option 1: User Provides Data
+Request GSC export from user:
+1. Go to Search Console > Performance
+2. Export data (CSV or Google Sheets)
+3. Share with assistant
+
+### Option 2: User Describes Data
+User verbally provides:
+- Top queries and positions
+- CTR trends
+- Coverage issues
+
+## Analysis Framework
+
+### Performance Metrics
+
+| Metric | What It Measures | Good Benchmark |
+|--------|------------------|----------------|
+| Clicks | User visits from search | Trending up |
+| Impressions | Search appearances | High for target keywords |
+| CTR | Click-through rate | 2-5% average |
+| Position | Average ranking | <10 for key terms |
+
+### Query Analysis
+
+Identify:
+- **Winners** - High position, high CTR
+- **Opportunities** - High impressions, low CTR
+- **Quick wins** - Position 8-20, low effort to improve
+
+### Page Analysis
+
+Categorize:
+- **Top performers** - High clicks, good CTR
+- **Underperformers** - High impressions, low CTR
+- **Declining** - Down vs previous period
+
+## Workflow
+
+1. Collect GSC data from user
+2. Analyze performance trends
+3. Identify top queries and pages
+4. Find optimization opportunities
+5. Check for coverage issues
+6. Provide actionable recommendations
+
+## Output Format
+
+```markdown
+## Search Console Analysis: [Site]
+
+### Overview (Last 28 Days)
+| Metric | Value | vs Previous |
+|--------|-------|-------------|
+| Clicks | X | +X% |
+| Impressions | X | +X% |
+| CTR | X% | +X% |
+| Position | X | +X |
+
+### Top Queries
+| Query | Clicks | Position | Opportunity |
+|-------|--------|----------|-------------|
+
+### Top Pages
+| Page | Clicks | CTR | Status |
+|------|--------|-----|--------|
+
+### Opportunities
+1. [Query with high impressions, low CTR]
+2. [Page ranking 8-20 that can improve]
+
+### Issues
+- [Coverage problems]
+- [Sitemap issues]
+
+### Recommendations
+1. [Priority action]
+```
+
+## Common Issues
+
+| Issue | Impact | Fix |
+|-------|--------|-----|
+| Low CTR on high-impression query | Lost traffic | Improve title/description |
+| Declining positions | Traffic loss | Update content, build links |
+| Not indexed pages | No visibility | Fix crawl issues |
+| Sitemap errors | Discovery problems | Fix sitemap XML |
+
+## Limitations
+
+- Requires user to provide GSC data
+- API access needs service account setup
+- Data has 2-3 day delay
+- Limited to verified properties
+
+## Notion Output (Required)
+
+All audit reports MUST be saved to OurDigital SEO Audit Log:
+- **Database ID**: `2c8581e5-8a1e-8035-880b-e38cefc2f3ef`
+- **Properties**: Issue (title), Site (url), Category, Priority, Found Date, Audit ID
+- **Language**: Korean with English technical terms
+- **Audit ID Format**: [TYPE]-YYYYMMDD-NNN
+

custom-skills/16-seo-schema-validator/SKILL.md

@@ -0,0 +1,100 @@
+---
+name: seo-schema-validator
+description: |
+  Validates an AUTHORED JSON-LD schema dataset (pre-deployment QA) and audits
+  live structured data (post-deployment). Runs a 5-layer offline validation
+  pipeline (coverage, syntax, vocabulary, Google rich-result requirements,
+  business-logic/consistency) and emits a severity-ranked defect log, a gate
+  decision, and a Markdown report. Fills the "16-seo-schema-validator" slot
+  referenced by seo-comprehensive-audit.
+  Triggers: schema validation, JSON-LD QA, structured data check, schema 검수,
+  스키마 유효성 검증, 구조화 데이터 검토, rich result eligibility, schema 오류 점검.
+version: "1.0"
+author: OurDigital / D.intelligence
+environment: Code
+---
+
+# SEO Schema Validator (16)
+
+Quality-assure structured data at scale. Built for the kind of failure where a
+client review of hundreds of authored entries surfaces "too many errors" — by
+moving the cheap, machine-checkable errors OUT of the human review and INTO an
+automated gate that runs first.
+
+## Two modes
+
+| Mode | When | Input | Adds |
+|------|------|-------|------|
+| **A — Dataset QA (default)** | Before deployment, while authoring/reviewing | An authored dataset: `.xlsx` / `.csv` (one row per entry, a JSON-LD column), `.jsonl`, `.json`, or a directory of `.json/.jsonld` | Layer 0 coverage vs the canonical URL list |
+| **B — Live audit** | After deployment, or feeding `seo-comprehensive-audit` | Live URLs (extract embedded JSON-LD first, then validate) | Layer 5 rendering-reality (schema present in rendered HTML, matches content) |
+
+This skill's primary job is **Mode A**: catch errors before the client sees them.
+
+## The 5 validation layers
+
+| # | Layer | Catches | Default severity |
+|---|-------|---------|------------------|
+| L0 | Coverage | URLs with no entry; entries whose URL isn't in the inventory | P1 / P2 |
+| L1 | Syntax | invalid JSON, missing/wrong `@context`, no `@type`, encoding corruption | P0 / P1 |
+| L2 | Vocabulary | unknown type, property not valid for type, bad value formats (URL/date/lang/currency/number) | P1 / P2 |
+| L3 | Rich-result | Google **required** missing (blocks rich result); recommended absent | P0 / P2 |
+| L4 | Consistency | NAP mismatch across a property, `@id` dupes/dangling refs, swapped geo, placeholder text, duplicate descriptions | P0 / P1 |
+
+Full rationale and the type→requirement matrix: `references/validation-methodology.md`.
+Severity + category codes: `references/defect-taxonomy.md`.
+Hotel page-type → schema-type map: `references/hotel-type-map.md`.
+Client-facing report + P1 decision log: `templates/client-qa-report-template.md`, `templates/decision-log.md`.
+
+## Stage gates (aligned to the project lifecycle 설계→개발→테스트→안정화→런칭 후)
+
+- **G1 설계** — Lock the schema spec and the page-type→type map (`hotel-type-map.md`). Approve the entry template. *DoD:* every page template has an assigned schema type and a required-property list.
+- **G2 개발** — Authors produce entries. Run the validator with `--strict`. *DoD (gate):* **zero P0**, JSON parses for 100% of entries. Entries failing this NEVER reach client review.
+- **G3 테스트** — Re-run; triage P1 in `defect_log.csv` (assign owner/status). Client reviews ONLY the clean, P0-free entries, against a defect report — not raw JSON. *DoD:* P1 triaged, decisions logged in `templates/decision-log.md`.
+- **G4 안정화** — Fix → re-run → confirm no regressions. Spot-check a sample in Google Rich Results Test (online, outside this runtime). *DoD:* P0=0, P1 accepted/closed, online validator green on sample.
+- **G5 런칭 후** — Mode B live audit + GSC "Rich results" report monitoring. *DoD:* deployed schema matches authored dataset; no new GSC structured-data errors.
+
+## How to run
+
+```bash
+# Mode A — validate an authored dataset (the common case)
+python scripts/validate_schema.py path/to/schema_dataset.xlsx \
+    --url-list path/to/URLlist.xlsx \
+    --out schema_qa_out
+
+# Highest signal for the pre-review gate (unexpected props -> P1, drop optional recommended)
+python scripts/validate_schema.py dataset.csv --strict --no-recommended --out qa_strict
+
+# Try it on the bundled flawed fixture first
+python scripts/make_sample.py
+python scripts/validate_schema.py fixtures/sample_schema.csv --out demo_out
+```
+
+**Input expectations (Mode A tabular):** the loader auto-detects a JSON-LD column
+(`jsonld`, `schema`, `structured_data`, `스키마`, …) plus optional `url`/`메뉴 URL`,
+`lang`/`언어코드`, `device`/`PC/MOBILE`, `page_type` columns. Multi-sheet `.xlsx`
+is supported (each sheet with a JSON-LD column is read). No JSON-LD column → clear error.
+
+## Reading the output
+
+- `report.md` — counts, **gate decision (PASS = zero P0)**, defects-by-category, top P0 entries, next step.
+- `defect_log.csv` — one row per finding with `status/owner/note` columns ready for triage. This is the client-facing artifact (open issues, not raw schema).
+- `results.json` — full machine-readable results for dashboards / CI.
+
+**The rule:** an entry advances to client review only when it has **zero P0**. P1 =
+triage backlog (fix before launch). P2 = optimization backlog (recommended props, style).
+
+## Limits & honesty
+
+- Offline by design — the runtime can't reach schema.org or Google. The bundled
+  rule set (`scripts/schema_rules.json`) is a curated hotel-focused subset; unknown
+  types/properties degrade to warnings (never hard errors) to avoid false positives.
+- Authoritative rich-result eligibility still requires Google's online testers on a
+  sample at G4. This skill makes that sample small and clean, not redundant.
+- Adding a new schema type or tightening a rule = edit `schema_rules.json` only.
+
+## Integration
+
+`seo-comprehensive-audit` calls this skill as pipeline stage 4 ("Schema Validation").
+For that orchestrator, run **Mode B** on a sample of live URLs and return the score
+(100 − weighted defect penalty) and the issue list. For day-to-day client work, run
+**Mode A** on the authored dataset.

custom-skills/16-seo-schema-validator/code/CLAUDE.md

@@ -1,148 +1,57 @@
-# CLAUDE.md
+# CLAUDE.md — seo-schema-validator (Claude Code)
 
-## Overview
+## Canonical entry point
 
-Structured data validator: extract, parse, and validate JSON-LD, Microdata, and RDFa markup against schema.org vocabulary.
+This skill was upgraded to a **5-layer dataset-QA pipeline**. The authoritative
+directive and run instructions live in the skill root:
 
-## Quick Start
+- **`../SKILL.md`** — modes, the 5 layers, stage gates, how to run.
+- **`../scripts/validate_schema.py`** — the validator (run this, not the legacy script below).
+- **`../scripts/schema_rules.json`** — the offline rule set (edit this to add a type/rule).
+- **`../references/`** — `validation-methodology.md`, `defect-taxonomy.md`, `hotel-type-map.md`.
+- **`../templates/`** — `client-qa-report-template.md`, `decision-log.md`.
 
 ```bash
-pip install -r scripts/requirements.txt
+# Primary use — QA an AUTHORED dataset before the client sees it (Mode A)
-python scripts/schema_validator.py --url https://example.com
+python ../scripts/validate_schema.py DATASET.xlsx --url-list URLLIST.xlsx --out schema_qa_out
+
+# Highest-signal pre-review gate
+python ../scripts/validate_schema.py DATASET.csv --strict --no-recommended --out qa_strict
+
+# Try the bundled flawed fixture first
+python ../scripts/make_sample.py
+python ../scripts/validate_schema.py ../fixtures/sample_schema.csv --out demo_out
+
+# Post-deploy live audit (Mode B) — feeds seo-comprehensive-audit stage 4
+python ../scripts/validate_schema.py --live https://example.com --out live_out
 ```
 
-## Scripts
+Gate rule: **PASS = zero P0.** The process exits 1 when the gate fails, so it stops
+`&&` chains and CI. Only P0-free entries advance to client review.
 
-| Script | Purpose |
+## Legacy single-URL tool (kept for quick one-offs)
-|--------|---------|
-| `schema_validator.py` | Extract and validate structured data |
-| `base_client.py` | Shared utilities |
 
-## Usage
+`scripts/schema_validator.py --url <URL>` extracts and validates structured data from
+one live page (JSON-LD / Microdata / RDFa via extruct). It predates the pipeline and is
+**not** the gate. For any dataset or client-facing QA, use `validate_schema.py` above.
 
 ```bash
-# Validate page schema
+pip install -r scripts/requirements.txt   # extruct, jsonschema, rdflib, lxml, requests
-python scripts/schema_validator.py --url https://example.com
-
-# JSON output
 python scripts/schema_validator.py --url https://example.com --json
-
-# Validate local file
-python scripts/schema_validator.py --file schema.json
-
-# Check Rich Results eligibility
-python scripts/schema_validator.py --url https://example.com --rich-results
 ```
 
-## Supported Formats
+## Notion output (OurDigital SEO Audit Log)
 
-| Format | Detection |
+When a run is part of an OurDigital/D.intelligence audit, log a summary to the SEO Audit
-|--------|-----------|
+Log database. Per the user-level Notion rule, push **page content** with the
-| JSON-LD | `<script type="application/ld+json">` |
+`notion-writer` skill; use Notion MCP only for **properties** (Status, Category, etc.).
-| Microdata | `itemscope`, `itemtype`, `itemprop` |
-| RDFa | `vocab`, `typeof`, `property` |
-
-## Validation Levels
-
-### 1. Syntax Validation
-- Valid JSON structure
-- Proper nesting
-- No syntax errors
-
-### 2. Schema.org Vocabulary
-- Valid @type values
-- Known properties
-- Correct property types
-
-### 3. Google Rich Results
-- Required properties present
-- Recommended properties
-- Feature-specific requirements
-
-## Schema Types Validated
-
-| Type | Required Properties | Rich Result |
-|------|---------------------|-------------|
-| Article | headline, author, datePublished | Yes |
-| Product | name, offers | Yes |
-| LocalBusiness | name, address | Yes |
-| FAQPage | mainEntity | Yes |
-| Organization | name, url | Yes |
-| BreadcrumbList | itemListElement | Yes |
-| WebSite | name, url | Sitelinks |
-
-## Output
-
-```json
-{
-  "url": "https://example.com",
-  "schemas_found": 3,
-  "schemas": [
-    {
-      "@type": "Organization",
-      "valid": true,
-      "rich_results_eligible": true,
-      "issues": [],
-      "warnings": []
-    }
-  ],
-  "summary": {
-    "valid": 3,
-    "invalid": 0,
-    "rich_results_eligible": 2
-  }
-}
-```
-
-## Issue Severity
-
-| Level | Description |
-|-------|-------------|
-| Error | Invalid schema, blocks rich results |
-| Warning | Missing recommended property |
-| Info | Optimization suggestion |
-
-## Dependencies
-
-```
-extruct>=0.16.0
-jsonschema>=4.21.0
-rdflib>=7.0.0
-lxml>=5.1.0
-requests>=2.31.0
-```
-
-## Notion Output (Required)
-
-**IMPORTANT**: All audit reports MUST be saved to the OurDigital SEO Audit Log database.
-
-### Database Configuration
 
 | Field | Value |
 |-------|-------|
 | Database ID | `2c8581e5-8a1e-8035-880b-e38cefc2f3ef` |
-| URL | https://www.notion.so/dintelligence/2c8581e58a1e8035880be38cefc2f3ef |
+| Category | `Schema/Structured Data` |
-
+| Priority | map gate: FAIL→Critical/High, PASS-with-P1→Medium, PASS-clean→Low |
-### Required Properties
+| Audit ID | `SCHEMA-YYYYMMDD-NNN` |
-
-| Property | Type | Description |
-|----------|------|-------------|
-| Issue | Title | Report title (Korean + date) |
-| Site | URL | Audited website URL |
-| Category | Select | Technical SEO, On-page SEO, Performance, Schema/Structured Data, Sitemap, Robots.txt, Content, Local SEO |
-| Priority | Select | Critical, High, Medium, Low |
-| Found Date | Date | Audit date (YYYY-MM-DD) |
-| Audit ID | Rich Text | Format: [TYPE]-YYYYMMDD-NNN |
-
-### Language Guidelines
-
-- Report content in Korean (한국어)
-- Keep technical English terms as-is (e.g., SEO Audit, Core Web Vitals, Schema Markup)
-- URLs and code remain unchanged
-
-### Example MCP Call
-
-```bash
-mcp-cli call notion/API-post-page '{"parent": {"database_id": "2c8581e5-8a1e-8035-880b-e38cefc2f3ef"}, "properties": {...}}'
-```
 
+Report content in Korean; keep technical terms (Schema, JSON-LD, rich result) and
+URLs/code unchanged.

custom-skills/16-seo-schema-validator/fixtures/sample_schema.csv

@@ -0,0 +1,16 @@
+url,언어코드,PC/MOBILE,page_type,스키마
+https://www.josunhotel.com/en/brand/grand,en,PC,brand-hub,"{""@context"": ""https://schema.org"", ""@type"": ""Organization"", ""@id"": ""https://www.josunhotel.com/#org"", ""name"": ""Josun Hotels & Resorts"", ""url"": ""https://www.josunhotel.com/"", ""logo"": ""https://www.josunhotel.com/logo.png"", ""sameAs"": [""https://www.instagram.com/josunhotelsandresorts/""]}"
+https://www.josunhotel.com/ko/grand,ko,PC,hotel,"{""@context"": ""https://schema.org"", ""@type"": ""Hotel"", name: ""그랜드조선"",}"
+https://www.josunhotel.com/ko/grand/rooms,ko,MOBILE,rooms,"{""@context"": ""https://schema.org"", ""name"": ""디럭스룸"", ""url"": ""https://www.josunhotel.com/ko/grand/rooms""}"
+https://www.josunhotel.com/ko/palace,ko,PC,hotel,"{""@context"": ""https://example.org"", ""@type"": ""Hotel"", ""name"": ""조선팰리스"", ""address"": {""@type"": ""PostalAddress"", ""streetAddress"": ""테헤란로 231"", ""addressLocality"": ""서울"", ""addressCountry"": ""KR""}}"
+https://www.josunhotel.com/ko/lescape,ko,PC,hotel,"{""@context"": ""https://schema.org"", ""@type"": ""Hotel"", ""name"": ""레스케이프 호텔"", ""telephone"": ""+82-2-317-4000"", ""description"": ""조선호텔앤리조트가 운영하는 럭셔리 호텔로, 도심 속에서 품격 있는 휴식을 제공합니다. 최상의 서비스와 시설을 경험하실 수 있습니다.""}"
+https://www.josunhotel.com/ko/grand/dining,ko,PC,restaurant,"{""@context"": ""https://schema.org"", ""@type"": ""Restaurant"", ""name"": ""예시 레스토랑"", ""address"": {""@type"": ""PostalAddress"", ""streetAddress"": ""수정필요"", ""addressCountry"": ""KR""}, ""servesCuisine"": ""Korean""}"
+https://www.josunhotel.com/ko/westin,ko,PC,hotel,"{""@context"": ""https://schema.org"", ""@type"": ""Hotel"", ""name"": ""웨스틴 조선 서울"", ""telephone"": ""+82-2-771-0500"", ""address"": {""@type"": ""PostalAddress"", ""streetAddress"": ""소공로 106"", ""addressLocality"": ""서울"", ""addressCountry"": ""KR""}, ""description"": ""조선호텔앤리조트가 운영하는 럭셔리 호텔로, 도심 속에서 품격 있는 휴식을 제공합니다. 최상의 서비스와 시설을 경험하실 수 있습니다.""}"
+https://www.josunhotel.com/en/westin,en,PC,hotel,"{""@context"": ""https://schema.org"", ""@type"": ""Hotel"", ""name"": ""웨스틴 조선 서울"", ""telephone"": ""+82-2-771-9999"", ""address"": {""@type"": ""PostalAddress"", ""streetAddress"": ""소공로 106"", ""addressLocality"": ""Seoul"", ""addressCountry"": ""KR""}, ""description"": ""조선호텔앤리조트가 운영하는 럭셔리 호텔로, 도심 속에서 품격 있는 휴식을 제공합니다. 최상의 서비스와 시설을 경험하실 수 있습니다.""}"
+https://www.josunhotel.com/ko,ko,PC,home,"{""@context"": ""https://schema.org"", ""@type"": ""WebSite"", ""name"": ""조선호텔앤리조트"", ""url"": ""https://www.josunhotel.com/"", ""publisher"": {""@id"": ""https://www.josunhotel.com/#missing-org""}}"
+https://www.josunhotel.com/ko/grand/location,ko,PC,location,"{""@context"": ""https://schema.org"", ""@type"": ""Hotel"", ""name"": ""그랜드 조선 부산"", ""address"": {""@type"": ""PostalAddress"", ""streetAddress"": ""동백로 60"", ""addressLocality"": ""부산"", ""addressCountry"": ""KR""}, ""geo"": {""@type"": ""GeoCoordinates"", ""latitude"": 129.1603, ""longitude"": 35.1586}}"
+https://www.josunhotel.com/ko/offers/spring,ko,PC,offer,"{""@context"": ""https://schema.org"", ""@type"": ""Offer"", ""price"": ""350000"", ""priceCurrency"": ""KRW"", ""validFrom"": ""2026년 3월 1일"", ""url"": ""https://www.josunhotel.com/ko/offers/spring""}"
+https://www.josunhotel.com/ko/offers/dining,ko,PC,offer,"{""@context"": ""https://schema.org"", ""@type"": ""Offer"", ""price"": ""120000"", ""priceCurrency"": ""₩"", ""availability"": ""https://schema.org/InStock""}"
+https://www.josunhotel.com/ko/spa,ko,PC,facility,"{""@context"": ""https://schema.org"", ""@type"": ""SpaResort"", ""name"": ""조선 스파""}"
+https://www.josunhotel.com/ko/grand/intro,ko,PC,hotel,"{""@context"": ""https://schema.org"", ""@type"": ""Hotel"", ""name"": ""그랜드 조선 제주"", ""address"": {""@type"": ""PostalAddress"", ""streetAddress"": ""중문관광로 75"", ""addressLocality"": ""제주"", ""addressCountry"": ""KR""}, ""description"": ""조선호텔앤리조트가 운영하는 럭셔리 호텔로, 도심 속에서 품격 있는 휴식을 제공합니다. 최상의 서비스와 시설을 경험하실 수 있습니다.""}"
+https://www.josunhotel.com/ko/faq?stale=1,ko,MOBILE,faq,"{""@context"": ""https://schema.org"", ""@type"": ""FAQPage"", ""mainEntity"": [{""@type"": ""Question"", ""name"": ""체크인 시간은 언제인가요?"", ""acceptedAnswer"": {""@type"": ""Answer"", ""text"": ""오후 3시부터 체크인 가능합니다.""}}]}"

custom-skills/16-seo-schema-validator/references/defect-taxonomy.md

@@ -0,0 +1,74 @@
+# Defect Taxonomy
+
+Every code `validate_schema.py` can emit, its default severity, and what to do.
+The validator writes these to `defect_log.csv` (columns: `entry_id, url, node_type,
+layer, code, severity, message, status, owner, note`) and `results.json`.
+
+## Severity model
+
+| Severity | Definition | Owner action |
+|---|---|---|
+| **P0** | Blocker — breaks parsing, blocks the rich result, or ships wrong/placeholder data. **Fails the gate.** | Must fix before the entry reaches client review. |
+| **P1** | Real defect, doesn't block the rich result. | Fix before launch; track in the triage log. |
+| **P2** | Optimization — recommended properties, formatting, orphan URLs. | Backlog; fix opportunistically. |
+
+`--strict` promotes vocabulary/format warnings (and unknown types) from P2 to P1 and
+turns on `UNEXPECTED_PROPERTY`. `--no-recommended` drops `MISSING_RECOMMENDED` entirely.
+**Neither changes the gate — the gate is always "zero P0."**
+
+## Code reference
+
+### Layer 0 — Coverage
+| Code | Sev | Trigger | Fix |
+|---|---|---|---|
+| `COVERAGE_MISSING` | P1 | Inventory URL has no authored entry. | Author the entry, or remove the URL from the inventory. |
+| `COVERAGE_ORPHAN` | P2 | Entry URL isn't in the inventory. | Fix the URL typo, or update the canonical list. |
+
+### Layer 1 — Syntax
+| Code | Sev | Trigger | Fix |
+|---|---|---|---|
+| `INVALID_JSON` | P0 | JSON does not parse. | Fix the JSON (trailing comma, unquoted key, smart quotes). |
+| `NO_SCHEMA_IN_HTML` | P0 | Live page has no `ld+json` block (Mode B). | Confirm the tag deployed and renders. |
+| `MISSING_CONTEXT` | P1 | No top-level `@context`. | Add `"@context": "https://schema.org"`. |
+| `WRONG_CONTEXT` | P1 | `@context` isn't schema.org. | Correct the context URL. |
+| `NO_TYPE` | P1 | No `@type` anywhere in the entry. | Add the intended `@type`. |
+| `ENCODING_CORRUPTION` | P1 | Replacement char `<60>` present. | Re-export as UTF-8; check the source pipeline. |
+| `FETCH_ERROR` | P1 | Live URL could not be fetched (Mode B). | Check the URL/network; retry. |
+
+### Layer 2 — Vocabulary & value formats
+| Code | Sev (strict) | Trigger | Fix |
+|---|---|---|---|
+| `UNKNOWN_TYPE` | P2 (P1) | `@type` not in the curated rule set. | If intended, add it to `schema_rules.json`; else correct the type. |
+| `UNEXPECTED_PROPERTY` | — (P1) | Property unknown for a known type (**strict only**). | Remove the typo'd property, or add it to the type's `allowed`. |
+| `BAD_URL` | P2 (P1) | A URL property isn't an `http(s)` URL. | Use an absolute URL. |
+| `BAD_DATE` | P2 (P1) | A date property isn't ISO-8601. | Use `YYYY-MM-DD` (or full datetime). |
+| `BAD_LANG` | P2 (P1) | `inLanguage`/`availableLanguage` isn't a BCP-47 code. | Use `ko`, `en`, `ja`, `zh`, … |
+| `BAD_CURRENCY` | P2 (P1) | `priceCurrency` isn't a 3-letter ISO-4217 code. | Use `KRW`/`USD`, not `₩`/`$`. |
+| `BAD_NUMBER` | P2 (P1) | A numeric property isn't numeric. | Remove units/commas; keep digits. |
+
+### Layer 3 — Rich-result requirements
+| Code | Sev | Trigger | Fix |
+|---|---|---|---|
+| `MISSING_REQUIRED` | P0 | A Google-required property is absent. | Add the property — the rich result is blocked without it. |
+| `MISSING_RECOMMENDED` | P2 | Recommended properties absent (one line per node, lists all). | Add what applies to improve eligibility/appearance. |
+
+### Layer 4 — Consistency
+| Code | Sev | Trigger | Fix |
+|---|---|---|---|
+| `PLACEHOLDER_TEXT` | P0 | Boilerplate token in a string (`예시`, `수정필요`, `lorem`, `{{`, …). | Replace with real content. |
+| `NAP_PHONE_MISMATCH` | P0 | Same business, different `telephone` across entries. | Reconcile to the canonical phone. |
+| `NAP_ADDRESS_MISMATCH` | P0 | Same business, different `streetAddress`. | Reconcile to the canonical address. |
+| `DUPLICATE_ID` | P1 | One `@id` defined ≥2× with differing content. | Make definitions identical, or split the `@id`. |
+| `DANGLING_ID` | P1 | `{"@id": …}` reference to a node never defined. | Define the node, or fix the reference. |
+| `GEO_SWAPPED` | P1 | latitude/longitude transposed (swapping fixes it). | Swap the values. |
+| `GEO_OUT_OF_RANGE` | P1 | Coordinates impossible (lat∉[-90,90] or lon∉[-180,180]). | Correct the coordinates. |
+| `DUPLICATE_DESCRIPTION` | P1 | Same description reused across ≥3 entries. | Write distinct descriptions per page. |
+
+## Triage workflow
+
+1. Sort `defect_log.csv` by severity (already sorted P0→P1→P2 on write).
+2. **P0:** assign an owner, fix, re-run. No P0 may survive into client review.
+3. **P1:** set `owner` + `status`, decide fix-now vs accept; log accepted ones in
+   `templates/decision-log.md`.
+4. **P2:** schedule into the optimization backlog.
+5. Re-run after fixes and confirm no regressions before advancing the stage gate.

custom-skills/16-seo-schema-validator/references/hotel-type-map.md

@@ -0,0 +1,68 @@
+# Hotel Page-Type → Schema-Type Map
+
+The G1 (설계) deliverable: every page template gets an assigned schema `@type` and a
+required-property list *before* anyone authors entries. Locking this map first is what
+prevents the most expensive error — authoring hundreds of entries against the wrong type.
+
+This is the reusable, hotel-domain map. The worked example is JHR (Josun Hotels &
+Resorts, `josunhotel.com`) — a multi-brand, multi-language, multi-property group — but
+the mapping applies to any lodging-group site (it replaces the earlier client-specific
+draft). Adapt the brand/property layer to the client; the page-type → type rules are stable.
+
+## Site shape this map assumes
+
+```
+대표 허브 (group)        →  Organization + WebSite        (one canonical node set, @id-anchored)
+브랜드 허브 (brand)       →  Brand / Organization + Hotel families
+개별 호텔 (property)      →  Hotel / LodgingBusiness / Resort
+  ├─ 객실 (rooms)        →  HotelRoom / Suite (nested or itemList)
+  ├─ 다이닝 (dining)     →  Restaurant / BarOrPub
+  ├─ 시설·웨딩·연회       →  LocalBusiness / MeetingRoom (nested)
+  ├─ 프로모션 (offers)    →  Offer / AggregateOffer
+  └─ FAQ / 안내          →  FAQPage
+```
+
+Each rendered URL also multiplies by **language × device** (ko/en/ja/zh × PC/MOBILE),
+which is why the entry count reaches the thousands. The schema `@type` does **not**
+change across language/device — only the localized string values do. (Use that fact:
+NAP, geo, and `@id` must stay identical across the language variants of one property;
+Layer 4 will catch it when they drift.)
+
+## The map
+
+| Page template (Korean / English) | Primary `@type` | Required (P0) | Add these (recommended) |
+|---|---|---|---|
+| 대표 홈 / group home | `WebSite` (+ `Organization`) | name, url / name, url | publisher, potentialAction(SearchAction), inLanguage / logo, sameAs |
+| 브랜드 허브 / brand hub | `Organization` (+ `Brand`) | name, url | logo, sameAs, brand |
+| 호텔 메인 / property home | `Hotel` (or `LodgingBusiness`, `Resort`) | name, address | telephone, image, priceRange, geo, url, starRating, aggregateRating |
+| 객실 목록·상세 / rooms | `Hotel` w/ `containsPlace`→`HotelRoom`/`Suite`, or `ItemList` | name, address (host) | image, occupancy, bed, amenityFeature |
+| 다이닝 / restaurant | `Restaurant` (or `BarOrPub`) | name, address | servesCuisine, priceRange, telephone, menu, openingHoursSpecification, acceptsReservations |
+| 부대시설·웨딩·연회 / facilities | `LocalBusiness` w/ `MeetingRoom` nested | name, address | telephone, openingHoursSpecification, image, url |
+| 프로모션·패키지 / offers | `Offer` (or `AggregateOffer`) | price, priceCurrency / lowPrice, priceCurrency | availability, url, validFrom, priceValidUntil |
+| 멤버십 / membership | `MemberProgram` | name | hasTiers, hostingOrganization, url |
+| 위치·오시는 길 / location | `Hotel` w/ `geo`→`GeoCoordinates` | name, address | geo (lat/long), hasMap |
+| FAQ / 자주 묻는 질문 | `FAQPage` → `Question`/`Answer` | mainEntity / name, acceptedAnswer / text | — |
+| 공지·매거진·기사 / article | `Article` / `NewsArticle` / `BlogPosting` | headline | author, datePublished, image, dateModified, publisher |
+| 모든 하위 페이지 / breadcrumbs | `BreadcrumbList` → `ListItem` | itemListElement / position | item, name |
+
+## Conventions that keep Layer 4 green
+
+- **Anchor shared nodes by `@id`.** Define `Organization` and `WebSite` once
+  (`https://…/#organization`, `https://…/#website`) and reference them everywhere with
+  `{"@id": "…"}`. Avoids `DANGLING_ID` (define before you reference) and `DUPLICATE_ID`
+  (don't redefine with different content).
+- **One canonical NAP per property.** The same `telephone` and `streetAddress` must
+  appear in every language/device variant of a property, or `NAP_*_MISMATCH` (P0) fires.
+- **Distinct descriptions.** A reused boilerplate description across ≥3 pages →
+  `DUPLICATE_DESCRIPTION` (P1). Write per-page copy.
+- **geo as `{latitude, longitude}`** in decimal degrees; Korea is lat ≈ 33–39, lon ≈
+  124–132. Transposing them trips `GEO_SWAPPED`.
+- **No placeholders.** `예시 / 수정필요 / 임시 / lorem / {{…}}` anywhere → `PLACEHOLDER_TEXT`
+  (P0). The gate exists precisely to stop these from reaching the client.
+
+## Using the map in the lifecycle
+
+- **G1 설계:** fill this table for the client's actual templates; that *is* the schema
+  spec. DoD: every template has a type + required list.
+- **G2 개발:** authors produce entries against it; `--strict` run; zero P0 to advance.
+- **G3+:** the map is the reference reviewers and the validator agree on.

custom-skills/16-seo-schema-validator/references/validation-methodology.md

@@ -0,0 +1,123 @@
+# Validation Methodology
+
+The reasoning behind the 5 layers, and the type → requirement matrix the validator
+enforces. The matrix is the human-readable mirror of `scripts/schema_rules.json` —
+if you change one, change the other.
+
+## Why a machine gate before human review
+
+At a few dozen entries, a person can eyeball JSON-LD. At hundreds (a multi-language,
+multi-device, multi-property hotel site easily reaches 2,000+ URLs), eyeballing
+fails in a predictable way: the reviewer drowns in *mechanical* errors (a missing
+required field, a bad date format, a typo'd URL) and never reaches the *judgement*
+errors that actually need a human (is this the right schema type for this page? is
+this description accurate?).
+
+The fix is not "review harder." It is to split the work by who is best at it:
+
+| Error class | Best checker | This skill |
+|---|---|---|
+| Mechanical (parse, required-present, value format, duplicate, consistency) | A script, every time | Layers 0–4, automated |
+| Judgement (type choice, copy accuracy, intent) | A human, once | Client reviews only P0-free entries |
+
+So the gate runs first. **An entry reaches client review only when it has zero P0.**
+The client then reviews a clean set against a defect report — never raw JSON in a meeting.
+
+## The layers, in order
+
+Each layer assumes the previous one passed for that entry. A fatal L1 failure
+(unparseable JSON, no `@type`) stops deeper layers for that entry — there is nothing
+to inspect.
+
+### L0 — Coverage (needs `--url-list`)
+Compares the canonical URL inventory against the URLs that actually have an entry.
+- `COVERAGE_MISSING` (P1): inventory URL with no authored entry — a gap to fill.
+- `COVERAGE_ORPHAN` (P2): entry whose URL isn't in the inventory — a typo, a stale
+  path, or a list that's out of date. (Expect many orphans if your inventory is a
+  subset; expect ~zero when it's the real canonical list.)
+
+### L1 — Syntax
+The cheapest, hardest blockers. If these fail, nothing downstream is trustworthy.
+- `INVALID_JSON` (P0), `NO_SCHEMA_IN_HTML` (P0, live mode).
+- `MISSING_CONTEXT` / `WRONG_CONTEXT` / `NO_TYPE` / `ENCODING_CORRUPTION` (P1).
+
+### L2 — Vocabulary & value formats
+Is the type known, and are values well-formed?
+- `UNKNOWN_TYPE` (P2; P1 in `--strict`): type isn't in the curated rule set. A
+  *warning*, not an error — add it to `schema_rules.json` if it's intended.
+- `BAD_URL` / `BAD_DATE` / `BAD_LANG` / `BAD_CURRENCY` / `BAD_NUMBER` (P2; P1 strict).
+- `UNEXPECTED_PROPERTY` (P1, `--strict` only): a property not known for a known type.
+  **Off by default** — flagging every unexpected property offline produces exactly the
+  false-positive flood that makes reviewers distrust the tool.
+
+### L3 — Rich-result requirements
+The contract Google enforces for eligibility.
+- `MISSING_REQUIRED` (P0): a required property is absent → the rich result is blocked.
+- `MISSING_RECOMMENDED` (P2): recommended properties absent. **Aggregated to one line
+  per node** (never one defect per property) — this is the single most important
+  noise-control decision in the tool.
+
+### L4 — Consistency (cross-node / cross-entry)
+The errors a per-entry check can't see.
+- `PLACEHOLDER_TEXT` (P0): boilerplate that escaped authoring (`예시`, `수정필요`,
+  `lorem`, `{{`, …). Almost always a real, embarrassing leak.
+- `NAP_PHONE_MISMATCH` / `NAP_ADDRESS_MISMATCH` (P0): the same business shows
+  different Name/Address/Phone across entries — a local-SEO and trust problem.
+- `DUPLICATE_ID` (P1): one `@id` defined twice with different content.
+- `DANGLING_ID` (P1): a `{"@id": …}` reference points at a node never defined.
+- `GEO_SWAPPED` / `GEO_OUT_OF_RANGE` (P1): latitude/longitude transposed or impossible.
+- `DUPLICATE_DESCRIPTION` (P1): the same description reused across ≥3 entries.
+
+## Severity → gate
+
+| Severity | Meaning | Gate effect |
+|---|---|---|
+| **P0** | Blocker. Breaks parsing, blocks the rich result, or publishes wrong data. | **Fails the gate.** Process exits 1. Entry must not reach client review. |
+| **P1** | Fix before launch. Real defect, doesn't block the rich result. | Triage backlog. |
+| **P2** | Optimization. Recommended props, style, orphan URLs. | Optimization backlog. |
+
+Full code list: `defect-taxonomy.md`.
+
+## Type → requirement matrix (mirror of `schema_rules.json`)
+
+`required` missing → **P0**. `recommended` missing → **P2** (aggregated). Anything in
+`allowed` is accepted silently. Properties outside all three are flagged only in `--strict`.
+
+| Type | Required (P0 if missing) | Recommended (P2 if missing) |
+|---|---|---|
+| Organization | name, url | logo, sameAs, contactPoint, address |
+| WebSite | name, url | publisher, potentialAction, inLanguage |
+| WebPage | name | url, isPartOf, primaryImageOfPage, breadcrumb, datePublished, dateModified |
+| Hotel / LodgingBusiness / Resort | name, address | telephone, image, priceRange, geo, url, starRating, aggregateRating |
+| LocalBusiness | name, address | telephone, openingHoursSpecification, geo, image, url, priceRange, aggregateRating |
+| Restaurant / FoodEstablishment | name, address | servesCuisine, priceRange, telephone, menu, openingHoursSpecification |
+| FAQPage | mainEntity | — |
+| Question | name, acceptedAnswer | — |
+| Answer | text | — |
+| BreadcrumbList / ItemList | itemListElement | — |
+| ListItem | position | item, name |
+| Product | name | image, offers, brand, aggregateRating, review, description, sku |
+| Offer | price, priceCurrency | availability, url, validFrom, priceValidUntil |
+| Article / NewsArticle / BlogPosting | headline | author, datePublished, image, dateModified, publisher |
+| Event | name, startDate, location | endDate, offers, performer, image, eventStatus, eventAttendanceMode, organizer |
+| Review | reviewRating, author | datePublished, reviewBody, itemReviewed |
+| AggregateRating | ratingValue | reviewCount, ratingCount, bestRating |
+| MemberProgram | name | hasTiers, hostingOrganization, url |
+
+**Container types** (validated for value formats, but *not* for required/recommended,
+because they only ever appear nested): PostalAddress, GeoCoordinates, ImageObject,
+ContactPoint, OpeningHoursSpecification, Rating, Brand, EntryPoint, Place, OfferCatalog,
+ReserveAction, MeetingRoom, Room/HotelRoom/Suite, MemberProgramTier, Menu/MenuItem, … (full
+list in `schema_rules.json` → `container_types`).
+
+## Extending the rules
+
+Add a type, tighten a requirement, or recognize a new container by editing
+`scripts/schema_rules.json` **only** — no Python change needed:
+- New rich-result type → add to `known_types` with `required` / `recommended` / `allowed`.
+- New nested type to stop "unknown type" warnings → add to `container_types`.
+- New value-format property → add to the relevant `value_formats` group.
+- New placeholder token to catch → add to `placeholder_tokens`.
+
+After any edit, re-run `make_sample.py` + `validate_schema.py` against the fixture to
+confirm you didn't regress.

custom-skills/16-seo-schema-validator/scripts/make_sample.py

@@ -0,0 +1,160 @@
+#!/usr/bin/env python3
+"""
+make_sample.py — generate fixtures/sample_schema.csv.
+
+A small, deliberately FLAWED hotel dataset (Josun-style, fictional values) that
+seeds at least one defect per validation layer. Use it to learn the tool and to
+regression-test changes to validate_schema.py or schema_rules.json:
+
+    python make_sample.py
+    python validate_schema.py ../fixtures/sample_schema.csv --out /tmp/demo_out
+
+Each row's comment names the defect(s) it is designed to trigger.
+"""
+
+import csv
+import json
+from pathlib import Path
+
+OUT = Path(__file__).resolve().parent.parent / "fixtures" / "sample_schema.csv"
+
+CTX = "https://schema.org"
+SHARED_DESC = ("조선호텔앤리조트가 운영하는 럭셔리 호텔로, 도심 속에서 품격 있는 휴식을 "
+               "제공합니다. 최상의 서비스와 시설을 경험하실 수 있습니다.")  # >30 chars, reused 3x
+
+
+def jd(obj):
+    return json.dumps(obj, ensure_ascii=False)
+
+
+# Each tuple: (url, lang, device, page_type, jsonld_string)
+ROWS = []
+
+# 1) CLEAN Organization — only a recommended gap (P2 MISSING_RECOMMENDED, aggregated)
+ROWS.append((
+    "https://www.josunhotel.com/en/brand/grand", "en", "PC", "brand-hub",
+    jd({"@context": CTX, "@type": "Organization", "@id": "https://www.josunhotel.com/#org",
+        "name": "Josun Hotels & Resorts", "url": "https://www.josunhotel.com/",
+        "logo": "https://www.josunhotel.com/logo.png",
+        "sameAs": ["https://www.instagram.com/josunhotelsandresorts/"]}),
+))
+
+# 2) INVALID JSON (P0 INVALID_JSON) — trailing comma, unquoted key
+ROWS.append((
+    "https://www.josunhotel.com/ko/grand", "ko", "PC", "hotel",
+    '{"@context": "https://schema.org", "@type": "Hotel", name: "그랜드조선",}',
+))
+
+# 3) MISSING @type (P1 NO_TYPE)
+ROWS.append((
+    "https://www.josunhotel.com/ko/grand/rooms", "ko", "MOBILE", "rooms",
+    jd({"@context": CTX, "name": "디럭스룸", "url": "https://www.josunhotel.com/ko/grand/rooms"}),
+))
+
+# 4) WRONG @context (P1 WRONG_CONTEXT)
+ROWS.append((
+    "https://www.josunhotel.com/ko/palace", "ko", "PC", "hotel",
+    jd({"@context": "https://example.org", "@type": "Hotel", "name": "조선팰리스",
+        "address": {"@type": "PostalAddress", "streetAddress": "테헤란로 231",
+                    "addressLocality": "서울", "addressCountry": "KR"}}),
+))
+
+# 5) Hotel MISSING REQUIRED address (P0 MISSING_REQUIRED)
+ROWS.append((
+    "https://www.josunhotel.com/ko/lescape", "ko", "PC", "hotel",
+    jd({"@context": CTX, "@type": "Hotel", "name": "레스케이프 호텔",
+        "telephone": "+82-2-317-4000", "description": SHARED_DESC}),
+))
+
+# 6) PLACEHOLDER text (P0 PLACEHOLDER_TEXT)
+ROWS.append((
+    "https://www.josunhotel.com/ko/grand/dining", "ko", "PC", "restaurant",
+    jd({"@context": CTX, "@type": "Restaurant", "name": "예시 레스토랑",
+        "address": {"@type": "PostalAddress", "streetAddress": "수정필요",
+                    "addressCountry": "KR"}, "servesCuisine": "Korean"}),
+))
+
+# 7a + 7b) NAP PHONE MISMATCH (P0 NAP_PHONE_MISMATCH) — same business, two phones
+ROWS.append((
+    "https://www.josunhotel.com/ko/westin", "ko", "PC", "hotel",
+    jd({"@context": CTX, "@type": "Hotel", "name": "웨스틴 조선 서울",
+        "telephone": "+82-2-771-0500",
+        "address": {"@type": "PostalAddress", "streetAddress": "소공로 106",
+                    "addressLocality": "서울", "addressCountry": "KR"},
+        "description": SHARED_DESC}),
+))
+ROWS.append((
+    "https://www.josunhotel.com/en/westin", "en", "PC", "hotel",
+    jd({"@context": CTX, "@type": "Hotel", "name": "웨스틴 조선 서울",
+        "telephone": "+82-2-771-9999",
+        "address": {"@type": "PostalAddress", "streetAddress": "소공로 106",
+                    "addressLocality": "Seoul", "addressCountry": "KR"},
+        "description": SHARED_DESC}),
+))
+
+# 8) DANGLING @id reference (P1 DANGLING_ID) — publisher points at undefined node
+ROWS.append((
+    "https://www.josunhotel.com/ko", "ko", "PC", "home",
+    jd({"@context": CTX, "@type": "WebSite", "name": "조선호텔앤리조트",
+        "url": "https://www.josunhotel.com/",
+        "publisher": {"@id": "https://www.josunhotel.com/#missing-org"}}),
+))
+
+# 9) SWAPPED geo (P1 GEO_SWAPPED) — lat/long transposed for Seoul
+ROWS.append((
+    "https://www.josunhotel.com/ko/grand/location", "ko", "PC", "location",
+    jd({"@context": CTX, "@type": "Hotel", "name": "그랜드 조선 부산",
+        "address": {"@type": "PostalAddress", "streetAddress": "동백로 60",
+                    "addressLocality": "부산", "addressCountry": "KR"},
+        "geo": {"@type": "GeoCoordinates", "latitude": 129.1603, "longitude": 35.1586}}),
+))
+
+# 10) BAD date (P2 BAD_DATE) in an Offer-bearing page
+ROWS.append((
+    "https://www.josunhotel.com/ko/offers/spring", "ko", "PC", "offer",
+    jd({"@context": CTX, "@type": "Offer", "price": "350000", "priceCurrency": "KRW",
+        "validFrom": "2026년 3월 1일", "url": "https://www.josunhotel.com/ko/offers/spring"}),
+))
+
+# 11) BAD currency symbol (P2 BAD_CURRENCY)
+ROWS.append((
+    "https://www.josunhotel.com/ko/offers/dining", "ko", "PC", "offer",
+    jd({"@context": CTX, "@type": "Offer", "price": "120000", "priceCurrency": "₩",
+        "availability": "https://schema.org/InStock"}),
+))
+
+# 12) UNKNOWN type (P2 UNKNOWN_TYPE)
+ROWS.append((
+    "https://www.josunhotel.com/ko/spa", "ko", "PC", "facility",
+    jd({"@context": CTX, "@type": "SpaResort", "name": "조선 스파"}),
+))
+
+# 13) Third reuse of SHARED_DESC → triggers DUPLICATE_DESCRIPTION (P1) across rows 5,7a,7b,13
+ROWS.append((
+    "https://www.josunhotel.com/ko/grand/intro", "ko", "PC", "hotel",
+    jd({"@context": CTX, "@type": "Hotel", "name": "그랜드 조선 제주",
+        "address": {"@type": "PostalAddress", "streetAddress": "중문관광로 75",
+                    "addressLocality": "제주", "addressCountry": "KR"},
+        "description": SHARED_DESC}),
+))
+
+# 14) CLEAN FAQPage — exercises a passing entry (and an inventory-orphan URL for L0 demo)
+ROWS.append((
+    "https://www.josunhotel.com/ko/faq?stale=1", "ko", "MOBILE", "faq",
+    jd({"@context": CTX, "@type": "FAQPage", "mainEntity": [
+        {"@type": "Question", "name": "체크인 시간은 언제인가요?",
+         "acceptedAnswer": {"@type": "Answer", "text": "오후 3시부터 체크인 가능합니다."}}]}),
+))
+
+
+def main():
+    OUT.parent.mkdir(parents=True, exist_ok=True)
+    with open(OUT, "w", newline="", encoding="utf-8-sig") as f:
+        w = csv.writer(f)
+        w.writerow(["url", "언어코드", "PC/MOBILE", "page_type", "스키마"])  # Korean aliases on purpose
+        w.writerows(ROWS)
+    print(f"Wrote {len(ROWS)} entries → {OUT}")
+
+
+if __name__ == "__main__":
+    main()

custom-skills/16-seo-schema-validator/scripts/requirements.txt

@@ -0,0 +1,6 @@
+# validate_schema.py runs on the Python standard library alone for
+# CSV / JSON / JSONL / directory inputs (the offline default).
+#
+# Optional extras, installed only when you need them:
+openpyxl>=3.1   # required to read .xlsx datasets and .xlsx URL inventories
+requests>=2.31  # required only for --live (Mode B) URL fetching

custom-skills/16-seo-schema-validator/scripts/schema_rules.json.bak-20260529

@@ -0,0 +1,200 @@
+{
+  "_meta": {
+    "version": "1.0",
+    "scope": "Curated, hotel-focused subset of schema.org + Google rich-result requirements.",
+    "intent": "Self-contained offline rules (the runtime cannot reach schema.org or Google). Unknown types/properties degrade to warnings, never hard errors, to avoid false positives. To support a new type or tighten a rule, edit THIS file only.",
+    "sources": "schema.org/Hotel, schema.org/LocalBusiness, Google Search Central 'Structured data' rich-result docs (as of 2025)."
+  },
+
+  "valid_contexts": [
+    "https://schema.org",
+    "http://schema.org",
+    "https://schema.org/",
+    "http://schema.org/",
+    "https://www.schema.org",
+    "http://www.schema.org"
+  ],
+
+  "global_properties": [
+    "@context", "@type", "@id", "@graph", "@reverse",
+    "name", "alternateName", "legalName", "description", "disambiguatingDescription",
+    "url", "image", "logo", "sameAs", "identifier", "mainEntityOfPage",
+    "additionalType", "subjectOf", "potentialAction", "inLanguage"
+  ],
+
+  "known_types": {
+    "Organization": {
+      "required": ["name", "url"],
+      "recommended": ["logo", "sameAs", "contactPoint", "address"],
+      "allowed": ["legalName", "foundingDate", "parentOrganization", "subOrganization", "brand", "telephone", "email", "founder", "numberOfEmployees", "memberOf", "hasMerchantReturnPolicy", "member"]
+    },
+    "Corporation": {
+      "required": ["name", "url"],
+      "recommended": ["logo", "sameAs", "address"],
+      "allowed": ["legalName", "foundingDate", "parentOrganization", "tickerSymbol", "telephone", "email", "brand"]
+    },
+    "WebSite": {
+      "required": ["name", "url"],
+      "recommended": ["publisher", "potentialAction", "inLanguage"],
+      "allowed": ["alternateName", "about", "copyrightHolder", "copyrightYear"]
+    },
+    "WebPage": {
+      "required": ["name"],
+      "recommended": ["url", "isPartOf", "primaryImageOfPage", "breadcrumb", "datePublished", "dateModified"],
+      "allowed": ["about", "mentions", "speakable", "lastReviewed", "reviewedBy", "significantLink"]
+    },
+    "LocalBusiness": {
+      "required": ["name", "address"],
+      "recommended": ["telephone", "openingHoursSpecification", "geo", "image", "url", "priceRange", "aggregateRating"],
+      "allowed": ["email", "openingHours", "paymentAccepted", "currenciesAccepted", "areaServed", "hasMap", "department", "menu", "review", "containedInPlace", "containsPlace", "amenityFeature"]
+    },
+    "Hotel": {
+      "required": ["name", "address"],
+      "recommended": ["telephone", "image", "priceRange", "geo", "url", "starRating", "aggregateRating", "checkinTime", "checkoutTime"],
+      "allowed": ["email", "amenityFeature", "petsAllowed", "numberOfRooms", "availableLanguage", "containedInPlace", "containsPlace", "makesOffer", "brand", "currenciesAccepted", "smokingAllowed", "openingHoursSpecification", "audience", "review"]
+    },
+    "LodgingBusiness": {
+      "required": ["name", "address"],
+      "recommended": ["telephone", "image", "priceRange", "geo", "url", "starRating", "aggregateRating", "checkinTime", "checkoutTime"],
+      "allowed": ["email", "amenityFeature", "petsAllowed", "numberOfRooms", "availableLanguage", "containedInPlace", "containsPlace", "makesOffer", "currenciesAccepted", "smokingAllowed"]
+    },
+    "Resort": {
+      "required": ["name", "address"],
+      "recommended": ["telephone", "image", "priceRange", "geo", "url", "starRating", "aggregateRating"],
+      "allowed": ["email", "amenityFeature", "numberOfRooms", "containedInPlace", "containsPlace", "checkinTime", "checkoutTime"]
+    },
+    "Restaurant": {
+      "required": ["name", "address"],
+      "recommended": ["servesCuisine", "priceRange", "telephone", "menu", "openingHoursSpecification", "image", "url", "geo", "acceptsReservations"],
+      "allowed": ["email", "hasMenu", "starRating", "aggregateRating", "review", "containedInPlace", "smokingAllowed"]
+    },
+    "FoodEstablishment": {
+      "required": ["name", "address"],
+      "recommended": ["servesCuisine", "priceRange", "telephone", "menu", "openingHoursSpecification"],
+      "allowed": ["email", "hasMenu", "acceptsReservations", "containedInPlace"]
+    },
+    "BarOrPub": {
+      "required": ["name", "address"],
+      "recommended": ["telephone", "openingHoursSpecification", "priceRange", "servesCuisine"],
+      "allowed": ["menu", "hasMenu", "image", "url"]
+    },
+    "FAQPage": {
+      "required": ["mainEntity"],
+      "recommended": [],
+      "allowed": ["about", "headline", "datePublished", "dateModified"]
+    },
+    "Question": {
+      "required": ["name", "acceptedAnswer"],
+      "recommended": [],
+      "allowed": ["text", "answerCount", "suggestedAnswer", "upvoteCount", "author"]
+    },
+    "Answer": {
+      "required": ["text"],
+      "recommended": [],
+      "allowed": ["url", "upvoteCount", "author", "dateCreated"]
+    },
+    "BreadcrumbList": {
+      "required": ["itemListElement"],
+      "recommended": [],
+      "allowed": ["numberOfItems", "itemListOrder"]
+    },
+    "ItemList": {
+      "required": ["itemListElement"],
+      "recommended": [],
+      "allowed": ["numberOfItems", "itemListOrder"]
+    },
+    "ListItem": {
+      "required": ["position"],
+      "recommended": ["item", "name"],
+      "allowed": ["url", "image", "nextItem", "previousItem"]
+    },
+    "Product": {
+      "required": ["name"],
+      "recommended": ["image", "offers", "brand", "aggregateRating", "review", "description", "sku"],
+      "allowed": ["gtin", "gtin13", "gtin8", "gtin12", "mpn", "color", "material", "category", "audience", "isVariantOf", "additionalProperty", "hasMerchantReturnPolicy"]
+    },
+    "Offer": {
+      "required": ["price", "priceCurrency"],
+      "recommended": ["availability", "url", "validFrom", "priceValidUntil"],
+      "allowed": ["itemCondition", "seller", "eligibleRegion", "priceSpecification", "shippingDetails", "availabilityStarts"]
+    },
+    "AggregateOffer": {
+      "required": ["lowPrice", "priceCurrency"],
+      "recommended": ["highPrice", "offerCount"],
+      "allowed": ["offers", "availability"]
+    },
+    "Article": {
+      "required": ["headline"],
+      "recommended": ["author", "datePublished", "image", "dateModified", "publisher"],
+      "allowed": ["articleBody", "articleSection", "wordCount", "keywords", "speakable"]
+    },
+    "NewsArticle": {
+      "required": ["headline"],
+      "recommended": ["author", "datePublished", "image", "dateModified", "publisher"],
+      "allowed": ["articleBody", "dateline", "printSection"]
+    },
+    "BlogPosting": {
+      "required": ["headline"],
+      "recommended": ["author", "datePublished", "image", "dateModified", "publisher"],
+      "allowed": ["articleBody", "keywords", "wordCount"]
+    },
+    "Event": {
+      "required": ["name", "startDate", "location"],
+      "recommended": ["endDate", "offers", "performer", "image", "eventStatus", "eventAttendanceMode", "organizer"],
+      "allowed": ["doorTime", "previousStartDate", "typicalAgeRange", "maximumAttendeeCapacity"]
+    },
+    "Review": {
+      "required": ["reviewRating", "author"],
+      "recommended": ["datePublished", "reviewBody", "itemReviewed"],
+      "allowed": ["publisher", "name"]
+    },
+    "AggregateRating": {
+      "required": ["ratingValue"],
+      "recommended": ["reviewCount", "ratingCount", "bestRating"],
+      "allowed": ["worstRating", "itemReviewed"]
+    },
+    "MemberProgram": {
+      "required": ["name"],
+      "recommended": ["hasTiers", "hostingOrganization", "url"],
+      "allowed": ["description", "membershipPointsEarned"]
+    }
+  },
+
+  "container_types": [
+    "PostalAddress", "GeoCoordinates", "GeoShape", "ImageObject", "VideoObject",
+    "ContactPoint", "OpeningHoursSpecification", "Rating", "QuantitativeValue",
+    "MonetaryAmount", "PriceSpecification", "Brand", "EntryPoint", "Place",
+    "OfferCatalog", "ReserveAction", "OrderAction", "SearchAction", "ViewAction",
+    "MeetingRoom", "Room", "HotelRoom", "Suite", "LocationFeatureSpecification",
+    "MemberProgramTier", "MobileApplication", "WebApplication", "SoftwareApplication",
+    "Menu", "MenuItem", "MenuSection", "Country", "AdministrativeArea", "Duration",
+    "PropertyValue", "Person", "Audience", "Language"
+  ],
+
+  "value_formats": {
+    "url_props": ["url", "logo", "sameAs", "image", "contentUrl", "thumbnailUrl", "target", "urlTemplate", "installUrl", "menu", "hasMap", "downloadUrl", "embedUrl"],
+    "date_props": ["datePublished", "dateModified", "dateCreated", "startDate", "endDate", "validFrom", "validThrough", "priceValidUntil", "foundingDate", "uploadDate", "availabilityStarts", "availabilityEnds", "lastReviewed", "previousStartDate"],
+    "lang_props": ["inLanguage", "availableLanguage"],
+    "currency_props": ["priceCurrency", "currenciesAccepted"],
+    "number_props": ["price", "lowPrice", "highPrice", "ratingValue", "reviewCount", "ratingCount", "bestRating", "worstRating", "position", "numberOfRooms", "maxValue", "minValue", "offerCount"]
+  },
+
+  "valid_currencies": ["KRW", "USD", "EUR", "JPY", "CNY", "GBP", "HKD", "SGD", "THB", "AUD", "CAD", "CHF", "TWD", "MYR", "PHP", "VND", "IDR", "INR"],
+
+  "valid_language_codes": ["ko", "en", "ja", "zh", "zh-CN", "zh-TW", "zh-Hans", "zh-Hant", "ko-KR", "en-US", "en-GB", "ja-JP", "fr", "de", "es", "ru", "th", "vi", "id", "ms"],
+
+  "placeholder_tokens": [
+    "lorem ipsum", "lorem", "ipsum", "dolor sit", "todo", "tbd", "fixme",
+    "xxx", "yyy", "zzz", "placeholder", "insert here", "insert text",
+    "example.com", "your-domain", "yourdomain", "changeme", "sample text",
+    "{{", "}}", "<insert", "[insert", "n/a", "샘플", "예시", "여기에",
+    "변경필요", "수정필요", "입력필요", "내용입력", "테스트", "임시"
+  ],
+
+  "geo": {
+    "lat_min": -90.0, "lat_max": 90.0,
+    "lon_min": -180.0, "lon_max": 180.0,
+    "kr_lat_range": [33.0, 39.0],
+    "kr_lon_range": [124.0, 132.0]
+  }
+}

custom-skills/16-seo-schema-validator/scripts/schema_rules.json.bak2-20260529

@@ -0,0 +1,876 @@
+{
+  "_meta": {
+    "version": "1.1",
+    "scope": "Curated, hotel-focused subset of schema.org + Google rich-result requirements.",
+    "intent": "Self-contained offline rules (the runtime cannot reach schema.org or Google). Unknown types/properties degrade to warnings, never hard errors, to avoid false positives. To support a new type or tighten a rule, edit THIS file only. [v1.1 2026-05-29: +EventVenue/ExerciseGym/SportsActivityLocation/HealthAndBeautyBusiness/DaySpa/CafeOrCoffeeShop, +LodgingReservation container, Organization/Corporation url->recommended per Google, +slogan/founder/ceo/parentOrganization/award/hasOfferCatalog/openingDate/isPartOf allowances.]",
+    "sources": "schema.org/Hotel, schema.org/LocalBusiness, Google Search Central 'Structured data' rich-result docs (as of 2025)."
+  },
+  "valid_contexts": [
+    "https://schema.org",
+    "http://schema.org",
+    "https://schema.org/",
+    "http://schema.org/",
+    "https://www.schema.org",
+    "http://www.schema.org"
+  ],
+  "global_properties": [
+    "@context",
+    "@type",
+    "@id",
+    "@graph",
+    "@reverse",
+    "name",
+    "alternateName",
+    "legalName",
+    "description",
+    "disambiguatingDescription",
+    "url",
+    "image",
+    "logo",
+    "sameAs",
+    "identifier",
+    "mainEntityOfPage",
+    "additionalType",
+    "subjectOf",
+    "potentialAction",
+    "inLanguage",
+    "isPartOf"
+  ],
+  "known_types": {
+    "Organization": {
+      "required": [
+        "name"
+      ],
+      "recommended": [
+        "logo",
+        "sameAs",
+        "contactPoint",
+        "address",
+        "url"
+      ],
+      "allowed": [
+        "legalName",
+        "foundingDate",
+        "parentOrganization",
+        "subOrganization",
+        "brand",
+        "telephone",
+        "email",
+        "founder",
+        "numberOfEmployees",
+        "memberOf",
+        "hasMerchantReturnPolicy",
+        "member",
+        "slogan",
+        "hasOfferCatalog"
+      ]
+    },
+    "Corporation": {
+      "required": [
+        "name"
+      ],
+      "recommended": [
+        "logo",
+        "sameAs",
+        "address",
+        "url"
+      ],
+      "allowed": [
+        "legalName",
+        "foundingDate",
+        "parentOrganization",
+        "tickerSymbol",
+        "telephone",
+        "email",
+        "brand",
+        "founder",
+        "ceo",
+        "subOrganization",
+        "memberOf",
+        "slogan",
+        "hasOfferCatalog"
+      ]
+    },
+    "WebSite": {
+      "required": [
+        "name",
+        "url"
+      ],
+      "recommended": [
+        "publisher",
+        "potentialAction",
+        "inLanguage"
+      ],
+      "allowed": [
+        "alternateName",
+        "about",
+        "copyrightHolder",
+        "copyrightYear"
+      ]
+    },
+    "WebPage": {
+      "required": [
+        "name"
+      ],
+      "recommended": [
+        "url",
+        "isPartOf",
+        "primaryImageOfPage",
+        "breadcrumb",
+        "datePublished",
+        "dateModified"
+      ],
+      "allowed": [
+        "about",
+        "mentions",
+        "speakable",
+        "lastReviewed",
+        "reviewedBy",
+        "significantLink"
+      ]
+    },
+    "LocalBusiness": {
+      "required": [
+        "name",
+        "address"
+      ],
+      "recommended": [
+        "telephone",
+        "openingHoursSpecification",
+        "geo",
+        "image",
+        "url",
+        "priceRange",
+        "aggregateRating"
+      ],
+      "allowed": [
+        "email",
+        "openingHours",
+        "paymentAccepted",
+        "currenciesAccepted",
+        "areaServed",
+        "hasMap",
+        "department",
+        "menu",
+        "review",
+        "containedInPlace",
+        "containsPlace",
+        "amenityFeature"
+      ]
+    },
+    "Hotel": {
+      "required": [
+        "name",
+        "address"
+      ],
+      "recommended": [
+        "telephone",
+        "image",
+        "priceRange",
+        "geo",
+        "url",
+        "starRating",
+        "aggregateRating",
+        "checkinTime",
+        "checkoutTime"
+      ],
+      "allowed": [
+        "email",
+        "amenityFeature",
+        "petsAllowed",
+        "numberOfRooms",
+        "availableLanguage",
+        "containedInPlace",
+        "containsPlace",
+        "makesOffer",
+        "brand",
+        "currenciesAccepted",
+        "smokingAllowed",
+        "openingHoursSpecification",
+        "audience",
+        "review",
+        "parentOrganization",
+        "openingDate",
+        "award"
+      ]
+    },
+    "LodgingBusiness": {
+      "required": [
+        "name",
+        "address"
+      ],
+      "recommended": [
+        "telephone",
+        "image",
+        "priceRange",
+        "geo",
+        "url",
+        "starRating",
+        "aggregateRating",
+        "checkinTime",
+        "checkoutTime"
+      ],
+      "allowed": [
+        "email",
+        "amenityFeature",
+        "petsAllowed",
+        "numberOfRooms",
+        "availableLanguage",
+        "containedInPlace",
+        "containsPlace",
+        "makesOffer",
+        "currenciesAccepted",
+        "smokingAllowed"
+      ]
+    },
+    "Resort": {
+      "required": [
+        "name",
+        "address"
+      ],
+      "recommended": [
+        "telephone",
+        "image",
+        "priceRange",
+        "geo",
+        "url",
+        "starRating",
+        "aggregateRating"
+      ],
+      "allowed": [
+        "email",
+        "amenityFeature",
+        "numberOfRooms",
+        "containedInPlace",
+        "containsPlace",
+        "checkinTime",
+        "checkoutTime"
+      ]
+    },
+    "Restaurant": {
+      "required": [
+        "name",
+        "address"
+      ],
+      "recommended": [
+        "servesCuisine",
+        "priceRange",
+        "telephone",
+        "menu",
+        "openingHoursSpecification",
+        "image",
+        "url",
+        "geo",
+        "acceptsReservations"
+      ],
+      "allowed": [
+        "email",
+        "hasMenu",
+        "starRating",
+        "aggregateRating",
+        "review",
+        "containedInPlace",
+        "smokingAllowed",
+        "award"
+      ]
+    },
+    "FoodEstablishment": {
+      "required": [
+        "name",
+        "address"
+      ],
+      "recommended": [
+        "servesCuisine",
+        "priceRange",
+        "telephone",
+        "menu",
+        "openingHoursSpecification"
+      ],
+      "allowed": [
+        "email",
+        "hasMenu",
+        "acceptsReservations",
+        "containedInPlace"
+      ]
+    },
+    "BarOrPub": {
+      "required": [
+        "name",
+        "address"
+      ],
+      "recommended": [
+        "telephone",
+        "openingHoursSpecification",
+        "priceRange",
+        "servesCuisine"
+      ],
+      "allowed": [
+        "menu",
+        "hasMenu",
+        "image",
+        "url",
+        "containedInPlace",
+        "acceptsReservations",
+        "award"
+      ]
+    },
+    "FAQPage": {
+      "required": [
+        "mainEntity"
+      ],
+      "recommended": [],
+      "allowed": [
+        "about",
+        "headline",
+        "datePublished",
+        "dateModified",
+        "isPartOf"
+      ]
+    },
+    "Question": {
+      "required": [
+        "name",
+        "acceptedAnswer"
+      ],
+      "recommended": [],
+      "allowed": [
+        "text",
+        "answerCount",
+        "suggestedAnswer",
+        "upvoteCount",
+        "author"
+      ]
+    },
+    "Answer": {
+      "required": [
+        "text"
+      ],
+      "recommended": [],
+      "allowed": [
+        "url",
+        "upvoteCount",
+        "author",
+        "dateCreated"
+      ]
+    },
+    "BreadcrumbList": {
+      "required": [
+        "itemListElement"
+      ],
+      "recommended": [],
+      "allowed": [
+        "numberOfItems",
+        "itemListOrder"
+      ]
+    },
+    "ItemList": {
+      "required": [
+        "itemListElement"
+      ],
+      "recommended": [],
+      "allowed": [
+        "numberOfItems",
+        "itemListOrder"
+      ]
+    },
+    "ListItem": {
+      "required": [
+        "position"
+      ],
+      "recommended": [
+        "item",
+        "name"
+      ],
+      "allowed": [
+        "url",
+        "image",
+        "nextItem",
+        "previousItem"
+      ]
+    },
+    "Product": {
+      "required": [
+        "name"
+      ],
+      "recommended": [
+        "image",
+        "offers",
+        "brand",
+        "aggregateRating",
+        "review",
+        "description",
+        "sku"
+      ],
+      "allowed": [
+        "gtin",
+        "gtin13",
+        "gtin8",
+        "gtin12",
+        "mpn",
+        "color",
+        "material",
+        "category",
+        "audience",
+        "isVariantOf",
+        "additionalProperty",
+        "hasMerchantReturnPolicy"
+      ]
+    },
+    "Offer": {
+      "required": [
+        "price",
+        "priceCurrency"
+      ],
+      "recommended": [
+        "availability",
+        "url",
+        "validFrom",
+        "priceValidUntil"
+      ],
+      "allowed": [
+        "itemCondition",
+        "seller",
+        "eligibleRegion",
+        "priceSpecification",
+        "shippingDetails",
+        "availabilityStarts"
+      ]
+    },
+    "AggregateOffer": {
+      "required": [
+        "lowPrice",
+        "priceCurrency"
+      ],
+      "recommended": [
+        "highPrice",
+        "offerCount"
+      ],
+      "allowed": [
+        "offers",
+        "availability"
+      ]
+    },
+    "Article": {
+      "required": [
+        "headline"
+      ],
+      "recommended": [
+        "author",
+        "datePublished",
+        "image",
+        "dateModified",
+        "publisher"
+      ],
+      "allowed": [
+        "articleBody",
+        "articleSection",
+        "wordCount",
+        "keywords",
+        "speakable"
+      ]
+    },
+    "NewsArticle": {
+      "required": [
+        "headline"
+      ],
+      "recommended": [
+        "author",
+        "datePublished",
+        "image",
+        "dateModified",
+        "publisher"
+      ],
+      "allowed": [
+        "articleBody",
+        "dateline",
+        "printSection"
+      ]
+    },
+    "BlogPosting": {
+      "required": [
+        "headline"
+      ],
+      "recommended": [
+        "author",
+        "datePublished",
+        "image",
+        "dateModified",
+        "publisher"
+      ],
+      "allowed": [
+        "articleBody",
+        "keywords",
+        "wordCount"
+      ]
+    },
+    "Event": {
+      "required": [
+        "name",
+        "startDate",
+        "location"
+      ],
+      "recommended": [
+        "endDate",
+        "offers",
+        "performer",
+        "image",
+        "eventStatus",
+        "eventAttendanceMode",
+        "organizer"
+      ],
+      "allowed": [
+        "doorTime",
+        "previousStartDate",
+        "typicalAgeRange",
+        "maximumAttendeeCapacity"
+      ]
+    },
+    "Review": {
+      "required": [
+        "reviewRating",
+        "author"
+      ],
+      "recommended": [
+        "datePublished",
+        "reviewBody",
+        "itemReviewed"
+      ],
+      "allowed": [
+        "publisher",
+        "name"
+      ]
+    },
+    "AggregateRating": {
+      "required": [
+        "ratingValue"
+      ],
+      "recommended": [
+        "reviewCount",
+        "ratingCount",
+        "bestRating"
+      ],
+      "allowed": [
+        "worstRating",
+        "itemReviewed"
+      ]
+    },
+    "MemberProgram": {
+      "required": [
+        "name"
+      ],
+      "recommended": [
+        "hasTiers",
+        "hostingOrganization",
+        "url"
+      ],
+      "allowed": [
+        "description",
+        "membershipPointsEarned"
+      ]
+    },
+    "EventVenue": {
+      "required": [
+        "name"
+      ],
+      "recommended": [
+        "url",
+        "address",
+        "maximumAttendeeCapacity",
+        "image"
+      ],
+      "allowed": [
+        "containedInPlace",
+        "amenityFeature",
+        "openingHoursSpecification",
+        "photo",
+        "telephone",
+        "alternateName",
+        "geo"
+      ]
+    },
+    "ExerciseGym": {
+      "required": [
+        "name"
+      ],
+      "recommended": [
+        "url",
+        "address",
+        "openingHoursSpecification",
+        "image"
+      ],
+      "allowed": [
+        "containedInPlace",
+        "amenityFeature",
+        "telephone",
+        "priceRange",
+        "alternateName"
+      ]
+    },
+    "SportsActivityLocation": {
+      "required": [
+        "name"
+      ],
+      "recommended": [
+        "url",
+        "address"
+      ],
+      "allowed": [
+        "containedInPlace",
+        "amenityFeature",
+        "openingHoursSpecification",
+        "telephone",
+        "alternateName"
+      ]
+    },
+    "HealthAndBeautyBusiness": {
+      "required": [
+        "name"
+      ],
+      "recommended": [
+        "url",
+        "address",
+        "telephone",
+        "openingHoursSpecification",
+        "priceRange",
+        "image"
+      ],
+      "allowed": [
+        "containedInPlace",
+        "amenityFeature",
+        "potentialAction",
+        "parentOrganization",
+        "geo",
+        "alternateName"
+      ]
+    },
+    "DaySpa": {
+      "required": [
+        "name"
+      ],
+      "recommended": [
+        "url",
+        "address",
+        "telephone",
+        "openingHoursSpecification",
+        "priceRange",
+        "image"
+      ],
+      "allowed": [
+        "containedInPlace",
+        "amenityFeature",
+        "potentialAction",
+        "parentOrganization",
+        "geo",
+        "alternateName"
+      ]
+    },
+    "CafeOrCoffeeShop": {
+      "required": [
+        "name"
+      ],
+      "recommended": [
+        "url",
+        "address",
+        "servesCuisine",
+        "priceRange",
+        "telephone",
+        "openingHoursSpecification",
+        "image"
+      ],
+      "allowed": [
+        "menu",
+        "hasMenu",
+        "containedInPlace",
+        "acceptsReservations",
+        "alternateName"
+      ]
+    }
+  },
+  "container_types": [
+    "PostalAddress",
+    "GeoCoordinates",
+    "GeoShape",
+    "ImageObject",
+    "VideoObject",
+    "ContactPoint",
+    "OpeningHoursSpecification",
+    "Rating",
+    "QuantitativeValue",
+    "MonetaryAmount",
+    "PriceSpecification",
+    "Brand",
+    "EntryPoint",
+    "Place",
+    "OfferCatalog",
+    "ReserveAction",
+    "OrderAction",
+    "SearchAction",
+    "ViewAction",
+    "MeetingRoom",
+    "Room",
+    "HotelRoom",
+    "Suite",
+    "LocationFeatureSpecification",
+    "MemberProgramTier",
+    "MobileApplication",
+    "WebApplication",
+    "SoftwareApplication",
+    "Menu",
+    "MenuItem",
+    "MenuSection",
+    "Country",
+    "AdministrativeArea",
+    "Duration",
+    "PropertyValue",
+    "Person",
+    "Audience",
+    "Language",
+    "LodgingReservation"
+  ],
+  "value_formats": {
+    "url_props": [
+      "url",
+      "logo",
+      "sameAs",
+      "image",
+      "contentUrl",
+      "thumbnailUrl",
+      "target",
+      "urlTemplate",
+      "installUrl",
+      "menu",
+      "hasMap",
+      "downloadUrl",
+      "embedUrl"
+    ],
+    "date_props": [
+      "datePublished",
+      "dateModified",
+      "dateCreated",
+      "startDate",
+      "endDate",
+      "validFrom",
+      "validThrough",
+      "priceValidUntil",
+      "foundingDate",
+      "uploadDate",
+      "availabilityStarts",
+      "availabilityEnds",
+      "lastReviewed",
+      "previousStartDate"
+    ],
+    "lang_props": [
+      "inLanguage",
+      "availableLanguage"
+    ],
+    "currency_props": [
+      "priceCurrency",
+      "currenciesAccepted"
+    ],
+    "number_props": [
+      "price",
+      "lowPrice",
+      "highPrice",
+      "ratingValue",
+      "reviewCount",
+      "ratingCount",
+      "bestRating",
+      "worstRating",
+      "position",
+      "numberOfRooms",
+      "maxValue",
+      "minValue",
+      "offerCount"
+    ]
+  },
+  "valid_currencies": [
+    "KRW",
+    "USD",
+    "EUR",
+    "JPY",
+    "CNY",
+    "GBP",
+    "HKD",
+    "SGD",
+    "THB",
+    "AUD",
+    "CAD",
+    "CHF",
+    "TWD",
+    "MYR",
+    "PHP",
+    "VND",
+    "IDR",
+    "INR"
+  ],
+  "valid_language_codes": [
+    "ko",
+    "en",
+    "ja",
+    "zh",
+    "zh-CN",
+    "zh-TW",
+    "zh-Hans",
+    "zh-Hant",
+    "ko-KR",
+    "en-US",
+    "en-GB",
+    "ja-JP",
+    "fr",
+    "de",
+    "es",
+    "ru",
+    "th",
+    "vi",
+    "id",
+    "ms"
+  ],
+  "placeholder_tokens": [
+    "lorem ipsum",
+    "lorem",
+    "ipsum",
+    "dolor sit",
+    "todo",
+    "tbd",
+    "fixme",
+    "xxx",
+    "yyy",
+    "zzz",
+    "placeholder",
+    "insert here",
+    "insert text",
+    "example.com",
+    "your-domain",
+    "yourdomain",
+    "changeme",
+    "sample text",
+    "{{",
+    "}}",
+    "<insert",
+    "[insert",
+    "n/a",
+    "샘플",
+    "예시",
+    "여기에",
+    "변경필요",
+    "수정필요",
+    "입력필요",
+    "내용입력",
+    "테스트",
+    "임시"
+  ],
+  "geo": {
+    "lat_min": -90.0,
+    "lat_max": 90.0,
+    "lon_min": -180.0,
+    "lon_max": 180.0,
+    "kr_lat_range": [
+      33.0,
+      39.0
+    ],
+    "kr_lon_range": [
+      124.0,
+      132.0
+    ]
+  }
+}

custom-skills/16-seo-schema-validator/scripts/validate_schema.py.bak-20260529

@@ -0,0 +1,854 @@
+#!/usr/bin/env python3
+"""
+validate_schema.py — 5-layer offline JSON-LD schema validator.
+
+WHY THIS EXISTS
+---------------
+When a client reviews hundreds of authored schema entries and says "there are too
+many errors," the root cause is almost always that nobody ran a machine lint first.
+Humans end up eyeballing raw JSON in a meeting. This tool moves every cheap,
+machine-checkable error OUT of human review and INTO an automated gate that runs
+first — so the client only ever sees clean, P0-free entries plus a defect report.
+
+It is OFFLINE by design (the runtime cannot reach schema.org or Google). All rules
+live in schema_rules.json; unknown types/properties degrade to warnings, never hard
+errors, so the gate does not invent false positives.
+
+THE 5 LAYERS
+------------
+  L0 Coverage    — URLs with no entry; entries whose URL isn't in the inventory.
+  L1 Syntax      — invalid JSON, bad/missing @context, missing @type, encoding corruption.
+  L2 Vocabulary  — unknown type, value-format errors (URL/date/lang/currency/number),
+                   (strict only) unexpected properties on a known type.
+  L3 Rich-result — Google REQUIRED property missing (blocks rich result); recommended absent.
+  L4 Consistency — NAP mismatch, @id duplicates/dangling refs, swapped geo,
+                   placeholder text, duplicate descriptions across entries.
+
+GATE: PASS iff zero P0. Process exits 1 when the gate fails (so CI/`&&` chains stop).
+
+Usage:
+  python validate_schema.py DATASET [--url-list URLLIST] [--out DIR]
+                            [--strict] [--no-recommended]
+                            [--live URL ...] [--rules schema_rules.json]
+DATASET may be .xlsx / .csv (one row per entry, a JSON-LD column) / .jsonl / .json
+/ a directory of .json|.jsonld files. With --live, validate live URLs instead.
+"""
+
+import argparse
+import csv
+import json
+import os
+import re
+import sys
+from collections import Counter, defaultdict
+from pathlib import Path
+
+RULES_DEFAULT = Path(__file__).resolve().parent / "schema_rules.json"
+
+SEVERITY_ORDER = {"P0": 0, "P1": 1, "P2": 2}
+
+# Header aliases for tabular input. Keys are normalized (lowercased, spaces removed).
+COLUMN_ALIASES = {
+    "jsonld": ["jsonld", "jsonld", "json-ld", "json_ld", "schema", "schemamarkup",
+               "structureddata", "structured_data", "markup", "스키마", "구조화데이터",
+               "구조화된데이터", "jsonldcode", "스키마코드"],
+    "url": ["url", "메뉴url", "pageurl", "주소", "링크", "loc", "uri", "캐노니컬", "canonical"],
+    "lang": ["lang", "language", "언어", "언어코드", "locale", "lng"],
+    "device": ["device", "pc/mobile", "pcmobile", "pc_mobile", "platform", "디바이스", "기기"],
+    "page_type": ["page_type", "pagetype", "type", "페이지유형", "페이지타입", "menulevel",
+                  "menu_level", "메뉴레벨", "template", "템플릿", "유형"],
+}
+
+URL_RE = re.compile(r"^https?://[^\s]+$", re.IGNORECASE)
+# ISO-8601 date or datetime (date, date+time, optional tz). Loose but rejects free text.
+DATE_RE = re.compile(
+    r"^\d{4}-\d{2}-\d{2}"
+    r"(?:[T ]\d{2}:\d{2}(?::\d{2})?(?:\.\d+)?(?:Z|[+-]\d{2}:?\d{2})?)?$"
+)
+LANG_RE = re.compile(r"^[a-zA-Z]{2,3}(?:-[A-Za-z0-9]{2,4})?$")
+JSONLD_SCRIPT_RE = re.compile(
+    r'<script[^>]+type=["\']application/ld\+json["\'][^>]*>(.*?)</script>',
+    re.IGNORECASE | re.DOTALL,
+)
+
+
+# --------------------------------------------------------------------------- #
+# Defect collection
+# --------------------------------------------------------------------------- #
+class DefectLog:
+    """Accumulates findings. One row per finding, ready for triage."""
+
+    def __init__(self):
+        self.rows = []
+
+    def add(self, severity, layer, code, message, entry_id="", url="", node_type=""):
+        self.rows.append({
+            "entry_id": str(entry_id),
+            "url": url or "",
+            "node_type": node_type or "",
+            "layer": layer,
+            "code": code,
+            "severity": severity,
+            "message": message,
+            "status": "open",
+            "owner": "",
+            "note": "",
+        })
+
+    def counts(self):
+        c = Counter(r["severity"] for r in self.rows)
+        return {"P0": c.get("P0", 0), "P1": c.get("P1", 0), "P2": c.get("P2", 0)}
+
+
+# --------------------------------------------------------------------------- #
+# Input adapters  (Mode A: authored dataset / Mode B: live URLs)
+# --------------------------------------------------------------------------- #
+def _norm_header(h):
+    return re.sub(r"\s+", "", str(h or "").strip().lower())
+
+
+def _detect_columns(headers):
+    """Map normalized headers to canonical column roles. Returns {role: index}."""
+    found = {}
+    for idx, h in enumerate(headers):
+        nh = _norm_header(h)
+        for role, aliases in COLUMN_ALIASES.items():
+            if role in found:
+                continue
+            if nh in aliases:
+                found[role] = idx
+    return found
+
+
+def _row_to_entry(row, cols, entry_id, source_ref):
+    def cell(role):
+        i = cols.get(role)
+        if i is None or i >= len(row):
+            return None
+        v = row[i]
+        return None if v is None else str(v).strip()
+    raw = cell("jsonld")
+    if not raw:
+        return None  # blank JSON-LD cell → no entry to validate
+    return {
+        "entry_id": entry_id,
+        "url": cell("url") or "",
+        "lang": cell("lang") or "",
+        "device": cell("device") or "",
+        "page_type": cell("page_type") or "",
+        "raw": raw,
+        "source_ref": source_ref,
+    }
+
+
+def _load_csv(path):
+    entries = []
+    with open(path, newline="", encoding="utf-8-sig") as f:
+        reader = csv.reader(f)
+        rows = list(reader)
+    if not rows:
+        return entries
+    cols = _detect_columns(rows[0])
+    if "jsonld" not in cols:
+        raise ValueError(
+            f"No JSON-LD column found in {path}. Looked for: "
+            f"{', '.join(COLUMN_ALIASES['jsonld'][:6])} … Headers were: {rows[0]}"
+        )
+    for n, row in enumerate(rows[1:], start=2):
+        e = _row_to_entry(row, cols, f"{Path(path).stem}#r{n}", f"{path}:row{n}")
+        if e:
+            entries.append(e)
+    return entries
+
+
+def _load_xlsx(path):
+    try:
+        from openpyxl import load_workbook
+    except ImportError:
+        raise SystemExit(
+            "Reading .xlsx needs openpyxl: pip install openpyxl\n"
+            "(or export the sheet to .csv and pass that instead)."
+        )
+    entries = []
+    wb = load_workbook(path, read_only=True, data_only=True)
+    for sheet in wb.worksheets:
+        rows = list(sheet.iter_rows(values_only=True))
+        if not rows:
+            continue
+        cols = _detect_columns(rows[0])
+        if "jsonld" not in cols:
+            continue  # a tab without a JSON-LD column (e.g. summary) — skip silently
+        for n, row in enumerate(rows[1:], start=2):
+            e = _row_to_entry(list(row), cols, f"{sheet.title}#r{n}",
+                              f"{path}:{sheet.title}:row{n}")
+            if e:
+                entries.append(e)
+    if not entries:
+        raise ValueError(
+            f"No sheet in {path} had a recognizable JSON-LD column. "
+            f"Looked for: {', '.join(COLUMN_ALIASES['jsonld'][:6])} …"
+        )
+    return entries
+
+
+def _looks_like_schema(obj):
+    """True if a parsed object is itself JSON-LD (vs a wrapper row)."""
+    if isinstance(obj, list):
+        return True
+    if isinstance(obj, dict):
+        return any(k in obj for k in ("@context", "@type", "@graph"))
+    return False
+
+
+def _wrapper_to_entry(obj, entry_id, source_ref):
+    """A JSONL/JSON wrapper object that carries url/lang + a jsonld payload."""
+    cols = {k: k for k in obj.keys()}
+    norm = {_norm_header(k): k for k in obj.keys()}
+    def pick(role):
+        for alias in COLUMN_ALIASES[role]:
+            if alias in norm:
+                v = obj[norm[alias]]
+                return v
+        return None
+    payload = pick("jsonld")
+    raw = payload if isinstance(payload, str) else json.dumps(payload, ensure_ascii=False)
+    url = pick("url")
+    return {
+        "entry_id": entry_id,
+        "url": str(url).strip() if url else "",
+        "lang": str(pick("lang") or "").strip(),
+        "device": str(pick("device") or "").strip(),
+        "page_type": str(pick("page_type") or "").strip(),
+        "raw": raw,
+        "source_ref": source_ref,
+    }
+
+
+def _load_jsonl(path):
+    entries = []
+    with open(path, encoding="utf-8") as f:
+        for n, line in enumerate(f, start=1):
+            line = line.strip()
+            if not line:
+                continue
+            sref = f"{path}:line{n}"
+            try:
+                obj = json.loads(line)
+            except json.JSONDecodeError:
+                # Keep the bad line so L1 reports it as a syntax error.
+                entries.append({"entry_id": f"{Path(path).stem}#l{n}", "url": "",
+                                "lang": "", "device": "", "page_type": "",
+                                "raw": line, "source_ref": sref})
+                continue
+            eid = f"{Path(path).stem}#l{n}"
+            if _looks_like_schema(obj):
+                entries.append({"entry_id": eid, "url": "", "lang": "", "device": "",
+                                "page_type": "", "raw": line, "source_ref": sref})
+            else:
+                entries.append(_wrapper_to_entry(obj, eid, sref))
+    return entries
+
+
+def _load_json(path):
+    with open(path, encoding="utf-8") as f:
+        data = json.load(f)
+    entries = []
+    if isinstance(data, dict) and not _looks_like_schema(data) and all(
+        isinstance(v, (dict, list, str)) for v in data.values()
+    ) and not any(k.startswith("@") for k in data):
+        # url -> jsonld map
+        for url, payload in data.items():
+            raw = payload if isinstance(payload, str) else json.dumps(payload, ensure_ascii=False)
+            entries.append({"entry_id": url, "url": url, "lang": "", "device": "",
+                            "page_type": "", "raw": raw, "source_ref": f"{path}:{url}"})
+    elif isinstance(data, list):
+        for n, item in enumerate(data, start=1):
+            sref = f"{path}:[{n}]"
+            eid = f"{Path(path).stem}#{n}"
+            if _looks_like_schema(item) or not isinstance(item, dict):
+                raw = item if isinstance(item, str) else json.dumps(item, ensure_ascii=False)
+                entries.append({"entry_id": eid, "url": "", "lang": "", "device": "",
+                                "page_type": "", "raw": raw, "source_ref": sref})
+            else:
+                entries.append(_wrapper_to_entry(item, eid, sref))
+    else:
+        entries.append({"entry_id": Path(path).stem, "url": "", "lang": "", "device": "",
+                        "page_type": "", "raw": json.dumps(data, ensure_ascii=False),
+                        "source_ref": path})
+    return entries
+
+
+def _load_dir(path):
+    entries = []
+    for p in sorted(Path(path).rglob("*")):
+        if p.suffix.lower() in (".json", ".jsonld"):
+            entries.append({"entry_id": p.stem, "url": "", "lang": "", "device": "",
+                            "page_type": "", "raw": p.read_text(encoding="utf-8"),
+                            "source_ref": str(p)})
+    if not entries:
+        raise ValueError(f"No .json/.jsonld files found under {path}")
+    return entries
+
+
+def _load_live(urls):
+    try:
+        import requests
+    except ImportError:
+        raise SystemExit("Live mode (--live) needs requests: pip install requests")
+    entries = []
+    headers = {"User-Agent": "Mozilla/5.0 (compatible; SchemaValidator/1.0)"}
+    for url in urls:
+        try:
+            resp = requests.get(url, headers=headers, timeout=20)
+            resp.raise_for_status()
+        except Exception as exc:  # noqa: BLE001 — best-effort live fetch
+            entries.append({"entry_id": url, "url": url, "lang": "", "device": "",
+                            "page_type": "", "raw": "", "source_ref": url,
+                            "_fetch_error": str(exc)})
+            continue
+        scripts = JSONLD_SCRIPT_RE.findall(resp.text)
+        if not scripts:
+            entries.append({"entry_id": url, "url": url, "lang": "", "device": "",
+                            "page_type": "", "raw": "", "source_ref": url,
+                            "_no_schema": True})
+            continue
+        for i, block in enumerate(scripts, start=1):
+            entries.append({"entry_id": f"{url}#{i}", "url": url, "lang": "",
+                            "device": "", "page_type": "", "raw": block.strip(),
+                            "source_ref": f"{url} (script {i})"})
+    return entries
+
+
+def load_entries(input_path, live_urls):
+    if live_urls:
+        return _load_live(live_urls)
+    p = Path(input_path)
+    if p.is_dir():
+        return _load_dir(p)
+    suffix = p.suffix.lower()
+    if suffix == ".csv":
+        return _load_csv(p)
+    if suffix in (".xlsx", ".xlsm"):
+        return _load_xlsx(p)
+    if suffix == ".jsonl":
+        return _load_jsonl(p)
+    if suffix in (".json", ".jsonld"):
+        return _load_json(p)
+    raise ValueError(f"Unsupported input: {input_path} (suffix {suffix!r})")
+
+
+# --------------------------------------------------------------------------- #
+# Node helpers
+# --------------------------------------------------------------------------- #
+def type_of(node):
+    """Return the primary @type as a string (first if it's a list)."""
+    t = node.get("@type")
+    if isinstance(t, list):
+        return t[0] if t else ""
+    return t or ""
+
+
+def iter_typed_nodes(parsed):
+    """Yield every dict that has an @type, top-level and nested (recursively)."""
+    seen = []
+
+    def walk(obj):
+        if isinstance(obj, dict):
+            if "@type" in obj:
+                seen.append(obj)
+            for v in obj.values():
+                walk(v)
+        elif isinstance(obj, list):
+            for v in obj:
+                walk(v)
+
+    # @graph documents: walk the graph; otherwise walk the object/array directly.
+    if isinstance(parsed, dict) and "@graph" in parsed:
+        walk(parsed["@graph"])
+    else:
+        walk(parsed)
+    return seen
+
+
+def all_strings(obj):
+    """Yield (key, value) for every string value anywhere in the structure."""
+    if isinstance(obj, dict):
+        for k, v in obj.items():
+            if isinstance(v, str):
+                yield k, v
+            else:
+                yield from all_strings(v)
+    elif isinstance(obj, list):
+        for v in obj:
+            yield from all_strings(v)
+
+
+def normalize_name(s):
+    return re.sub(r"\s+", " ", str(s or "").strip().lower())
+
+
+def first_text(value):
+    """Coerce a property value to a comparable scalar (handles list/dict)."""
+    if isinstance(value, list):
+        return first_text(value[0]) if value else ""
+    if isinstance(value, dict):
+        return value.get("name") or value.get("@id") or value.get("streetAddress") or ""
+    return value
+
+
+# --------------------------------------------------------------------------- #
+# Layer 0 — Coverage
+# --------------------------------------------------------------------------- #
+def load_url_inventory(url_list_path):
+    urls = set()
+    p = Path(url_list_path)
+    suffix = p.suffix.lower()
+    if suffix in (".xlsx", ".xlsm"):
+        from openpyxl import load_workbook
+        wb = load_workbook(p, read_only=True, data_only=True)
+        for sheet in wb.worksheets:
+            for row in sheet.iter_rows(values_only=True):
+                for cell in row:
+                    if isinstance(cell, str) and URL_RE.match(cell.strip()):
+                        urls.add(cell.strip())
+    elif suffix == ".csv":
+        with open(p, newline="", encoding="utf-8-sig") as f:
+            for row in csv.reader(f):
+                for cell in row:
+                    if isinstance(cell, str) and URL_RE.match(cell.strip()):
+                        urls.add(cell.strip())
+    else:  # plain text, one URL per line
+        for line in p.read_text(encoding="utf-8").splitlines():
+            line = line.strip()
+            if URL_RE.match(line):
+                urls.add(line)
+    return urls
+
+
+def layer0_coverage(entries, inventory, defects):
+    entry_urls = {e["url"] for e in entries if e.get("url")}
+    missing = inventory - entry_urls
+    for url in sorted(missing):
+        defects.add("P1", "L0", "COVERAGE_MISSING",
+                    "Inventory URL has no authored schema entry.", url=url)
+    orphans = entry_urls - inventory
+    for url in sorted(orphans):
+        defects.add("P2", "L0", "COVERAGE_ORPHAN",
+                    "Entry URL is not in the canonical URL inventory "
+                    "(typo, stale path, or missing from list).", url=url)
+
+
+# --------------------------------------------------------------------------- #
+# Layer 1 — Syntax
+# --------------------------------------------------------------------------- #
+def layer1_syntax(entry, rules, defects):
+    """Parse + structural checks. Returns parsed object or None (fatal)."""
+    eid, url = entry["entry_id"], entry["url"]
+    if entry.get("_fetch_error"):
+        defects.add("P1", "L1", "FETCH_ERROR",
+                    f"Could not fetch live URL: {entry['_fetch_error']}", eid, url)
+        return None
+    if entry.get("_no_schema"):
+        defects.add("P0", "L1", "NO_SCHEMA_IN_HTML",
+                    "Live page has no application/ld+json script block.", eid, url)
+        return None
+    raw = entry["raw"]
+    if "<22>" in raw:
+        defects.add("P1", "L1", "ENCODING_CORRUPTION",
+                    "Replacement character (\\ufffd) present — encoding corruption.",
+                    eid, url)
+    try:
+        parsed = json.loads(raw)
+    except json.JSONDecodeError as exc:
+        defects.add("P0", "L1", "INVALID_JSON",
+                    f"JSON does not parse: {exc.msg} at line {exc.lineno} col {exc.colno}.",
+                    eid, url)
+        return None
+
+    nodes = iter_typed_nodes(parsed)
+    if not nodes:
+        defects.add("P1", "L1", "NO_TYPE",
+                    "No @type found anywhere in the entry — not a usable schema object.",
+                    eid, url)
+
+    # @context lives at the top of the document; nested nodes inherit it.
+    if isinstance(parsed, dict):
+        ctx = parsed.get("@context")
+        if ctx is None:
+            defects.add("P1", "L1", "MISSING_CONTEXT",
+                        "Top-level @context is missing.", eid, url)
+        else:
+            ctx_urls = [ctx] if isinstance(ctx, str) else (
+                [c for c in ctx if isinstance(c, str)] if isinstance(ctx, list) else []
+            )
+            valid = rules["valid_contexts"]
+            if ctx_urls and not any(c.rstrip("/") in [v.rstrip("/") for v in valid]
+                                    for c in ctx_urls):
+                defects.add("P1", "L1", "WRONG_CONTEXT",
+                            f"@context is not schema.org: {ctx_urls}.", eid, url)
+    return parsed
+
+
+# --------------------------------------------------------------------------- #
+# Layer 2 — Vocabulary + value formats
+# --------------------------------------------------------------------------- #
+def _check_value_formats(node, rules, defects, eid, url, ntype, severity):
+    vf = rules["value_formats"]
+
+    def each(value):
+        if isinstance(value, list):
+            for v in value:
+                yield from each(v)
+        else:
+            yield value
+
+    for prop, value in node.items():
+        if prop.startswith("@"):
+            continue
+        if prop in vf["url_props"]:
+            for v in each(value):
+                if isinstance(v, str) and not URL_RE.match(v.strip()):
+                    defects.add(severity, "L2", "BAD_URL",
+                                f"'{prop}' is not an http(s) URL: {v!r}.", eid, url, ntype)
+        if prop in vf["date_props"]:
+            for v in each(value):
+                if isinstance(v, str) and not DATE_RE.match(v.strip()):
+                    defects.add(severity, "L2", "BAD_DATE",
+                                f"'{prop}' is not ISO-8601: {v!r}.", eid, url, ntype)
+        if prop in vf["lang_props"]:
+            for v in each(value):
+                if isinstance(v, str) and not LANG_RE.match(v.strip()):
+                    defects.add(severity, "L2", "BAD_LANG",
+                                f"'{prop}' is not a BCP-47 language code: {v!r}.",
+                                eid, url, ntype)
+        if prop in vf["currency_props"]:
+            for v in each(value):
+                if isinstance(v, str) and not re.match(r"^[A-Z]{3}$", v.strip()):
+                    defects.add(severity, "L2", "BAD_CURRENCY",
+                                f"'{prop}' is not a 3-letter ISO-4217 code: {v!r}.",
+                                eid, url, ntype)
+        if prop in vf["number_props"]:
+            for v in each(value):
+                if isinstance(v, str):
+                    try:
+                        float(v.replace(",", ""))
+                    except ValueError:
+                        defects.add(severity, "L2", "BAD_NUMBER",
+                                    f"'{prop}' is not numeric: {v!r}.", eid, url, ntype)
+
+
+def layer2_vocabulary(node, rules, defects, eid, url, strict):
+    ntype = type_of(node)
+    known = rules["known_types"]
+    containers = set(rules["container_types"])
+    minor = "P1" if strict else "P2"
+
+    if ntype and ntype not in known and ntype not in containers:
+        defects.add(minor, "L2", "UNKNOWN_TYPE",
+                    f"@type '{ntype}' is not in the curated rule set "
+                    "(treated as a warning — add it to schema_rules.json if intended).",
+                    eid, url, ntype)
+
+    _check_value_formats(node, rules, defects, eid, url, ntype, minor)
+
+    # Unexpected-property check is OPT-IN (--strict). Off by default to avoid the
+    # exact noise explosion that makes clients say "too many errors".
+    if strict and ntype in known:
+        spec = known[ntype]
+        allowed = set(spec["required"]) | set(spec["recommended"]) | set(spec["allowed"])
+        allowed |= set(rules["global_properties"])
+        for prop in node:
+            if prop.startswith("@"):
+                continue
+            if prop not in allowed:
+                defects.add("P1", "L2", "UNEXPECTED_PROPERTY",
+                            f"'{prop}' is not a known property of {ntype} (strict mode).",
+                            eid, url, ntype)
+
+
+# --------------------------------------------------------------------------- #
+# Layer 3 — Rich-result (required / recommended)
+# --------------------------------------------------------------------------- #
+def layer3_richresult(node, rules, defects, eid, url, no_recommended):
+    ntype = type_of(node)
+    known = rules["known_types"]
+    if ntype not in known:
+        return  # containers + unknown types have no required-property contract
+    spec = known[ntype]
+
+    for prop in spec["required"]:
+        if not node.get(prop):
+            defects.add("P0", "L3", "MISSING_REQUIRED",
+                        f"{ntype} is missing required property '{prop}' "
+                        "(blocks the rich result).", eid, url, ntype)
+
+    if not no_recommended:
+        missing_rec = [p for p in spec["recommended"] if not node.get(p)]
+        if missing_rec:
+            # Aggregate to ONE line per node — never one defect per property.
+            defects.add("P2", "L3", "MISSING_RECOMMENDED",
+                        f"{ntype} is missing recommended properties: "
+                        f"{', '.join(missing_rec)}.", eid, url, ntype)
+
+
+# --------------------------------------------------------------------------- #
+# Layer 4 — Consistency (cross-node / cross-entry)
+# --------------------------------------------------------------------------- #
+NAP_TYPES = {"Organization", "Corporation", "LocalBusiness", "Hotel",
+             "LodgingBusiness", "Resort", "Restaurant", "FoodEstablishment", "BarOrPub"}
+
+
+def _address_street(node):
+    addr = node.get("address")
+    if isinstance(addr, dict):
+        return normalize_name(addr.get("streetAddress"))
+    if isinstance(addr, list) and addr and isinstance(addr[0], dict):
+        return normalize_name(addr[0].get("streetAddress"))
+    return ""
+
+
+def _walk_ids(obj, defined, referenced):
+    """Collect @id definitions vs pure references by walking the whole document.
+
+    A *reference* is an object whose only key is @id (e.g. {"@id": "...#org"}).
+    A *definition* is any object carrying @id plus other content. References live
+    in untyped wrapper dicts, so this must walk the raw doc — not just typed nodes.
+    """
+    if isinstance(obj, dict):
+        nid = obj.get("@id")
+        if nid:
+            if set(obj.keys()) == {"@id"}:
+                referenced.add(nid)
+            else:
+                defined.setdefault(nid, []).append(obj)
+        for v in obj.values():
+            _walk_ids(v, defined, referenced)
+    elif isinstance(obj, list):
+        for v in obj:
+            _walk_ids(v, defined, referenced)
+
+
+def layer4_consistency(node_index, parsed_docs, rules, defects):
+    """node_index: (entry, node) for every TYPED node.
+    parsed_docs: (entry, parsed) for every entry that parsed — used for @id scan."""
+    # ---- placeholder text (P0) ----
+    tokens = [t.lower() for t in rules["placeholder_tokens"]]
+    for entry, node in node_index:
+        ntype = type_of(node)
+        for key, val in all_strings(node):
+            low = val.lower()
+            hit = next((t for t in tokens if t in low), None)
+            if hit:
+                defects.add("P0", "L4", "PLACEHOLDER_TEXT",
+                            f"Placeholder/boilerplate token {hit!r} in '{key}': {val[:60]!r}.",
+                            entry["entry_id"], entry["url"], ntype)
+                break  # one placeholder defect per node is enough signal
+
+    # ---- NAP consistency (P0) ----
+    by_name = defaultdict(list)
+    for entry, node in node_index:
+        if type_of(node) in NAP_TYPES and node.get("name"):
+            by_name[normalize_name(first_text(node.get("name")))].append((entry, node))
+    for name, group in by_name.items():
+        phones = {str(first_text(n.get("telephone"))).strip()
+                  for _, n in group if n.get("telephone")}
+        streets = {_address_street(n) for _, n in group if _address_street(n)}
+        if len(phones) > 1:
+            defects.add("P0", "L4", "NAP_PHONE_MISMATCH",
+                        f"Business '{name}' has conflicting telephone values across "
+                        f"entries: {sorted(phones)}.", entry_id="(dataset)")
+        if len(streets) > 1:
+            defects.add("P0", "L4", "NAP_ADDRESS_MISMATCH",
+                        f"Business '{name}' has conflicting streetAddress values across "
+                        f"entries: {sorted(streets)}.", entry_id="(dataset)")
+
+    # ---- @id duplicates + dangling references (P1) ----
+    defined = {}        # @id -> list of definition dicts (walked across all docs)
+    referenced = set()  # @id values used purely as references
+    for _, parsed in parsed_docs:
+        _walk_ids(parsed, defined, referenced)
+    for nid, defs in defined.items():
+        if len(defs) > 1:
+            # duplicate only matters if the definitions actually differ
+            shapes = {json.dumps(n, sort_keys=True, ensure_ascii=False) for n in defs}
+            if len(shapes) > 1:
+                defects.add("P1", "L4", "DUPLICATE_ID",
+                            f"@id {nid!r} is defined {len(defs)} times with differing content.",
+                            entry_id="(dataset)")
+    for nid in sorted(referenced - set(defined)):
+        defects.add("P1", "L4", "DANGLING_ID",
+                    f"@id reference {nid!r} points to a node that is never defined.",
+                    entry_id="(dataset)")
+
+    # ---- swapped / out-of-range geo (P1) ----
+    g = rules["geo"]
+    for entry, node in node_index:
+        if type_of(node) != "GeoCoordinates":
+            continue
+        try:
+            lat = float(first_text(node.get("latitude")))
+            lon = float(first_text(node.get("longitude")))
+        except (TypeError, ValueError):
+            continue
+        lat_ok = g["lat_min"] <= lat <= g["lat_max"]
+        lon_ok = g["lon_min"] <= lon <= g["lon_max"]
+        if lat_ok and lon_ok:
+            continue  # both in valid global range
+        # Invalid — distinguish a clean transposition from plain garbage.
+        swap_ok = (g["lat_min"] <= lon <= g["lat_max"]) and (g["lon_min"] <= lat <= g["lon_max"])
+        if swap_ok:
+            defects.add("P1", "L4", "GEO_SWAPPED",
+                        f"GeoCoordinates look transposed (latitude={lat}, longitude={lon}) "
+                        "— swapping them yields valid coordinates.",
+                        entry["entry_id"], entry["url"], "GeoCoordinates")
+        else:
+            defects.add("P1", "L4", "GEO_OUT_OF_RANGE",
+                        f"GeoCoordinates out of range (latitude={lat}, longitude={lon}).",
+                        entry["entry_id"], entry["url"], "GeoCoordinates")
+
+    # ---- duplicate descriptions across entries (P1) ----
+    desc_groups = defaultdict(set)
+    for entry, node in node_index:
+        d = first_text(node.get("description"))
+        if isinstance(d, str) and len(d.strip()) >= 30:
+            desc_groups[d.strip()].add(entry["entry_id"])
+    for desc, eids in desc_groups.items():
+        if len(eids) >= 3:
+            defects.add("P1", "L4", "DUPLICATE_DESCRIPTION",
+                        f"Identical description reused across {len(eids)} entries "
+                        f"(e.g. {sorted(eids)[:3]}): {desc[:50]!r}…", entry_id="(dataset)")
+
+
+# --------------------------------------------------------------------------- #
+# Orchestration + output
+# --------------------------------------------------------------------------- #
+def run(entries, rules, inventory, strict, no_recommended):
+    defects = DefectLog()
+    if inventory is not None:
+        layer0_coverage(entries, inventory, defects)
+
+    node_index = []
+    parsed_docs = []
+    valid_entries = 0
+    for entry in entries:
+        parsed = layer1_syntax(entry, rules, defects)
+        if parsed is None:
+            continue
+        valid_entries += 1
+        parsed_docs.append((entry, parsed))
+        for node in iter_typed_nodes(parsed):
+            layer2_vocabulary(node, rules, defects, entry["entry_id"], entry["url"], strict)
+            layer3_richresult(node, rules, defects, entry["entry_id"], entry["url"],
+                              no_recommended)
+            node_index.append((entry, node))
+
+    layer4_consistency(node_index, parsed_docs, rules, defects)
+    return defects, valid_entries, len(node_index)
+
+
+def write_outputs(defects, outdir, meta):
+    outdir = Path(outdir)
+    outdir.mkdir(parents=True, exist_ok=True)
+
+    # defect_log.csv — the client-facing triage artifact
+    fields = ["entry_id", "url", "node_type", "layer", "code", "severity",
+              "message", "status", "owner", "note"]
+    rows = sorted(defects.rows, key=lambda r: (SEVERITY_ORDER[r["severity"]],
+                                               r["layer"], r["code"]))
+    with open(outdir / "defect_log.csv", "w", newline="", encoding="utf-8-sig") as f:
+        w = csv.DictWriter(f, fieldnames=fields)
+        w.writeheader()
+        w.writerows(rows)
+
+    counts = defects.counts()
+    gate = "PASS" if counts["P0"] == 0 else "FAIL"
+    by_code = Counter((r["severity"], r["code"]) for r in defects.rows)
+
+    # results.json — machine-readable
+    results = {
+        "summary": {**meta, **counts, "total": len(rows), "gate": gate},
+        "by_code": [{"severity": s, "code": c, "count": n}
+                    for (s, c), n in by_code.most_common()],
+        "defects": rows,
+    }
+    (outdir / "results.json").write_text(
+        json.dumps(results, ensure_ascii=False, indent=2), encoding="utf-8")
+
+    # report.md — human summary
+    lines = [
+        "# Schema Validation Report", "",
+        f"- Entries read: **{meta['entries']}**  |  parsed OK: **{meta['valid_entries']}**  "
+        f"|  nodes checked: **{meta['nodes']}**",
+        f"- Defects: **P0 {counts['P0']}** · **P1 {counts['P1']}** · **P2 {counts['P2']}** "
+        f"(total {len(rows)})",
+        "",
+        f"## Gate: **{gate}**",
+        ("> ✅ Zero P0 — entries may advance to client review."
+         if gate == "PASS" else
+         "> ⛔ P0 present — these entries must NOT reach client review. Fix P0 first."),
+        "",
+        "## Defects by code", "",
+        "| Severity | Code | Count |", "|---|---|---|",
+    ]
+    for (sev, code), n in by_code.most_common():
+        lines.append(f"| {sev} | {code} | {n} |")
+
+    p0 = [r for r in rows if r["severity"] == "P0"]
+    if p0:
+        lines += ["", "## P0 blockers (top 15)", "",
+                  "| Entry | Type | Code | Message |", "|---|---|---|---|"]
+        for r in p0[:15]:
+            msg = r["message"].replace("|", "\\|")
+            lines.append(f"| {r['entry_id']} | {r['node_type']} | {r['code']} | {msg} |")
+
+    lines += ["", "## Next step",
+              ("Triage P1 in `defect_log.csv`; client reviews the clean entries against this report."
+               if gate == "PASS" else
+               "Assign and fix every P0, re-run the validator, and only then open client review."),
+              ""]
+    (outdir / "report.md").write_text("\n".join(lines), encoding="utf-8")
+    return gate, counts
+
+
+def main(argv=None):
+    ap = argparse.ArgumentParser(description="5-layer offline JSON-LD schema validator.")
+    ap.add_argument("dataset", nargs="?", help="xlsx/csv/jsonl/json file or a directory")
+    ap.add_argument("--url-list", help="canonical URL inventory (xlsx/csv/txt) → enables Layer 0")
+    ap.add_argument("--out", default="schema_qa_out", help="output directory")
+    ap.add_argument("--strict", action="store_true",
+                    help="unexpected props on known types → P1; unknown types → P1")
+    ap.add_argument("--no-recommended", action="store_true",
+                    help="drop L3 recommended (P2) findings — highest-signal gate")
+    ap.add_argument("--live", nargs="+", metavar="URL",
+                    help="Mode B: validate live URLs (extract embedded JSON-LD)")
+    ap.add_argument("--rules", default=str(RULES_DEFAULT), help="path to schema_rules.json")
+    args = ap.parse_args(argv)
+
+    if not args.dataset and not args.live:
+        ap.error("provide a DATASET path or --live URL ...")
+
+    rules = json.loads(Path(args.rules).read_text(encoding="utf-8"))
+
+    try:
+        entries = load_entries(args.dataset, args.live)
+    except (ValueError, FileNotFoundError) as exc:
+        print(f"ERROR loading input: {exc}", file=sys.stderr)
+        return 2
+
+    inventory = load_url_inventory(args.url_list) if args.url_list else None
+
+    defects, valid_entries, nodes = run(entries, rules, inventory,
+                                        args.strict, args.no_recommended)
+    meta = {"entries": len(entries), "valid_entries": valid_entries, "nodes": nodes,
+            "mode": "B-live" if args.live else "A-dataset", "strict": args.strict,
+            "coverage": inventory is not None}
+    gate, counts = write_outputs(defects, args.out, meta)
+
+    print(f"[{gate}] entries={len(entries)} nodes={nodes} "
+          f"P0={counts['P0']} P1={counts['P1']} P2={counts['P2']} → {args.out}/")
+    # Exit 1 when the gate fails so CI and `&&` chains stop on P0.
+    return 0 if gate == "PASS" else 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())

custom-skills/16-seo-schema-validator/templates/client-qa-report-template.md

@@ -0,0 +1,57 @@
+# 구조화 데이터 QA 리포트 — {{프로젝트명}}
+
+> 클라이언트 검토용. **원본 JSON이 아니라 결함 리포트를 검토합니다.**
+> 이 리포트에 오른 엔트리는 모두 기계 검증(Layer 0–4)을 통과한 **P0 0건** 상태입니다.
+
+| 항목 | 값 |
+|---|---|
+| 데이터셋 | `{{dataset_파일명}}` |
+| 검증 일시 | {{YYYY-MM-DD HH:MM}} |
+| 검증 모드 | A — Dataset QA (배포 전) / B — Live audit (배포 후) |
+| 엔트리 수 | {{entries}} (파싱 성공 {{valid_entries}}, 노드 {{nodes}}) |
+| **게이트** | **{{PASS / FAIL}}** (PASS = P0 0건) |
+| 결함 | P0 {{n}} · P1 {{n}} · P2 {{n}} |
+| Audit ID | SCHEMA-{{YYYYMMDD}}-{{NNN}} |
+
+## 1. 한눈에 보기
+
+- ✅ **검토 가능 엔트리**: P0 0건을 통과한 {{n}}개 — 아래 판단 항목만 확인해 주세요.
+- ⛔ **보류 엔트리**(있다면): P0 {{n}}건으로 검토 대상에서 제외. 수정 후 재검증합니다.
+- 이번 검토에서 **사람의 판단이 필요한 것**은 기계가 잡지 못하는 두 가지뿐입니다:
+  1. 페이지에 맞는 스키마 **타입**이 선택되었는가
+  2. 표시되는 **문구(설명·이름)**가 사실과 정확히 일치하는가
+
+## 2. 결함 요약 (코드별)
+
+| 심각도 | 코드 | 건수 | 의미 |
+|---|---|---|---|
+| P0 | {{CODE}} | {{n}} | {{한 줄 설명}} |
+| P1 | {{CODE}} | {{n}} | {{한 줄 설명}} |
+| P2 | {{CODE}} | {{n}} | {{한 줄 설명}} |
+
+> 코드 정의: `references/defect-taxonomy.md`. 전체 목록: 첨부 `defect_log.csv`.
+
+## 3. P0 블로커 (있을 경우 — 검토 전 수정 필수)
+
+| 엔트리 | 타입 | 코드 | 내용 | 담당 | 상태 |
+|---|---|---|---|---|---|
+| {{entry_id}} | {{type}} | {{CODE}} | {{message}} | {{owner}} | open |
+
+## 4. 클라이언트 확인 요청 (판단 항목)
+
+기계가 통과시킨 엔트리 중, 사람의 확인이 필요한 항목입니다.
+
+| # | URL / 페이지 | 확인 요청 | 비고 |
+|---|---|---|---|
+| 1 | {{url}} | 이 페이지에 `{{@type}}` 타입이 맞습니까? | |
+| 2 | {{url}} | 설명/이름 문구가 정확합니까? | |
+
+## 5. 다음 단계
+
+- **PASS인 경우**: 위 4번 판단 항목 확정 → 배포 단계(G4 안정화)로 이동, 샘플을 Google
+  Rich Results Test로 최종 확인.
+- **FAIL인 경우**: P0 담당 배정 → 수정 → 재검증(`validate_schema.py`) → 본 리포트 갱신.
+- P1 처리 방침(수정/수용)은 `decision-log.md`에 기록합니다.
+
+---
+*생성: 16-seo-schema-validator · 첨부: `report.md`, `defect_log.csv`, `results.json`*

custom-skills/16-seo-schema-validator/templates/decision-log.md

@@ -0,0 +1,39 @@
+# P1 Decision Log — {{프로젝트명}}
+
+P0 is non-negotiable: every P0 is fixed before launch (the gate enforces it). **P1 is
+where judgement lives** — some P1s get fixed, some get consciously accepted. This log
+records *which, by whom, and why*, so an accepted P1 is a decision on the record, not a
+silently ignored defect. It is the G3 (테스트) deliverable.
+
+## How to use
+
+1. Open `defect_log.csv`, filter to `severity = P1`.
+2. For each P1 (or each group of identical P1s), add a row below.
+3. Decision is one of: **Fix** (will correct before launch) / **Accept** (ship as-is,
+   with rationale) / **Defer** (post-launch backlog).
+4. An `Accept`/`Defer` needs a named approver. `Fix` needs an owner + target date.
+5. Re-run the validator after the fixes; confirm the fixed P1s are gone.
+
+## Log
+
+| # | Code | Entry / scope | Summary | Decision | Owner / Approver | Target / Date | Rationale |
+|---|---|---|---|---|---|---|---|
+| 1 | {{CODE}} | {{entry_id or (dataset)}} | {{one line}} | Fix / Accept / Defer | {{name}} | {{YYYY-MM-DD}} | {{why}} |
+| 2 | | | | | | | |
+| 3 | | | | | | | |
+
+## Standing decisions (apply to all entries unless overridden)
+
+Record cross-cutting calls once here instead of per row — e.g. "MISSING_RECOMMENDED for
+`starRating` is accepted group-wide: not contractually rated." Reduces log noise.
+
+| Code | Standing decision | Approver | Date |
+|---|---|---|---|
+| {{CODE}} | Accept group-wide — {{reason}} | {{name}} | {{YYYY-MM-DD}} |
+
+## Sign-off
+
+| Stage gate | Condition | Confirmed by | Date |
+|---|---|---|---|
+| G3 테스트 | All P1 triaged (Fix/Accept/Defer), decisions logged above | {{name}} | {{date}} |
+| G4 안정화 | P0 = 0, all "Fix" P1 closed, online validator green on sample | {{name}} | {{date}} |

custom-skills/17-seo-schema-generator/SKILL.md

@@ -0,0 +1,126 @@
+---
+name: seo-schema-generator
+description: |
+  Generates validation-ready JSON-LD structured data for a site, covering BOTH
+  scenarios: (1) from an existing website — extract facts from live pages; and
+  (2) from collected sources for a not-yet-published site — reconcile conflicting
+  facts into a provenance-tracked claims register. Both modes emit the same claims
+  register, build pruned drafts from type templates (no placeholders shipped), and
+  hand off to 16-seo-schema-validator (generate then validate, gate = zero P0).
+  Triggers: generate schema, create JSON-LD, schema markup, structured data generator,
+  source-to-schema, pre-launch schema, claims register, 스키마 생성, 스키마 저작,
+  구조화 데이터 생성, 미발행 사이트 스키마, 기존 사이트 스키마 추출.
+version: "2.0"
+author: OurDigital / D.intelligence
+environment: Code
+---
+
+# SEO Schema Generator (17)
+
+Author JSON-LD for a site — whether the pages already exist or the site is not yet
+published. Both cases are error-prone for the same reason: facts must be turned into
+schema without leaking conflicts, gaps, or placeholders. This skill makes that reliable
+by routing **both scenarios through one pivot — a claims register** — then generating
+pruned drafts that hand off cleanly to the `16-seo-schema-validator` gate.
+
+**Generate (17) → Validate (16).** This skill produces drafts; 16 is the QA gate.
+
+## Two modes, one pipeline
+
+The only thing that differs between the scenarios is **where facts come from**.
+Everything after the claims register is identical.
+
+| | **Mode 1 — from an existing site** | **Mode 2 — from collected sources** |
+|---|---|---|
+| When | Site has pages but lacks (or needs better) schema | Site not published yet (no DOM) |
+| Source of truth | the live pages | scattered, conflicting sources (DART, Wikidata, brochures) |
+| Seed the register with | `scripts/extract_site_claims.py` | manual research → `templates/claims-register.csv` |
+| Hard part | extraction & mapping | authority hierarchy + entity reconciliation |
+| Conflicts | rare (one source) | frequent → resolve before shipping |
+
+```
+ Mode 1 (extract_site_claims.py)─┐
+                                 ├─▶ claims_register.csv ─▶ build_schema_drafts.py ─▶ drafts/*.jsonld
+ Mode 2 (research + register)────┘        (the pivot)                               └─▶ schema_drafts_dataset.csv
+                                                                                          │
+                                                                    16-seo-schema-validator ▼ (gate: zero P0)
+```
+
+## The claims register — the core idea
+
+A **claims register** is a provenance-tracked, conflict-resolved fact table. Columns:
+`entity_id, entity_type, property, value, lang, url, source_ids, authority, confidence,
+conflict, status, note`. Dotted `property` paths nest (`address.streetAddress`);
+pipe-separate array values (`a|b|c`).
+
+**Only `CONFIRMED`, non-conflicting claims become schema.** Everything else (PENDING,
+CONFLICT, REJECTED, EMPTY) is excluded and reported — never shipped. An unfilled
+template slot is **deleted**, never emitted as `{{…}}` or `TODO` (placeholder leakage
+is the #1 pre-launch P0).
+
+## How to run
+
+```bash
+# Try the bundled sample first (Mode 2)
+python scripts/make_sample.py
+python scripts/build_schema_drafts.py fixtures/sample_claims.csv --out drafts_out
+
+# MODE 1 — existing site → register (URLs, or local .html / a directory offline)
+python scripts/extract_site_claims.py https://example.com/ https://example.com/about \
+    --out site_claims
+#   review site_claims/claims_register.csv (confirm PENDING rows), then build:
+python scripts/build_schema_drafts.py site_claims/claims_register.csv --out drafts_out
+
+# MODE 2 — collected sources → register (fill templates/claims-register.csv by hand)
+python scripts/build_schema_drafts.py path/to/claims_register.csv --out drafts_out
+
+# HAND OFF TO THE GATE (must reach zero P0)
+python ../16-seo-schema-validator/scripts/validate_schema.py \
+    drafts_out/schema_drafts_dataset.csv --out qa_out
+```
+
+## Outputs
+
+- `drafts/*.jsonld` — one pruned draft per entity (× language).
+- `schema_drafts_dataset.csv` — directly consumable by `16-seo-schema-validator`.
+- `build_report.md` — entities built + **excluded claims** (PENDING / CONFLICT / EMPTY) with reasons.
+- (Mode 1 also) `claims_register.csv` + `extraction_report.md`.
+
+## Stage gates (설계→개발→테스트→안정화→런칭 후)
+
+- **G1 설계** — Lock the entity→type map (`references/entity-and-type-map.md`). Mode 2: source
+  register complete (≥2 sources/entity). *DoD:* every entity has an assigned type + required list.
+- **G2 개발** — Seed the register (Mode 1 extract / Mode 2 research), reconcile to `CONFIRMED`,
+  conflicts = 0, run the builder → drafts have **zero placeholders**.
+- **G3 테스트** — Validate (16): **zero P0**; triage P1; fact-accuracy sign-off via `templates/review-guide.md` (report-based, not raw JSON).
+- **G4 안정화** — Google Rich Results Test green on a sample; re-run shows no regression.
+- **G5 런칭 후** — live schema == drafts; GSC "Rich results" no new errors.
+
+## References & templates
+
+- Mode 1 SOP: `references/site-extraction-methodology.md`.
+- Mode 2 SOP (9 steps): `references/source-to-schema-methodology.md`.
+- Source authority ranking: `references/source-authority-hierarchy.md`.
+- Entity→type scoping: `references/entity-and-type-map.md`.
+- Registers + review guide: `templates/claims-register.csv`, `templates/source-register.csv`, `templates/review-guide.md`.
+
+## Templates included
+
+`scripts/type_templates.json` covers Organization, WebSite, Hotel, Person, JobPosting,
+VideoObject, FAQPage. Required props are aligned with the validator's rule set, so a
+fully confirmed entity passes the gate. **Add a type = add a template block (edit JSON only).**
+
+## Limits & honesty
+
+- Quality of drafts == quality of the register. Garbage-in still produces gaps — but
+  reported, never as placeholders.
+- Mode 1 inference (title/OpenGraph) is seeded as `PENDING` and will NOT ship until a
+  human confirms it; existing JSON-LD is seeded `CONFIRMED`. If a site already has good
+  JSON-LD, prefer auditing it directly with `16` Mode B.
+- Authoritative rich-result eligibility still needs Google's online test on a sample at G4.
+
+## Integration
+
+- **→ 16-seo-schema-validator**: the dataset CSV is the handoff; the gate is `zero P0`.
+- **→ seo-comprehensive-audit**: post-launch (G5) uses the validator's Mode B as audit stage 4.
+- This skill is a one-time-per-site authoring workflow, **not** an audit-pipeline stage.

custom-skills/17-seo-schema-generator/code/CLAUDE.md

@@ -1,156 +1,52 @@
-# CLAUDE.md
+# CLAUDE.md — seo-schema-generator (Claude Code)
 
-## Overview
+## Canonical entry point
 
-Schema markup generator: create JSON-LD structured data from templates for various content types.
+This skill was upgraded to a **two-mode source-to-schema pipeline** (it absorbed and
+retired the old template-fill generator). The authoritative directive and run
+instructions live in the skill root:
 
-## Quick Start
+- **`../SKILL.md`** — the two modes, the claims-register pivot, stage gates, how to run.
+- **`../scripts/extract_site_claims.py`** — Mode 1: existing site → claims register.
+- **`../scripts/build_schema_drafts.py`** — claims register → JSON-LD drafts + dataset CSV.
+- **`../scripts/type_templates.json`** — draft templates (edit JSON to add a type).
+- **`../references/`** — `site-extraction-methodology.md` (Mode 1), `source-to-schema-methodology.md` (Mode 2), `source-authority-hierarchy.md`, `entity-and-type-map.md`.
+- **`../templates/`** — `claims-register.csv`, `source-register.csv`, `review-guide.md`.
 
 ```bash
-pip install -r scripts/requirements.txt
+# Try the bundled sample first (Mode 2)
+python ../scripts/make_sample.py
+python ../scripts/build_schema_drafts.py ../fixtures/sample_claims.csv --out drafts_out
 
-# Generate Organization schema
+# Mode 1 — existing site → claims register (URLs, or local .html / a directory offline)
-python scripts/schema_generator.py --type organization --url https://example.com
+python ../scripts/extract_site_claims.py https://example.com/ --out site_claims
+python ../scripts/build_schema_drafts.py site_claims/claims_register.csv --out drafts_out
 
-# Generate from template
+# Hand off to the QA gate (must reach zero P0)
-python scripts/schema_generator.py --template templates/article.json --data article_data.json
+python ../../16-seo-schema-validator/scripts/validate_schema.py \
+    drafts_out/schema_drafts_dataset.csv --out qa_out
 ```
 
-## Scripts
+Core rule: **only CONFIRMED, non-conflicting claims become schema.** Unfilled template
+slots are pruned — never emitted as `{{…}}` or `TODO`. **Generate (17) → Validate (16).**
 
-| Script | Purpose |
+## Retired
-|--------|---------|
-| `schema_generator.py` | Generate schema markup |
-| `base_client.py` | Shared utilities |
 
-## Supported Schema Types
+The previous template-fill tool (`schema_generator.py` + per-type JSON templates) is
+superseded by the claims-register engine above and has been removed. Use
+`build_schema_drafts.py` for all generation.
 
-| Type | Template | Use Case |
+## Notion output (OurDigital SEO Audit Log)
-|------|----------|----------|
-| Organization | `organization.json` | Company/brand info |
-| LocalBusiness | `local_business.json` | Physical locations |
-| Article | `article.json` | Blog posts, news |
-| Product | `product.json` | E-commerce items |
-| FAQPage | `faq.json` | FAQ sections |
-| BreadcrumbList | `breadcrumb.json` | Navigation path |
-| WebSite | `website.json` | Site-level info |
 
-## Usage Examples
+When generation is part of an OurDigital/D.intelligence engagement, log a summary to the
-
+SEO Audit Log database. Per the user-level Notion rule, push **page content** with the
-### Organization
+`notion-writer` skill; use Notion MCP only for **properties**.
-```bash
-python scripts/schema_generator.py --type organization \
-  --name "Company Name" \
-  --url "https://example.com" \
-  --logo "https://example.com/logo.png"
-```
-
-### LocalBusiness
-```bash
-python scripts/schema_generator.py --type localbusiness \
-  --name "Restaurant Name" \
-  --address "123 Main St, City, State 12345" \
-  --phone "+1-555-123-4567" \
-  --hours "Mo-Fr 09:00-17:00"
-```
-
-### Article
-```bash
-python scripts/schema_generator.py --type article \
-  --headline "Article Title" \
-  --author "Author Name" \
-  --published "2024-01-15" \
-  --image "https://example.com/image.jpg"
-```
-
-### FAQPage
-```bash
-python scripts/schema_generator.py --type faq \
-  --questions questions.json
-```
-
-## Output
-
-Generated JSON-LD ready for insertion:
-
-```html
-<script type="application/ld+json">
-{
-  "@context": "https://schema.org",
-  "@type": "Organization",
-  "name": "Company Name",
-  "url": "https://example.com",
-  "logo": "https://example.com/logo.png"
-}
-</script>
-```
-
-## Template Customization
-
-Templates in `templates/` can be modified. Required fields are marked:
-
-```json
-{
-  "@context": "https://schema.org",
-  "@type": "Article",
-  "headline": "{{REQUIRED}}",
-  "author": {
-    "@type": "Person",
-    "name": "{{REQUIRED}}"
-  },
-  "datePublished": "{{REQUIRED}}",
-  "image": "{{RECOMMENDED}}"
-}
-```
-
-## Validation
-
-Generated schemas are validated before output:
-- Syntax correctness
-- Required properties present
-- Schema.org vocabulary compliance
-
-Use skill 13 (schema-validator) for additional validation.
-
-## Dependencies
-
-```
-jsonschema>=4.21.0
-requests>=2.31.0
-python-dotenv>=1.0.0
-```
-
-## Notion Output (Required)
-
-**IMPORTANT**: All audit reports MUST be saved to the OurDigital SEO Audit Log database.
-
-### Database Configuration
 
 | Field | Value |
 |-------|-------|
 | Database ID | `2c8581e5-8a1e-8035-880b-e38cefc2f3ef` |
-| URL | https://www.notion.so/dintelligence/2c8581e58a1e8035880be38cefc2f3ef |
+| Category | `Schema/Structured Data` |
-
+| Audit ID | `SCHEMA-YYYYMMDD-NNN` |
-### Required Properties
-
-| Property | Type | Description |
-|----------|------|-------------|
-| Issue | Title | Report title (Korean + date) |
-| Site | URL | Audited website URL |
-| Category | Select | Technical SEO, On-page SEO, Performance, Schema/Structured Data, Sitemap, Robots.txt, Content, Local SEO |
-| Priority | Select | Critical, High, Medium, Low |
-| Found Date | Date | Audit date (YYYY-MM-DD) |
-| Audit ID | Rich Text | Format: [TYPE]-YYYYMMDD-NNN |
-
-### Language Guidelines
-
-- Report content in Korean (한국어)
-- Keep technical English terms as-is (e.g., SEO Audit, Core Web Vitals, Schema Markup)
-- URLs and code remain unchanged
-
-### Example MCP Call
-
-```bash
-mcp-cli call notion/API-post-page '{"parent": {"database_id": "2c8581e5-8a1e-8035-880b-e38cefc2f3ef"}, "properties": {...}}'
-```
 
+Report content in Korean; keep technical terms (Schema, JSON-LD, claims register) and
+URLs/code unchanged.

custom-skills/17-seo-schema-generator/code/scripts/base_client.py

@@ -1,207 +0,0 @@
-"""
-Base Client - Shared async client utilities
-===========================================
-Purpose: Rate-limited async operations for API clients
-Python: 3.10+
-"""
-
-import asyncio
-import logging
-import os
-from asyncio import Semaphore
-from datetime import datetime
-from typing import Any, Callable, TypeVar
-
-from dotenv import load_dotenv
-from tenacity import (
-    retry,
-    stop_after_attempt,
-    wait_exponential,
-    retry_if_exception_type,
-)
-
-# Load environment variables
-load_dotenv()
-
-# Logging setup
-logging.basicConfig(
-    level=logging.INFO,
-    format="%(asctime)s - %(levelname)s - %(message)s",
-)
-
-T = TypeVar("T")
-
-
-class RateLimiter:
-    """Rate limiter using token bucket algorithm."""
-
-    def __init__(self, rate: float, per: float = 1.0):
-        """
-        Initialize rate limiter.
-
-        Args:
-            rate: Number of requests allowed
-            per: Time period in seconds (default: 1 second)
-        """
-        self.rate = rate
-        self.per = per
-        self.tokens = rate
-        self.last_update = datetime.now()
-        self._lock = asyncio.Lock()
-
-    async def acquire(self) -> None:
-        """Acquire a token, waiting if necessary."""
-        async with self._lock:
-            now = datetime.now()
-            elapsed = (now - self.last_update).total_seconds()
-            self.tokens = min(self.rate, self.tokens + elapsed * (self.rate / self.per))
-            self.last_update = now
-
-            if self.tokens < 1:
-                wait_time = (1 - self.tokens) * (self.per / self.rate)
-                await asyncio.sleep(wait_time)
-                self.tokens = 0
-            else:
-                self.tokens -= 1
-
-
-class BaseAsyncClient:
-    """Base class for async API clients with rate limiting."""
-
-    def __init__(
-        self,
-        max_concurrent: int = 5,
-        requests_per_second: float = 3.0,
-        logger: logging.Logger | None = None,
-    ):
-        """
-        Initialize base client.
-
-        Args:
-            max_concurrent: Maximum concurrent requests
-            requests_per_second: Rate limit
-            logger: Logger instance
-        """
-        self.semaphore = Semaphore(max_concurrent)
-        self.rate_limiter = RateLimiter(requests_per_second)
-        self.logger = logger or logging.getLogger(self.__class__.__name__)
-        self.stats = {
-            "requests": 0,
-            "success": 0,
-            "errors": 0,
-            "retries": 0,
-        }
-
-    @retry(
-        stop=stop_after_attempt(3),
-        wait=wait_exponential(multiplier=1, min=2, max=10),
-        retry=retry_if_exception_type(Exception),
-    )
-    async def _rate_limited_request(
-        self,
-        coro: Callable[[], Any],
-    ) -> Any:
-        """Execute a request with rate limiting and retry."""
-        async with self.semaphore:
-            await self.rate_limiter.acquire()
-            self.stats["requests"] += 1
-            try:
-                result = await coro()
-                self.stats["success"] += 1
-                return result
-            except Exception as e:
-                self.stats["errors"] += 1
-                self.logger.error(f"Request failed: {e}")
-                raise
-
-    async def batch_requests(
-        self,
-        requests: list[Callable[[], Any]],
-        desc: str = "Processing",
-    ) -> list[Any]:
-        """Execute multiple requests concurrently."""
-        try:
-            from tqdm.asyncio import tqdm
-            has_tqdm = True
-        except ImportError:
-            has_tqdm = False
-
-        async def execute(req: Callable) -> Any:
-            try:
-                return await self._rate_limited_request(req)
-            except Exception as e:
-                return {"error": str(e)}
-
-        tasks = [execute(req) for req in requests]
-
-        if has_tqdm:
-            results = []
-            for coro in tqdm.as_completed(tasks, total=len(tasks), desc=desc):
-                result = await coro
-                results.append(result)
-            return results
-        else:
-            return await asyncio.gather(*tasks, return_exceptions=True)
-
-    def print_stats(self) -> None:
-        """Print request statistics."""
-        self.logger.info("=" * 40)
-        self.logger.info("Request Statistics:")
-        self.logger.info(f"  Total Requests: {self.stats['requests']}")
-        self.logger.info(f"  Successful: {self.stats['success']}")
-        self.logger.info(f"  Errors: {self.stats['errors']}")
-        self.logger.info("=" * 40)
-
-
-class ConfigManager:
-    """Manage API configuration and credentials."""
-
-    def __init__(self):
-        load_dotenv()
-
-    @property
-    def google_credentials_path(self) -> str | None:
-        """Get Google service account credentials path."""
-        # Prefer SEO-specific credentials, fallback to general credentials
-        seo_creds = os.path.expanduser("~/.credential/ourdigital-seo-agent.json")
-        if os.path.exists(seo_creds):
-            return seo_creds
-        return os.getenv("GOOGLE_APPLICATION_CREDENTIALS")
-
-    @property
-    def pagespeed_api_key(self) -> str | None:
-        """Get PageSpeed Insights API key."""
-        return os.getenv("PAGESPEED_API_KEY")
-
-    @property
-    def custom_search_api_key(self) -> str | None:
-        """Get Custom Search API key."""
-        return os.getenv("CUSTOM_SEARCH_API_KEY")
-
-    @property
-    def custom_search_engine_id(self) -> str | None:
-        """Get Custom Search Engine ID."""
-        return os.getenv("CUSTOM_SEARCH_ENGINE_ID")
-
-    @property
-    def notion_token(self) -> str | None:
-        """Get Notion API token."""
-        return os.getenv("NOTION_TOKEN") or os.getenv("NOTION_API_KEY")
-
-    def validate_google_credentials(self) -> bool:
-        """Validate Google credentials are configured."""
-        creds_path = self.google_credentials_path
-        if not creds_path:
-            return False
-        return os.path.exists(creds_path)
-
-    def get_required(self, key: str) -> str:
-        """Get required environment variable or raise error."""
-        value = os.getenv(key)
-        if not value:
-            raise ValueError(f"Missing required environment variable: {key}")
-        return value
-
-
-# Singleton config instance
-config = ConfigManager()

custom-skills/17-seo-schema-generator/code/scripts/requirements.txt

@@ -1,6 +0,0 @@
-# 14-seo-schema-generator dependencies
-jsonschema>=4.21.0
-requests>=2.31.0
-python-dotenv>=1.0.0
-rich>=13.7.0
-typer>=0.9.0

custom-skills/17-seo-schema-generator/code/scripts/schema_generator.py

@@ -1,490 +0,0 @@
-"""
-Schema Generator - Generate JSON-LD structured data markup
-==========================================================
-Purpose: Generate schema.org structured data in JSON-LD format
-Python: 3.10+
-Usage:
-    python schema_generator.py --type organization --name "Company Name" --url "https://example.com"
-"""
-
-import argparse
-import json
-import logging
-import os
-import re
-from datetime import datetime
-from pathlib import Path
-from typing import Any
-
-logging.basicConfig(
-    level=logging.INFO,
-    format="%(asctime)s - %(levelname)s - %(message)s",
-)
-logger = logging.getLogger(__name__)
-
-# Template directory relative to this script
-TEMPLATE_DIR = Path(__file__).parent.parent / "templates" / "schema_templates"
-
-
-class SchemaGenerator:
-    """Generate JSON-LD schema markup from templates."""
-
-    SCHEMA_TYPES = {
-        "organization": "organization.json",
-        "local_business": "local_business.json",
-        "product": "product.json",
-        "article": "article.json",
-        "faq": "faq.json",
-        "breadcrumb": "breadcrumb.json",
-        "website": "website.json",
-    }
-
-    # Business type mappings for LocalBusiness
-    BUSINESS_TYPES = {
-        "restaurant": "Restaurant",
-        "cafe": "CafeOrCoffeeShop",
-        "bar": "BarOrPub",
-        "hotel": "Hotel",
-        "store": "Store",
-        "medical": "MedicalBusiness",
-        "dental": "Dentist",
-        "legal": "LegalService",
-        "real_estate": "RealEstateAgent",
-        "auto": "AutoRepair",
-        "beauty": "BeautySalon",
-        "gym": "HealthClub",
-        "spa": "DaySpa",
-    }
-
-    # Article type mappings
-    ARTICLE_TYPES = {
-        "article": "Article",
-        "blog": "BlogPosting",
-        "news": "NewsArticle",
-        "tech": "TechArticle",
-        "scholarly": "ScholarlyArticle",
-    }
-
-    def __init__(self, template_dir: Path = TEMPLATE_DIR):
-        self.template_dir = template_dir
-
-    def load_template(self, schema_type: str) -> dict:
-        """Load a schema template file."""
-        if schema_type not in self.SCHEMA_TYPES:
-            raise ValueError(f"Unknown schema type: {schema_type}. "
-                           f"Available: {list(self.SCHEMA_TYPES.keys())}")
-
-        template_file = self.template_dir / self.SCHEMA_TYPES[schema_type]
-        if not template_file.exists():
-            raise FileNotFoundError(f"Template not found: {template_file}")
-
-        with open(template_file, "r", encoding="utf-8") as f:
-            return json.load(f)
-
-    def fill_template(self, template: dict, data: dict[str, Any]) -> dict:
-        """Fill template placeholders with actual data."""
-        template_str = json.dumps(template, ensure_ascii=False)
-
-        # Replace placeholders {{key}} with values
-        for key, value in data.items():
-            placeholder = f"{{{{{key}}}}}"
-            if value is not None:
-                template_str = template_str.replace(placeholder, str(value))
-
-        # Remove unfilled placeholders and their parent objects if empty
-        result = json.loads(template_str)
-        return self._clean_empty_values(result)
-
-    def _clean_empty_values(self, obj: Any) -> Any:
-        """Remove empty values and unfilled placeholders."""
-        if isinstance(obj, dict):
-            cleaned = {}
-            for key, value in obj.items():
-                cleaned_value = self._clean_empty_values(value)
-                # Skip if value is empty, None, or unfilled placeholder
-                if cleaned_value is None:
-                    continue
-                if isinstance(cleaned_value, str) and cleaned_value.startswith("{{"):
-                    continue
-                if isinstance(cleaned_value, (list, dict)) and not cleaned_value:
-                    continue
-                cleaned[key] = cleaned_value
-            return cleaned if cleaned else None
-        elif isinstance(obj, list):
-            cleaned = []
-            for item in obj:
-                cleaned_item = self._clean_empty_values(item)
-                if cleaned_item is not None:
-                    if isinstance(cleaned_item, str) and cleaned_item.startswith("{{"):
-                        continue
-                    cleaned.append(cleaned_item)
-            return cleaned if cleaned else None
-        elif isinstance(obj, str):
-            if obj.startswith("{{") and obj.endswith("}}"):
-                return None
-            return obj
-        return obj
-
-    def generate_organization(
-        self,
-        name: str,
-        url: str,
-        logo_url: str | None = None,
-        description: str | None = None,
-        founding_date: str | None = None,
-        phone: str | None = None,
-        address: dict | None = None,
-        social_links: list[str] | None = None,
-    ) -> dict:
-        """Generate Organization schema."""
-        template = self.load_template("organization")
-
-        data = {
-            "name": name,
-            "url": url,
-            "logo_url": logo_url,
-            "description": description,
-            "founding_date": founding_date,
-            "phone": phone,
-        }
-
-        if address:
-            data.update({
-                "street_address": address.get("street"),
-                "city": address.get("city"),
-                "region": address.get("region"),
-                "postal_code": address.get("postal_code"),
-                "country": address.get("country", "KR"),
-            })
-
-        if social_links:
-            # Handle social links specially
-            pass
-
-        return self.fill_template(template, data)
-
-    def generate_local_business(
-        self,
-        name: str,
-        business_type: str,
-        address: dict,
-        phone: str | None = None,
-        url: str | None = None,
-        description: str | None = None,
-        hours: dict | None = None,
-        geo: dict | None = None,
-        price_range: str | None = None,
-        rating: float | None = None,
-        review_count: int | None = None,
-    ) -> dict:
-        """Generate LocalBusiness schema."""
-        template = self.load_template("local_business")
-
-        schema_business_type = self.BUSINESS_TYPES.get(
-            business_type.lower(), "LocalBusiness"
-        )
-
-        data = {
-            "business_type": schema_business_type,
-            "name": name,
-            "url": url,
-            "description": description,
-            "phone": phone,
-            "price_range": price_range,
-            "street_address": address.get("street"),
-            "city": address.get("city"),
-            "region": address.get("region"),
-            "postal_code": address.get("postal_code"),
-            "country": address.get("country", "KR"),
-        }
-
-        if geo:
-            data["latitude"] = geo.get("lat")
-            data["longitude"] = geo.get("lng")
-
-        if hours:
-            data.update({
-                "weekday_opens": hours.get("weekday_opens", "09:00"),
-                "weekday_closes": hours.get("weekday_closes", "18:00"),
-                "weekend_opens": hours.get("weekend_opens"),
-                "weekend_closes": hours.get("weekend_closes"),
-            })
-
-        if rating is not None:
-            data["rating"] = str(rating)
-            data["review_count"] = str(review_count or 0)
-
-        return self.fill_template(template, data)
-
-    def generate_product(
-        self,
-        name: str,
-        description: str,
-        price: float,
-        currency: str = "KRW",
-        brand: str | None = None,
-        sku: str | None = None,
-        images: list[str] | None = None,
-        availability: str = "InStock",
-        condition: str = "NewCondition",
-        rating: float | None = None,
-        review_count: int | None = None,
-        url: str | None = None,
-        seller: str | None = None,
-    ) -> dict:
-        """Generate Product schema."""
-        template = self.load_template("product")
-
-        data = {
-            "name": name,
-            "description": description,
-            "price": str(int(price)),
-            "currency": currency,
-            "brand_name": brand,
-            "sku": sku,
-            "product_url": url,
-            "availability": availability,
-            "condition": condition,
-            "seller_name": seller,
-        }
-
-        if images:
-            for i, img in enumerate(images[:3], 1):
-                data[f"image_url_{i}"] = img
-
-        if rating is not None:
-            data["rating"] = str(rating)
-            data["review_count"] = str(review_count or 0)
-
-        return self.fill_template(template, data)
-
-    def generate_article(
-        self,
-        headline: str,
-        description: str,
-        author_name: str,
-        date_published: str,
-        publisher_name: str,
-        article_type: str = "article",
-        date_modified: str | None = None,
-        images: list[str] | None = None,
-        page_url: str | None = None,
-        publisher_logo: str | None = None,
-        author_url: str | None = None,
-        section: str | None = None,
-        word_count: int | None = None,
-        keywords: str | None = None,
-    ) -> dict:
-        """Generate Article schema."""
-        template = self.load_template("article")
-
-        schema_article_type = self.ARTICLE_TYPES.get(
-            article_type.lower(), "Article"
-        )
-
-        data = {
-            "article_type": schema_article_type,
-            "headline": headline,
-            "description": description,
-            "author_name": author_name,
-            "author_url": author_url,
-            "date_published": date_published,
-            "date_modified": date_modified or date_published,
-            "publisher_name": publisher_name,
-            "publisher_logo_url": publisher_logo,
-            "page_url": page_url,
-            "section": section,
-            "word_count": str(word_count) if word_count else None,
-            "keywords": keywords,
-        }
-
-        if images:
-            for i, img in enumerate(images[:2], 1):
-                data[f"image_url_{i}"] = img
-
-        return self.fill_template(template, data)
-
-    def generate_faq(self, questions: list[dict[str, str]]) -> dict:
-        """Generate FAQPage schema."""
-        schema = {
-            "@context": "https://schema.org",
-            "@type": "FAQPage",
-            "mainEntity": [],
-        }
-
-        for qa in questions:
-            schema["mainEntity"].append({
-                "@type": "Question",
-                "name": qa["question"],
-                "acceptedAnswer": {
-                    "@type": "Answer",
-                    "text": qa["answer"],
-                },
-            })
-
-        return schema
-
-    def generate_breadcrumb(self, items: list[dict[str, str]]) -> dict:
-        """Generate BreadcrumbList schema."""
-        schema = {
-            "@context": "https://schema.org",
-            "@type": "BreadcrumbList",
-            "itemListElement": [],
-        }
-
-        for i, item in enumerate(items, 1):
-            schema["itemListElement"].append({
-                "@type": "ListItem",
-                "position": i,
-                "name": item["name"],
-                "item": item["url"],
-            })
-
-        return schema
-
-    def generate_website(
-        self,
-        name: str,
-        url: str,
-        search_url_template: str | None = None,
-        description: str | None = None,
-        language: str = "ko-KR",
-        publisher_name: str | None = None,
-        logo_url: str | None = None,
-        alternate_name: str | None = None,
-    ) -> dict:
-        """Generate WebSite schema."""
-        template = self.load_template("website")
-
-        data = {
-            "site_name": name,
-            "url": url,
-            "description": description,
-            "language": language,
-            "search_url_template": search_url_template,
-            "publisher_name": publisher_name or name,
-            "logo_url": logo_url,
-            "alternate_name": alternate_name,
-        }
-
-        return self.fill_template(template, data)
-
-    def to_json_ld(self, schema: dict, pretty: bool = True) -> str:
-        """Convert schema dict to JSON-LD string."""
-        indent = 2 if pretty else None
-        return json.dumps(schema, ensure_ascii=False, indent=indent)
-
-    def to_html_script(self, schema: dict) -> str:
-        """Wrap schema in HTML script tag."""
-        json_ld = self.to_json_ld(schema)
-        return f'<script type="application/ld+json">\n{json_ld}\n</script>'
-
-
-def main():
-    """Main entry point for CLI usage."""
-    parser = argparse.ArgumentParser(
-        description="Generate JSON-LD schema markup",
-        formatter_class=argparse.RawDescriptionHelpFormatter,
-        epilog="""
-Examples:
-  # Generate Organization schema
-  python schema_generator.py --type organization --name "My Company" --url "https://example.com"
-
-  # Generate Product schema
-  python schema_generator.py --type product --name "Widget" --price 29900 --currency KRW
-
-  # Generate Article schema
-  python schema_generator.py --type article --headline "Article Title" --author "John Doe"
-        """,
-    )
-
-    parser.add_argument(
-        "--type", "-t",
-        required=True,
-        choices=SchemaGenerator.SCHEMA_TYPES.keys(),
-        help="Schema type to generate",
-    )
-    parser.add_argument("--name", help="Name/title")
-    parser.add_argument("--url", help="URL")
-    parser.add_argument("--description", help="Description")
-    parser.add_argument("--price", type=float, help="Price (for product)")
-    parser.add_argument("--currency", default="KRW", help="Currency code")
-    parser.add_argument("--headline", help="Headline (for article)")
-    parser.add_argument("--author", help="Author name")
-    parser.add_argument("--output", "-o", help="Output file path")
-    parser.add_argument("--html", action="store_true", help="Output as HTML script tag")
-
-    args = parser.parse_args()
-
-    generator = SchemaGenerator()
-
-    try:
-        if args.type == "organization":
-            schema = generator.generate_organization(
-                name=args.name or "Organization Name",
-                url=args.url or "https://example.com",
-                description=args.description,
-            )
-        elif args.type == "product":
-            schema = generator.generate_product(
-                name=args.name or "Product Name",
-                description=args.description or "Product description",
-                price=args.price or 0,
-                currency=args.currency,
-            )
-        elif args.type == "article":
-            schema = generator.generate_article(
-                headline=args.headline or args.name or "Article Title",
-                description=args.description or "Article description",
-                author_name=args.author or "Author",
-                date_published=datetime.now().strftime("%Y-%m-%d"),
-                publisher_name="Publisher",
-            )
-        elif args.type == "website":
-            schema = generator.generate_website(
-                name=args.name or "Website Name",
-                url=args.url or "https://example.com",
-                description=args.description,
-            )
-        elif args.type == "faq":
-            # Example FAQ
-            schema = generator.generate_faq([
-                {"question": "Question 1?", "answer": "Answer 1"},
-                {"question": "Question 2?", "answer": "Answer 2"},
-            ])
-        elif args.type == "breadcrumb":
-            # Example breadcrumb
-            schema = generator.generate_breadcrumb([
-                {"name": "Home", "url": "https://example.com/"},
-                {"name": "Category", "url": "https://example.com/category/"},
-            ])
-        elif args.type == "local_business":
-            schema = generator.generate_local_business(
-                name=args.name or "Business Name",
-                business_type="store",
-                address={"street": "123 Main St", "city": "Seoul", "country": "KR"},
-                url=args.url,
-                description=args.description,
-            )
-        else:
-            raise ValueError(f"Unsupported type: {args.type}")
-
-        if args.html:
-            output = generator.to_html_script(schema)
-        else:
-            output = generator.to_json_ld(schema)
-
-        if args.output:
-            with open(args.output, "w", encoding="utf-8") as f:
-                f.write(output)
-            logger.info(f"Schema written to {args.output}")
-        else:
-            print(output)
-
-    except Exception as e:
-        logger.error(f"Error generating schema: {e}")
-        raise
-
-
-if __name__ == "__main__":
-    main()

custom-skills/17-seo-schema-generator/code/templates/article.json

@@ -1,32 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "{{article_type}}",
-  "headline": "{{headline}}",
-  "description": "{{description}}",
-  "image": [
-    "{{image_url_1}}",
-    "{{image_url_2}}"
-  ],
-  "datePublished": "{{date_published}}",
-  "dateModified": "{{date_modified}}",
-  "author": {
-    "@type": "Person",
-    "name": "{{author_name}}",
-    "url": "{{author_url}}"
-  },
-  "publisher": {
-    "@type": "Organization",
-    "name": "{{publisher_name}}",
-    "logo": {
-      "@type": "ImageObject",
-      "url": "{{publisher_logo_url}}"
-    }
-  },
-  "mainEntityOfPage": {
-    "@type": "WebPage",
-    "@id": "{{page_url}}"
-  },
-  "articleSection": "{{section}}",
-  "wordCount": "{{word_count}}",
-  "keywords": "{{keywords}}"
-}

custom-skills/17-seo-schema-generator/code/templates/breadcrumb.json

@@ -1,24 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "BreadcrumbList",
-  "itemListElement": [
-    {
-      "@type": "ListItem",
-      "position": 1,
-      "name": "{{level_1_name}}",
-      "item": "{{level_1_url}}"
-    },
-    {
-      "@type": "ListItem",
-      "position": 2,
-      "name": "{{level_2_name}}",
-      "item": "{{level_2_url}}"
-    },
-    {
-      "@type": "ListItem",
-      "position": 3,
-      "name": "{{level_3_name}}",
-      "item": "{{level_3_url}}"
-    }
-  ]
-}

custom-skills/17-seo-schema-generator/code/templates/faq.json

@@ -1,30 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "FAQPage",
-  "mainEntity": [
-    {
-      "@type": "Question",
-      "name": "{{question_1}}",
-      "acceptedAnswer": {
-        "@type": "Answer",
-        "text": "{{answer_1}}"
-      }
-    },
-    {
-      "@type": "Question",
-      "name": "{{question_2}}",
-      "acceptedAnswer": {
-        "@type": "Answer",
-        "text": "{{answer_2}}"
-      }
-    },
-    {
-      "@type": "Question",
-      "name": "{{question_3}}",
-      "acceptedAnswer": {
-        "@type": "Answer",
-        "text": "{{answer_3}}"
-      }
-    }
-  ]
-}

custom-skills/17-seo-schema-generator/code/templates/local_business.json

@@ -1,47 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "{{business_type}}",
-  "name": "{{name}}",
-  "description": "{{description}}",
-  "url": "{{url}}",
-  "telephone": "{{phone}}",
-  "email": "{{email}}",
-  "image": "{{image_url}}",
-  "priceRange": "{{price_range}}",
-  "address": {
-    "@type": "PostalAddress",
-    "streetAddress": "{{street_address}}",
-    "addressLocality": "{{city}}",
-    "addressRegion": "{{region}}",
-    "postalCode": "{{postal_code}}",
-    "addressCountry": "{{country}}"
-  },
-  "geo": {
-    "@type": "GeoCoordinates",
-    "latitude": "{{latitude}}",
-    "longitude": "{{longitude}}"
-  },
-  "openingHoursSpecification": [
-    {
-      "@type": "OpeningHoursSpecification",
-      "dayOfWeek": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"],
-      "opens": "{{weekday_opens}}",
-      "closes": "{{weekday_closes}}"
-    },
-    {
-      "@type": "OpeningHoursSpecification",
-      "dayOfWeek": ["Saturday", "Sunday"],
-      "opens": "{{weekend_opens}}",
-      "closes": "{{weekend_closes}}"
-    }
-  ],
-  "aggregateRating": {
-    "@type": "AggregateRating",
-    "ratingValue": "{{rating}}",
-    "reviewCount": "{{review_count}}"
-  },
-  "sameAs": [
-    "{{facebook_url}}",
-    "{{instagram_url}}"
-  ]
-}

custom-skills/17-seo-schema-generator/code/templates/organization.json

@@ -1,37 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "Organization",
-  "name": "{{name}}",
-  "url": "{{url}}",
-  "logo": "{{logo_url}}",
-  "description": "{{description}}",
-  "foundingDate": "{{founding_date}}",
-  "founders": [
-    {
-      "@type": "Person",
-      "name": "{{founder_name}}"
-    }
-  ],
-  "address": {
-    "@type": "PostalAddress",
-    "streetAddress": "{{street_address}}",
-    "addressLocality": "{{city}}",
-    "addressRegion": "{{region}}",
-    "postalCode": "{{postal_code}}",
-    "addressCountry": "{{country}}"
-  },
-  "contactPoint": [
-    {
-      "@type": "ContactPoint",
-      "telephone": "{{phone}}",
-      "contactType": "customer service",
-      "availableLanguage": ["Korean", "English"]
-    }
-  ],
-  "sameAs": [
-    "{{facebook_url}}",
-    "{{twitter_url}}",
-    "{{linkedin_url}}",
-    "{{instagram_url}}"
-  ]
-}

custom-skills/17-seo-schema-generator/code/templates/product.json

@@ -1,76 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "Product",
-  "name": "{{name}}",
-  "description": "{{description}}",
-  "image": [
-    "{{image_url_1}}",
-    "{{image_url_2}}",
-    "{{image_url_3}}"
-  ],
-  "sku": "{{sku}}",
-  "mpn": "{{mpn}}",
-  "gtin13": "{{gtin13}}",
-  "brand": {
-    "@type": "Brand",
-    "name": "{{brand_name}}"
-  },
-  "offers": {
-    "@type": "Offer",
-    "url": "{{product_url}}",
-    "price": "{{price}}",
-    "priceCurrency": "{{currency}}",
-    "priceValidUntil": "{{price_valid_until}}",
-    "availability": "https://schema.org/{{availability}}",
-    "itemCondition": "https://schema.org/{{condition}}",
-    "seller": {
-      "@type": "Organization",
-      "name": "{{seller_name}}"
-    },
-    "shippingDetails": {
-      "@type": "OfferShippingDetails",
-      "shippingRate": {
-        "@type": "MonetaryAmount",
-        "value": "{{shipping_cost}}",
-        "currency": "{{currency}}"
-      },
-      "deliveryTime": {
-        "@type": "ShippingDeliveryTime",
-        "handlingTime": {
-          "@type": "QuantitativeValue",
-          "minValue": "{{handling_min_days}}",
-          "maxValue": "{{handling_max_days}}",
-          "unitCode": "DAY"
-        },
-        "transitTime": {
-          "@type": "QuantitativeValue",
-          "minValue": "{{transit_min_days}}",
-          "maxValue": "{{transit_max_days}}",
-          "unitCode": "DAY"
-        }
-      }
-    }
-  },
-  "aggregateRating": {
-    "@type": "AggregateRating",
-    "ratingValue": "{{rating}}",
-    "reviewCount": "{{review_count}}",
-    "bestRating": "5",
-    "worstRating": "1"
-  },
-  "review": [
-    {
-      "@type": "Review",
-      "reviewRating": {
-        "@type": "Rating",
-        "ratingValue": "{{review_rating}}",
-        "bestRating": "5"
-      },
-      "author": {
-        "@type": "Person",
-        "name": "{{reviewer_name}}"
-      },
-      "reviewBody": "{{review_text}}"
-    }
-  ]
-}

custom-skills/17-seo-schema-generator/code/templates/website.json

@@ -1,25 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "WebSite",
-  "name": "{{site_name}}",
-  "alternateName": "{{alternate_name}}",
-  "url": "{{url}}",
-  "description": "{{description}}",
-  "inLanguage": "{{language}}",
-  "potentialAction": {
-    "@type": "SearchAction",
-    "target": {
-      "@type": "EntryPoint",
-      "urlTemplate": "{{search_url_template}}"
-    },
-    "query-input": "required name=search_term_string"
-  },
-  "publisher": {
-    "@type": "Organization",
-    "name": "{{publisher_name}}",
-    "logo": {
-      "@type": "ImageObject",
-      "url": "{{logo_url}}"
-    }
-  }
-}

custom-skills/17-seo-schema-generator/desktop/SKILL.md

@@ -1,155 +1,55 @@
 ---
 name: seo-schema-generator
 description: |
-  JSON-LD structured data generator from templates for various content types.
+  Generates validation-ready JSON-LD for a site via a claims register — Mode 1 from
-  Triggers: generate schema, create JSON-LD, schema markup, structured data generator.
+  an existing website, Mode 2 from collected sources for a not-yet-published site.
+  Triggers: generate schema, create JSON-LD, source-to-schema, pre-launch schema,
+  schema from site, claims register, 스키마 생성, 스키마 저작.
 ---
 
 # SEO Schema Generator
 
+> Desktop reference. The full, runnable specification (scripts, references, templates,
+> fixtures, stage gates) is the skill-root `SKILL.md` and its bundled directories — this
+> file is the Claude Desktop entry point.
+
 ## Purpose
 
-Generate JSON-LD structured data markup for various content types using templates.
+Author JSON-LD for a site whether or not its pages exist yet. Both scenarios route
+through one pivot — a **claims register** (provenance-tracked, conflict-resolved facts) —
+then generate pruned drafts that hand off to **seo-schema-validator** (generate → validate).
 
-## Core Capabilities
+## Two modes, one pipeline
 
-1. **Organization** - Company/brand information
+| | Mode 1 — existing site | Mode 2 — collected sources |
-2. **LocalBusiness** - Physical location businesses
+|---|---|---|
-3. **Article** - Blog posts and news articles
+| Source of truth | the live pages | scattered sources (DART, Wikidata, brochures) |
-4. **Product** - E-commerce products
+| Seed the register with | extract from pages | manual research |
-5. **FAQPage** - FAQ sections
+| Hard part | extraction & mapping | authority hierarchy + entity reconciliation |
-6. **BreadcrumbList** - Navigation breadcrumbs
+
-7. **WebSite** - Site-level with search action
+Everything after the claims register (build drafts → prune unfilled slots → validate)
+is identical. **Only CONFIRMED, non-conflicting claims become schema;** unfilled template
+slots are deleted, never shipped as placeholders.
+
+## MCP Tool Usage
+
+```
+mcp__firecrawl__scrape / crawl : Mode 1 — pull existing pages to extract facts
+mcp__perplexity__search        : Mode 2 — discover & cross-check authoritative sources
+```
 
 ## Workflow
 
-1. Identify content type
+1. Lock the entity→type map (scope first).
-2. Gather required information
+2. Seed the claims register (Mode 1: extract from pages · Mode 2: research → register).
-3. Generate JSON-LD from template
+3. Reconcile to CONFIRMED; clear conflicts.
-4. Validate output
+4. Build drafts from type templates (placeholders pruned).
-5. Provide implementation instructions
+5. Validate with seo-schema-validator — gate = zero P0.
+6. Fix P0, re-validate, then client review against the report (not raw JSON).
 
-## Schema Templates
+## Notes
-
-### Organization
-```json
-{
-  "@context": "https://schema.org",
-  "@type": "Organization",
-  "name": "[Company Name]",
-  "url": "[Website URL]",
-  "logo": "[Logo URL]",
-  "sameAs": [
-    "[Social Media URLs]"
-  ]
-}
-```
-
-### LocalBusiness
-```json
-{
-  "@context": "https://schema.org",
-  "@type": "LocalBusiness",
-  "name": "[Business Name]",
-  "address": {
-    "@type": "PostalAddress",
-    "streetAddress": "[Street]",
-    "addressLocality": "[City]",
-    "addressRegion": "[State]",
-    "postalCode": "[ZIP]",
-    "addressCountry": "[Country]"
-  },
-  "telephone": "[Phone]",
-  "openingHours": ["Mo-Fr 09:00-17:00"]
-}
-```
-
-### Article
-```json
-{
-  "@context": "https://schema.org",
-  "@type": "Article",
-  "headline": "[Title]",
-  "author": {
-    "@type": "Person",
-    "name": "[Author Name]"
-  },
-  "datePublished": "[YYYY-MM-DD]",
-  "dateModified": "[YYYY-MM-DD]",
-  "image": "[Image URL]",
-  "publisher": {
-    "@type": "Organization",
-    "name": "[Publisher]",
-    "logo": "[Logo URL]"
-  }
-}
-```
-
-### FAQPage
-```json
-{
-  "@context": "https://schema.org",
-  "@type": "FAQPage",
-  "mainEntity": [
-    {
-      "@type": "Question",
-      "name": "[Question]",
-      "acceptedAnswer": {
-        "@type": "Answer",
-        "text": "[Answer]"
-      }
-    }
-  ]
-}
-```
-
-### Product
-```json
-{
-  "@context": "https://schema.org",
-  "@type": "Product",
-  "name": "[Product Name]",
-  "image": "[Image URL]",
-  "description": "[Description]",
-  "offers": {
-    "@type": "Offer",
-    "price": "[Price]",
-    "priceCurrency": "[Currency]",
-    "availability": "https://schema.org/InStock"
-  }
-}
-```
-
-## Implementation
-
-Place generated JSON-LD in `<head>` section:
-
-```html
-<head>
-  <script type="application/ld+json">
-  [Generated Schema Here]
-  </script>
-</head>
-```
-
-## Validation
-
-After generating:
-1. Use schema validator skill (13) to verify
-2. Test with Google Rich Results Test
-3. Monitor in Search Console
-
-## Limitations
-
-- Templates cover common types only
-- Complex nested schemas may need manual adjustment
-- Some Rich Results require additional properties
-
-## Notion Output (Required)
-
-All audit reports MUST be saved to OurDigital SEO Audit Log:
-- **Database ID**: `2c8581e5-8a1e-8035-880b-e38cefc2f3ef`
-- **Properties**: Issue (title), Site (url), Category, Priority, Found Date, Audit ID
-- **Language**: Korean with English technical terms
-- **Audit ID Format**: [TYPE]-YYYYMMDD-NNN
 
+- Mode 1 inference (title/OpenGraph) is seeded PENDING and never auto-ships; existing
+  JSON-LD is seeded CONFIRMED. If a site already has good JSON-LD, audit it with
+  seo-schema-validator (Mode B) instead of regenerating.
+- Authoritative rich-result eligibility still needs Google's online test on a sample.

custom-skills/17-seo-schema-generator/desktop/skill.yaml

@@ -2,7 +2,9 @@
 
 name: seo-schema-generator
 description: |
-  Schema markup generator for JSON-LD structured data. Triggers: generate schema, create JSON-LD, add structured data, schema markup.
+  JSON-LD generator with two modes — from an existing website, or from collected
+  sources for a not-yet-published site — both via a claims register. Triggers:
+  generate schema, create JSON-LD, source-to-schema, schema from site, claims register.
 
 # Optional fields
 allowed-tools:

custom-skills/17-seo-schema-generator/desktop/templates/article.json

@@ -1,32 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "{{article_type}}",
-  "headline": "{{headline}}",
-  "description": "{{description}}",
-  "image": [
-    "{{image_url_1}}",
-    "{{image_url_2}}"
-  ],
-  "datePublished": "{{date_published}}",
-  "dateModified": "{{date_modified}}",
-  "author": {
-    "@type": "Person",
-    "name": "{{author_name}}",
-    "url": "{{author_url}}"
-  },
-  "publisher": {
-    "@type": "Organization",
-    "name": "{{publisher_name}}",
-    "logo": {
-      "@type": "ImageObject",
-      "url": "{{publisher_logo_url}}"
-    }
-  },
-  "mainEntityOfPage": {
-    "@type": "WebPage",
-    "@id": "{{page_url}}"
-  },
-  "articleSection": "{{section}}",
-  "wordCount": "{{word_count}}",
-  "keywords": "{{keywords}}"
-}

custom-skills/17-seo-schema-generator/desktop/templates/breadcrumb.json

@@ -1,24 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "BreadcrumbList",
-  "itemListElement": [
-    {
-      "@type": "ListItem",
-      "position": 1,
-      "name": "{{level_1_name}}",
-      "item": "{{level_1_url}}"
-    },
-    {
-      "@type": "ListItem",
-      "position": 2,
-      "name": "{{level_2_name}}",
-      "item": "{{level_2_url}}"
-    },
-    {
-      "@type": "ListItem",
-      "position": 3,
-      "name": "{{level_3_name}}",
-      "item": "{{level_3_url}}"
-    }
-  ]
-}

custom-skills/17-seo-schema-generator/desktop/templates/faq.json

@@ -1,30 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "FAQPage",
-  "mainEntity": [
-    {
-      "@type": "Question",
-      "name": "{{question_1}}",
-      "acceptedAnswer": {
-        "@type": "Answer",
-        "text": "{{answer_1}}"
-      }
-    },
-    {
-      "@type": "Question",
-      "name": "{{question_2}}",
-      "acceptedAnswer": {
-        "@type": "Answer",
-        "text": "{{answer_2}}"
-      }
-    },
-    {
-      "@type": "Question",
-      "name": "{{question_3}}",
-      "acceptedAnswer": {
-        "@type": "Answer",
-        "text": "{{answer_3}}"
-      }
-    }
-  ]
-}

custom-skills/17-seo-schema-generator/desktop/templates/local_business.json

@@ -1,47 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "{{business_type}}",
-  "name": "{{name}}",
-  "description": "{{description}}",
-  "url": "{{url}}",
-  "telephone": "{{phone}}",
-  "email": "{{email}}",
-  "image": "{{image_url}}",
-  "priceRange": "{{price_range}}",
-  "address": {
-    "@type": "PostalAddress",
-    "streetAddress": "{{street_address}}",
-    "addressLocality": "{{city}}",
-    "addressRegion": "{{region}}",
-    "postalCode": "{{postal_code}}",
-    "addressCountry": "{{country}}"
-  },
-  "geo": {
-    "@type": "GeoCoordinates",
-    "latitude": "{{latitude}}",
-    "longitude": "{{longitude}}"
-  },
-  "openingHoursSpecification": [
-    {
-      "@type": "OpeningHoursSpecification",
-      "dayOfWeek": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"],
-      "opens": "{{weekday_opens}}",
-      "closes": "{{weekday_closes}}"
-    },
-    {
-      "@type": "OpeningHoursSpecification",
-      "dayOfWeek": ["Saturday", "Sunday"],
-      "opens": "{{weekend_opens}}",
-      "closes": "{{weekend_closes}}"
-    }
-  ],
-  "aggregateRating": {
-    "@type": "AggregateRating",
-    "ratingValue": "{{rating}}",
-    "reviewCount": "{{review_count}}"
-  },
-  "sameAs": [
-    "{{facebook_url}}",
-    "{{instagram_url}}"
-  ]
-}

custom-skills/17-seo-schema-generator/desktop/templates/organization.json

@@ -1,37 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "Organization",
-  "name": "{{name}}",
-  "url": "{{url}}",
-  "logo": "{{logo_url}}",
-  "description": "{{description}}",
-  "foundingDate": "{{founding_date}}",
-  "founders": [
-    {
-      "@type": "Person",
-      "name": "{{founder_name}}"
-    }
-  ],
-  "address": {
-    "@type": "PostalAddress",
-    "streetAddress": "{{street_address}}",
-    "addressLocality": "{{city}}",
-    "addressRegion": "{{region}}",
-    "postalCode": "{{postal_code}}",
-    "addressCountry": "{{country}}"
-  },
-  "contactPoint": [
-    {
-      "@type": "ContactPoint",
-      "telephone": "{{phone}}",
-      "contactType": "customer service",
-      "availableLanguage": ["Korean", "English"]
-    }
-  ],
-  "sameAs": [
-    "{{facebook_url}}",
-    "{{twitter_url}}",
-    "{{linkedin_url}}",
-    "{{instagram_url}}"
-  ]
-}

custom-skills/17-seo-schema-generator/desktop/templates/product.json

@@ -1,76 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "Product",
-  "name": "{{name}}",
-  "description": "{{description}}",
-  "image": [
-    "{{image_url_1}}",
-    "{{image_url_2}}",
-    "{{image_url_3}}"
-  ],
-  "sku": "{{sku}}",
-  "mpn": "{{mpn}}",
-  "gtin13": "{{gtin13}}",
-  "brand": {
-    "@type": "Brand",
-    "name": "{{brand_name}}"
-  },
-  "offers": {
-    "@type": "Offer",
-    "url": "{{product_url}}",
-    "price": "{{price}}",
-    "priceCurrency": "{{currency}}",
-    "priceValidUntil": "{{price_valid_until}}",
-    "availability": "https://schema.org/{{availability}}",
-    "itemCondition": "https://schema.org/{{condition}}",
-    "seller": {
-      "@type": "Organization",
-      "name": "{{seller_name}}"
-    },
-    "shippingDetails": {
-      "@type": "OfferShippingDetails",
-      "shippingRate": {
-        "@type": "MonetaryAmount",
-        "value": "{{shipping_cost}}",
-        "currency": "{{currency}}"
-      },
-      "deliveryTime": {
-        "@type": "ShippingDeliveryTime",
-        "handlingTime": {
-          "@type": "QuantitativeValue",
-          "minValue": "{{handling_min_days}}",
-          "maxValue": "{{handling_max_days}}",
-          "unitCode": "DAY"
-        },
-        "transitTime": {
-          "@type": "QuantitativeValue",
-          "minValue": "{{transit_min_days}}",
-          "maxValue": "{{transit_max_days}}",
-          "unitCode": "DAY"
-        }
-      }
-    }
-  },
-  "aggregateRating": {
-    "@type": "AggregateRating",
-    "ratingValue": "{{rating}}",
-    "reviewCount": "{{review_count}}",
-    "bestRating": "5",
-    "worstRating": "1"
-  },
-  "review": [
-    {
-      "@type": "Review",
-      "reviewRating": {
-        "@type": "Rating",
-        "ratingValue": "{{review_rating}}",
-        "bestRating": "5"
-      },
-      "author": {
-        "@type": "Person",
-        "name": "{{reviewer_name}}"
-      },
-      "reviewBody": "{{review_text}}"
-    }
-  ]
-}

custom-skills/17-seo-schema-generator/desktop/templates/website.json

@@ -1,25 +0,0 @@
-{
-  "@context": "https://schema.org",
-  "@type": "WebSite",
-  "name": "{{site_name}}",
-  "alternateName": "{{alternate_name}}",
-  "url": "{{url}}",
-  "description": "{{description}}",
-  "inLanguage": "{{language}}",
-  "potentialAction": {
-    "@type": "SearchAction",
-    "target": {
-      "@type": "EntryPoint",
-      "urlTemplate": "{{search_url_template}}"
-    },
-    "query-input": "required name=search_term_string"
-  },
-  "publisher": {
-    "@type": "Organization",
-    "name": "{{publisher_name}}",
-    "logo": {
-      "@type": "ImageObject",
-      "url": "{{logo_url}}"
-    }
-  }
-}

custom-skills/17-seo-schema-generator/fixtures/sample_claims.csv

@@ -0,0 +1,47 @@
+entity_id,entity_type,property,value,lang,url,source_ids,authority,confidence,conflict,status,note
+org:shilla,Organization,@id,https://www.shillahotels.com/#org,,,,1,high,,CONFIRMED,
+org:shilla,Organization,name,The Shilla Hotels & Resorts,,,S-OFF|S-WIKI,1,high,,CONFIRMED,
+org:shilla,Organization,legalName,주식회사 호텔신라,,,S-DART,1,high,,CONFIRMED,DART 법인명
+org:shilla,Organization,url,https://www.shillahotels.com/,,,S-OFF,1,high,,CONFIRMED,
+org:shilla,Organization,foundingDate,1973-05-09,,,S-DART,1,high,,CONFIRMED,
+org:shilla,Organization,sameAs,https://www.wikidata.org/wiki/Q494845|https://en.wikipedia.org/wiki/The_Shilla,,,S-WIKI|S-WD,2,high,,CONFIRMED,array via pipe
+org:shilla,Organization,address.streetAddress,동호로 249,,,S-DART,1,high,,CONFIRMED,
+org:shilla,Organization,address.addressLocality,중구,,,S-DART,1,high,,CONFIRMED,
+org:shilla,Organization,address.addressRegion,서울,,,S-DART,1,high,,CONFIRMED,
+org:shilla,Organization,address.addressCountry,KR,,,S-DART,1,high,,CONFIRMED,
+site:ko,WebSite,@id,https://www.shillahotels.com/ko#website,ko,https://www.shillahotels.com/ko/,S-OFF,1,high,,CONFIRMED,
+site:ko,WebSite,name,신라호텔,ko,,S-OFF,1,high,,CONFIRMED,
+site:ko,WebSite,url,https://www.shillahotels.com/ko/,ko,,S-OFF,1,high,,CONFIRMED,
+site:ko,WebSite,inLanguage,ko,ko,,S-OFF,1,high,,CONFIRMED,
+site:ko,WebSite,publisher.@id,https://www.shillahotels.com/#org,ko,,,1,high,,CONFIRMED,ref to org
+hotel:theshilla-seoul,Hotel,@id,https://www.shillahotels.com/ko/theshilla/seoul#hotel,ko,https://www.shillahotels.com/ko/theshilla/seoul/index.do,S-OFF|S-BROCH,1,high,,CONFIRMED,
+hotel:theshilla-seoul,Hotel,name,The Shilla Seoul,ko,,S-OFF,1,high,,CONFIRMED,
+hotel:theshilla-seoul,Hotel,telephone,+82-2-2233-3131,ko,,S-OFF|S-GBP,1,high,,CONFIRMED,
+hotel:theshilla-seoul,Hotel,priceRange,$$$$,ko,,S-OFF,2,med,,CONFIRMED,
+hotel:theshilla-seoul,Hotel,brand.name,The Shilla,ko,,S-OFF,1,high,,CONFIRMED,
+hotel:theshilla-seoul,Hotel,parentOrganization.@id,https://www.shillahotels.com/#org,ko,,,1,high,,CONFIRMED,entity graph link
+hotel:theshilla-seoul,Hotel,address.streetAddress,동호로 249,ko,,S-OFF|S-GBP,1,high,,CONFIRMED,
+hotel:theshilla-seoul,Hotel,address.addressLocality,서울,ko,,S-OFF,1,high,,CONFIRMED,
+hotel:theshilla-seoul,Hotel,address.addressCountry,KR,ko,,S-OFF,1,high,,CONFIRMED,
+hotel:theshilla-seoul,Hotel,geo.latitude,37.5564,ko,,S-GBP,1,high,,CONFIRMED,
+hotel:theshilla-seoul,Hotel,geo.longitude,127.0058,ko,,S-GBP,1,high,,CONFIRMED,
+person:ceo,Person,@id,https://www.shillahotels.com/#ceo,,,S-DART|S-NEWS,1,high,,CONFIRMED,
+person:ceo,Person,name,이부진,,,S-DART,1,high,,CONFIRMED,
+person:ceo,Person,jobTitle,대표이사 사장,,,S-DART,1,high,,CONFIRMED,
+person:ceo,Person,worksFor.@id,https://www.shillahotels.com/#org,,,,1,high,,CONFIRMED,
+job:fo-manager,JobPosting,title,프런트오피스 매니저,ko,https://recruit.shilla.net/job/1234,S-RECRUIT,1,high,,CONFIRMED,
+job:fo-manager,JobPosting,description,더 신라 서울 프런트오피스 운영 총괄 및 VIP 응대.,ko,,S-RECRUIT,1,high,,CONFIRMED,
+job:fo-manager,JobPosting,datePosted,2026-05-01,ko,,S-RECRUIT,1,high,,CONFIRMED,
+job:fo-manager,JobPosting,employmentType,FULL_TIME,ko,,S-RECRUIT,1,high,,CONFIRMED,
+job:fo-manager,JobPosting,hiringOrganization.@id,https://www.shillahotels.com/#org,ko,,,1,high,,CONFIRMED,
+job:fo-manager,JobPosting,jobLocation.addressLocality,서울,ko,,S-RECRUIT,1,high,,CONFIRMED,
+job:fo-manager,JobPosting,jobLocation.addressCountry,KR,ko,,S-RECRUIT,1,high,,CONFIRMED,
+video:brand-film,VideoObject,name,The Shilla — Authentic Indulgence,,https://www.youtube.com/watch?v=XXXX,S-YT,1,high,,CONFIRMED,
+video:brand-film,VideoObject,description,더 신라 브랜드 필름.,,,S-YT,1,high,,CONFIRMED,
+video:brand-film,VideoObject,thumbnailUrl,https://i.ytimg.com/vi/XXXX/maxresdefault.jpg,,,S-YT,1,high,,CONFIRMED,
+video:brand-film,VideoObject,uploadDate,2025-11-20,,,S-YT,1,high,,CONFIRMED,
+video:brand-film,VideoObject,duration,PT1M45S,,,S-YT,1,high,,CONFIRMED,
+video:brand-film,VideoObject,publisher.@id,https://www.shillahotels.com/#org,,,,1,high,,CONFIRMED,
+hotel:theshilla-seoul,Hotel,image,https://example.com/seoul.jpg,ko,,S-OFF,3,low,,PENDING,이미지 최종본 미확정
+org:shilla,Organization,telephone,+82-2-2233-3131,,,S-OFF,2,med,Y,CONFIRMED,대표번호 vs IR번호 출처 충돌
+person:ceo,Person,image,,,,,,,,CONFIRMED,값 공란 -> 제외

custom-skills/17-seo-schema-generator/fixtures/site/grand.html

@@ -0,0 +1,14 @@
+<!DOCTYPE html>
+<html lang="ko">
+<head>
+  <!-- No JSON-LD here → only meta/OG, seeded as PENDING (must be confirmed) -->
+  <title>그랜드 조선 부산 — 객실 및 예약</title>
+  <meta name="description" content="해운대 해변에 위치한 럭셔리 호텔, 그랜드 조선 부산.">
+  <meta property="og:type" content="business.business">
+  <meta property="og:title" content="그랜드 조선 부산">
+  <meta property="og:url" content="https://www.josunhotel.com/grand-busan">
+  <meta property="og:image" content="https://www.josunhotel.com/grand-busan.jpg">
+  <link rel="canonical" href="https://www.josunhotel.com/grand-busan">
+</head>
+<body><h1>그랜드 조선 부산</h1></body>
+</html>

custom-skills/17-seo-schema-generator/fixtures/site/index.html

@@ -0,0 +1,45 @@
+<!DOCTYPE html>
+<html lang="ko">
+<head>
+  <title>조선호텔앤리조트 — 공식 홈페이지</title>
+  <meta property="og:site_name" content="조선호텔앤리조트">
+  <meta property="og:type" content="website">
+  <meta property="og:url" content="https://www.josunhotel.com/">
+  <link rel="canonical" href="https://www.josunhotel.com/">
+  <!-- Existing JSON-LD on the live page → extracted as CONFIRMED claims -->
+  <script type="application/ld+json">
+  {
+    "@context": "https://schema.org",
+    "@graph": [
+      {
+        "@type": "Organization",
+        "@id": "https://www.josunhotel.com/#org",
+        "name": "조선호텔앤리조트",
+        "url": "https://www.josunhotel.com/",
+        "logo": "https://www.josunhotel.com/logo.png",
+        "sameAs": [
+          "https://www.instagram.com/josunhotelsandresorts/",
+          "https://www.wikidata.org/wiki/Q567458"
+        ]
+      },
+      {
+        "@type": "Hotel",
+        "@id": "https://www.josunhotel.com/westin#hotel",
+        "name": "웨스틴 조선 서울",
+        "url": "https://www.josunhotel.com/westin",
+        "telephone": "+82-2-771-0500",
+        "priceRange": "$$$$",
+        "address": {
+          "@type": "PostalAddress",
+          "streetAddress": "소공로 106",
+          "addressLocality": "서울",
+          "addressRegion": "중구",
+          "addressCountry": "KR"
+        }
+      }
+    ]
+  }
+  </script>
+</head>
+<body><h1>조선호텔앤리조트</h1></body>
+</html>

custom-skills/17-seo-schema-generator/references/entity-and-type-map.md

@@ -0,0 +1,59 @@
+# Entity → Schema Type Map (source-to-schema, pre-launch)
+
+Maps the source/entity kinds collected in steps 1–2 to schema.org types, and lists the
+Google rich-result requirements each type must satisfy. Required/recommended columns are
+kept in sync with `16-seo-schema-validator/scripts/schema_rules.json` so drafts pass the gate.
+
+## Type map
+
+| Source / entity | Type | Google required | Key recommended | Cardinality |
+|-----------------|------|-----------------|-----------------|-------------|
+| Corporate/legal (DART, official About) | `Organization` | `name`, `url` | `logo`, `sameAs`, `address`, `contactPoint` | 1 per legal entity |
+| Per-language site | `WebSite` | `name`, `url` | `inLanguage`, `publisher` | 1 per language |
+| Hotel property | `Hotel` | `name`, `address` | `telephone`, `priceRange`, `geo`, `image`, `brand` | 1 per property × language |
+| Executive / person | `Person` | `name` | `jobTitle`, `worksFor`, `sameAs`, `url` | 1 per person |
+| Recruitment posting | `JobPosting` | `title`, `description`, `datePosted`, `hiringOrganization`, `jobLocation` | `validThrough`, `employmentType`, `baseSalary` | 1 per open role |
+| Official video | `VideoObject` | `name`, `description`, `thumbnailUrl`, `uploadDate` | `duration`, `contentUrl`, `embedUrl` | 1 per featured video |
+| FAQ / press-kit Q&A | `FAQPage` | `mainEntity` (Question→Answer) | `inLanguage`, `url` | 1 per FAQ page |
+| Site navigation | `BreadcrumbList` | `itemListElement` | — | 1 per page |
+
+Note: `JobPosting` and `VideoObject` were added to the validator rule set for this workflow,
+since recruitment sites and the official YouTube channel are listed source types.
+
+## Address requirement nuance (avoid false P0)
+
+`PostalAddress` requires only `addressLocality` + `addressCountry` as the context-safe minimum.
+`streetAddress` is **recommended** (P2), because it is expected for `Hotel`/`LocalBusiness` NAP
+but NOT required by Google for `JobPosting.jobLocation` (city/region/country suffices). For
+hotels, the L4 NAP-consistency check still enforces a complete, identical street address across
+all pages of a property — so the street address signal is not lost where it matters.
+
+## Brand-tier rule (Shilla)
+
+- The Shilla, Shilla Monogram → `Hotel`
+- Shilla Stay → `Hotel` (preferred; it is lodging, not a generic LocalBusiness)
+- Always set `brand.name` (e.g. "The Shilla", "Shilla Monogram", "Shilla Stay") and link
+  `parentOrganization.@id` back to the single `Organization` node.
+
+## @id entity graph (critical for pre-launch coherence)
+
+Author stable `@id` URIs and cross-reference them so search engines read the portfolio as one
+connected entity graph rather than disconnected snippets:
+
+```
+Organization  @id = https://www.shillahotels.com/#org
+   ▲ parentOrganization        ▲ publisher          ▲ hiringOrganization   ▲ worksFor / publisher
+   │                           │                     │                      │
+Hotel (per property)      WebSite (per lang)     JobPosting             Person / VideoObject
+```
+
+Rules
+- One `Organization` node, one `@id`, referenced by every other node via `@id`.
+- `@id` must be an absolute, stable URI (the provisional production URL + a `#fragment`).
+- Every `@id` referenced must also be defined somewhere in the dataset (the validator's L4
+  checks for dangling `@id` references).
+
+## When NOT to author schema
+- Authenticated/transactional pages (mypage, login, booking cart) → no schema.
+- Thin or duplicate pages → no schema until content exists.
+- Any entity whose facts are still `conflict`/`PENDING` → resolve first (builder excludes them).

custom-skills/17-seo-schema-generator/references/site-extraction-methodology.md

@@ -0,0 +1,76 @@
+# Site-Extraction Methodology (Mode 1 — from an existing website)
+
+How to turn an existing site into a claims register, and why this mode is *easier*
+than Mode 2 (collected sources) but still must not blindly trust what it scrapes.
+
+Pair skill: extraction is `scripts/extract_site_claims.py`; the build engine and the
+QA gate are shared with Mode 2. See `source-to-schema-methodology.md` for Mode 2.
+
+## Why a website is the easy case (and where it still bites)
+
+A published site has a **single source of truth** — the pages themselves — so there is
+little to reconcile. The risks are different from Mode 2:
+
+| Risk on an existing site | What it causes | Countermeasure |
+|---|---|---|
+| Trusting inferred meta as fact | wrong/old values shipped as schema | meta/OG seeded **PENDING**, never auto-shipped |
+| Existing JSON-LD is partial or stale | gaps, outdated facts | extracted as CONFIRMED but **spot-checked** at review |
+| Many near-identical pages | duplicate descriptions, bloated register | one entity per real thing; let Layer 4 catch dupes |
+| JS-rendered schema not in raw HTML | "nothing extracted" | use a rendered snapshot / live fetch, or fall to Mode 2 |
+
+## The 5 steps
+
+### 1. Choose the pages
+Pick the canonical page per entity (home, about/company, each property/location, key
+product/FAQ pages). One representative page per entity is enough to seed it; you don't
+need the whole crawl.
+
+### 2. Extract
+Run the adapter on URLs, local `.html` files, or a directory (offline):
+```bash
+python scripts/extract_site_claims.py https://site/ https://site/about --out site_claims
+python scripts/extract_site_claims.py ./snapshot/ --out site_claims   # offline
+```
+It produces two tiers of claims:
+- **Existing JSON-LD → `CONFIRMED` (authority 1).** The site already published these
+  facts about itself; flattened to dotted-path claims.
+- **`<title>` / meta description / OpenGraph / `<html lang>` / canonical → `PENDING`
+  (authority 2).** Inferred, not authoritative. These will **not** ship until confirmed.
+
+### 3. Review the register (the critical human step)
+Open `site_claims/claims_register.csv`:
+- **Spot-check CONFIRMED rows** — extraction is faithful, but the site's own JSON-LD can
+  be wrong/stale. Correct values; clear nothing silently.
+- **Confirm or drop PENDING rows** — set `status=CONFIRMED` only for facts you've verified;
+  delete the rest. PENDING rows are excluded by the builder by design.
+- **Add what the page didn't expose** — telephone, full address, `geo`, `sameAs`,
+  `priceRange`. The richest schema usually needs facts no single page renders.
+- Set `conflict=Y` on any value you're unsure about to keep it out until resolved.
+
+### 4. Build
+```bash
+python scripts/build_schema_drafts.py site_claims/claims_register.csv --out drafts_out
+```
+Unfilled slots are pruned; only CONFIRMED, non-conflicting claims become schema. Read
+`drafts_out/build_report.md` for everything excluded and why.
+
+### 5. Validate (the gate)
+```bash
+python ../16-seo-schema-validator/scripts/validate_schema.py \
+    drafts_out/schema_drafts_dataset.csv --out qa_out
+```
+Gate = **zero P0**. Fix P0, re-build, re-validate, then open client review against the
+report (not raw JSON).
+
+## When NOT to use Mode 1
+
+If the existing site **already has good, complete JSON-LD**, you don't need to regenerate
+it — **audit it in place** with `16-seo-schema-validator` Mode B
+(`validate_schema.py --live <URL>`). Mode 1 is for sites whose pages carry the *facts* but
+not yet the *structured data*, or whose schema needs a rebuild.
+
+## entity_id convention
+
+The adapter assigns `prefix:slug` ids (`org:`, `site:`, `hotel:`, `dining:`, `page:`, …)
+derived from each node's `@id` fragment or page URL. Rename them to stable, human ids
+during review (e.g. `hotel:theshilla-seoul`) so re-runs and Mode 2 additions line up.

custom-skills/17-seo-schema-generator/references/source-authority-hierarchy.md

@@ -0,0 +1,62 @@
+# 출처 권위 위계 · 출처추적(Provenance) · 충돌 해소
+
+미발행 사이트 스키마 저작의 성패는 "사실을 스키마로 굳히기 전에 단일 확정값을 만들 수 있는가"에 달려 있다. 그 판단 규칙을 명문화한다.
+
+## 1. 출처 권위 위계 (authority rank)
+
+값이 충돌할 때 **상위 권위 출처가 이긴다.** 클레임 레지스터의 `authority` 열에 1~5로 기록한다.
+
+| 순위 | 출처 유형 | 신뢰 대상(어떤 사실에 권위) |
+|:---:|-----------|------------------------------|
+| **1** | 기업공시(DART), 사업자등록 정보 | 법인명·설립일·본사주소·대표자 (법적 사실) |
+| **1** | 공식 홈페이지/IR, 프레스킷 | 브랜드 표기·연락처·URL·로고 (공식 표기) |
+| **2** | 지속가능경영보고서, 사보, 공식 발간물 | 서사·정책·시설 스펙 |
+| **2** | Wikidata, 위키백과 | 엔티티 식별자(Q-ID)·sameAs·국제 표기 |
+| **3** | 주요 미디어 기사 | 사건·인용·맥락 (교차검증용) |
+| **4** | 인물정보/집계 사이트, 소셜 | 보조·후보값 (단독 근거 불가) |
+
+규칙
+- **법적 사실**(법인명/설립일/주소)은 순위 1(공시) 우선.
+- **공식 표기**(브랜드명/전화/URL)는 순위 1(공식 채널) 우선.
+- **국제 식별/연결**(sameAs, 외국어 표기)은 Wikidata 우선.
+- 순위 4 단독으로는 CONFIRMED 불가 → 상위 출처로 교차검증 필수.
+
+## 2. 출처추적(provenance)을 남기는 이유
+
+발행된 페이지 기반 작업은 "그 페이지가 근거"라는 자명한 출처가 있다. 미발행 작업은 그렇지 않으므로 **모든 클레임에 출처를 명시**해야 한다.
+
+- `source_ids` — 소스 레지스터의 출처 ID(파이프로 복수). 예: `S-DART|S-OFF`
+- 효용:
+  1. 충돌 시 권위 비교의 근거가 된다.
+  2. 럭셔리 브랜드 특성상 **사실 오류는 PR/법적 리스크** — 근거 추적이 방어선.
+  3. 런칭 후 사실 변경 시 어느 클레임을 갱신할지 즉시 특정 가능.
+
+## 3. 충돌 해소 절차
+
+```
+값 충돌 발견
+   │
+   ├─ 권위 순위가 다른가?  ──예──▶ 상위 출처 채택, 하위는 note에 기록, status=CONFIRMED
+   │
+   └─ 동순위 충돌인가?
+          ├─ 최신성(retrieved_date) 우선 적용 가능? ──예──▶ 최신 채택
+          └─ 판단 불가 ──▶ conflict=Y 유지, status=PENDING
+                          → 빌더가 자동 제외하고 build_report에 보고
+                          → 고객/이해관계자 질의로 확정 (최소 단위 질문)
+```
+
+원칙: **충돌이 미해소면 스키마에 넣지 않는다.** 모순된 사실로 만든 스키마는 NAP 불일치·KG 혼선으로 직결된다. 비우는 편이 틀리는 것보다 낫다.
+
+## 4. 엔티티 정합(reconciliation) — 동명 함정
+
+- 모든 핵심 엔티티는 **Wikidata Q-ID**로 못박는다(예: 호텔 법인 vs 동명 역사·지명).
+- `sameAs`에는 검증된 식별 URL만: Wikidata, 위키백과, 공식 소셜.
+- 미디어 기사 URL은 sameAs가 아님(엔티티 식별자가 아니라 언급).
+- Knowledge Panel이 이미 있으면 그 표기를 공식 표기와 대조해 일치시킨다.
+
+## 5. CONFIRMED 승격 체크리스트
+- [ ] 값이 정규화됨(전화 E.164 / 날짜 ISO 8601 / 언어 BCP-47 / 국가 ISO alpha-2)
+- [ ] `source_ids` 1개 이상, 핵심 사실은 권위 순위 1~2
+- [ ] 동일 속성 충돌 없음(`conflict` 비어 있음)
+- [ ] 엔티티는 `sameAs`/Q-ID로 식별 정합 완료
+- 위 충족 시에만 `status=CONFIRMED` → 빌더가 스키마로 채택.

custom-skills/17-seo-schema-generator/references/source-to-schema-methodology.md

@@ -0,0 +1,167 @@
+# Source-to-Schema 표준 프로세스 (미발행 사이트용 Schema 저작)
+
+> 대상: 아직 발행되지 않은 웹사이트의 구조화 데이터(JSON-LD)를 **텍스트 소스로부터 저작**하는 작업.
+> 짝 스킬: 생성/저작은 `17-seo-schema-generator`(본 문서 = Mode 2 소스 기반), 검증은 `16-seo-schema-validator`.
+
+---
+
+## 0. 왜 이 작업이 "발행된 페이지 기반"보다 어려운가
+
+발행된 페이지 기반 스키마는 **DOM이라는 단일 진실원본(single source of truth)** 이 이미 있고, 거기서 *추출*만 하면 된다. 미발행 사이트는 그 진실원본이 존재하지 않기 때문에 다음 네 가지 난점이 동시에 발생한다.
+
+| # | 난점 | 결과적으로 생기는 결함 | 대응 원칙 |
+|---|------|----------------------|-----------|
+| 1 | 사실이 여러 출처에 흩어져 있고 서로 **충돌** (DART vs 위키 vs 브로셔) | NAP 불일치, 값 모순 | **출처 권위 위계**로 단일 값 확정 |
+| 2 | 붙일 **URL이 아직 없음** | placeholder/TODO 누출 (최다 P0) | 확정값 없으면 **키 자체를 생성하지 않음** |
+| 3 | 엔티티 식별을 **사람이 수동**으로 (어느 "신라"인가) | 잘못된 sameAs, 엔티티 혼선 | **Wikidata/Wikipedia 정합(reconciliation)** |
+| 4 | 무엇을 만들지 **범위 자체가 미정** | 누락/과잉 엔티티 | **엔티티-타입 맵**으로 범위 선확정 |
+
+**결론적 설계 원칙**: 스키마로 굳히기 *전에* "출처 → 클레임(claim) 확정"을 먼저 끝낸다. 정제되지 않은 사실을 곧장 JSON-LD에 부으면 모든 충돌·공백이 그대로 스키마 결함이 된다. 그래서 본 프로세스의 중심축은 **클레임 레지스터(claims register)** — 출처가 추적되고 충돌이 해소된 사실 대장 — 이며, **CONFIRMED 클레임만 스키마가 된다.**
+
+---
+
+## 9단계 표준 프로세스
+
+각 단계는 목적 / 입력 / 절차 / 산출 / 완료기준(AC) / 리스크로 명세한다.
+
+### 1단계. 온라인 정통 소스(authentic source) 수집
+- **목적**: 권위 있는 1차 출처를 폭넓게 확보한다.
+- **입력**: 대상 기업/브랜드명, 법인명, 도메인.
+- **절차**: 다음을 수집·기록 → `templates/source-register.csv`
+  - 기업공시(**DART**) — 법인명/설립일/주소/대표자 (법적 사실의 최상위 권위)
+  - **공식 홈페이지**(About/푸터/IR), 지속가능경영보고서, 뉴스룸/미디어, 뉴스레터
+  - **Wikidata / 위키백과** — 엔티티 식별자(Q-ID)와 sameAs 후보
+  - 채용 사이트 — JobPosting 원천
+  - 공식 **YouTube 채널** — VideoObject 원천
+  - 공식 소셜/디지털 채널 — sameAs 후보
+  - 주요 미디어 기사, 인물정보 사이트 — 보조/교차검증용
+- **산출**: 소스 레지스터(출처별 1행, 권위순위·언어·커버 엔티티 기록).
+- **AC**: 각 핵심 엔티티에 대해 **최소 2개 독립 출처** 확보(교차검증 가능).
+- **리스크**: 비공식·오래된 출처를 1차로 오인 → 권위순위를 반드시 명시.
+
+### 2단계. 오프라인 콘텐츠 수집
+- **목적**: 온라인에 없는 1차 사실(브랜드 서사, 시설 스펙, 공식 표기) 확보.
+- **입력**: 브로셔 PDF, 사보/경영보고서, 프레스 킷, 보도자료 모음, 발간물.
+- **절차**: 파일을 소스 레지스터에 등록(파일 경로·발행일·언어). PDF는 텍스트 추출(스캔본은 OCR) 후 출처 표기 유지.
+- **산출**: 오프라인 출처도 동일 레지스터에 통합.
+- **AC**: 모든 오프라인 소스에 `retrieved_date`와 `authority` 기재.
+- **리스크**: PDF 추출 시 인코딩 깨짐/표 붕괴 → 추출 직후 육안 점검.
+
+### 3단계. 정규화 & 정제(distill)
+- **목적**: 수집물을 **클레임 단위**로 분해하고 노이즈·중복·빈값을 제거한다.
+- **입력**: 1·2단계 소스.
+- **절차**:
+  1. 각 소스에서 사실을 (엔티티, 속성, 값, 출처) 단위로 추출 → `templates/claims-register.csv`
+  2. 동일 (엔티티, 속성)의 **중복 통합**, 빈값/노이즈 제거
+  3. 출처 충돌 시 `conflict=Y`로 표시(해소 전까지 스키마 진입 차단)
+  4. 표기 정규화: 전화(E.164), 날짜(ISO 8601), 언어코드(BCP-47), 국가(ISO 3166-1 alpha-2)
+- **산출**: 1차 클레임 레지스터(아직 미확정 포함).
+- **AC**: 모든 핵심 속성이 단일 정규화 값 후보를 가짐(또는 conflict/pending로 명시).
+- **리스크**: 정규화 누락이 다운스트림 VAL 결함으로 직결 → 3단계에서 포맷 확정.
+
+### 4단계. 텍스트 분석 & Knowledge Graph 교차검증
+- **목적**: 클레임을 외부 KG와 대조해 **이중 점검**하고, 동시에 현황·개선과제를 도출한다.
+- **입력**: 1차 클레임 레지스터.
+- **절차**:
+  1. **엔티티 정합**: Wikidata Q-ID, 위키백과, Google Knowledge Panel과 대조 → `sameAs` 확정
+  2. 핵심 사실(설립일, 법인명, 대표자)을 KG 값과 비교 → 불일치는 `conflict`
+  3. KG에 **존재하지 않거나 빈약한 엔티티**를 식별 → *개선과제 자료*로 별도 기록(런칭 후 KG 강화 목표)
+  4. 충돌·미확정을 권위 위계로 해소 → `status=CONFIRMED` 승격
+- **산출**: 확정 클레임 레지스터 + **KG 현황/개선과제 메모**(별도 컨설팅 산출물로 활용).
+- **AC**: 모든 핵심 엔티티에 검증된 `sameAs` 1개 이상; conflict 0건.
+- **리스크**: 동명 엔티티 오정합(예: "신라" 왕조 vs 호텔) → Q-ID로 못박기.
+- 참고: `references/source-authority-hierarchy.md`
+
+### 5단계. 유형별 활용 스키마 타입 분류
+- **목적**: 어떤 엔티티에 어떤 schema.org 타입을 쓸지 범위를 확정한다.
+- **입력**: 확정 클레임 + 페이지/엔티티 목록.
+- **절차**: 엔티티·소스 유형을 타입에 매핑(아래는 본 스킬 기본 매핑).
+
+  | 소스/엔티티 | schema.org 타입 |
+  |-------------|-----------------|
+  | 법인·브랜드(공시/공식) | `Organization` |
+  | 언어별 사이트 | `WebSite` |
+  | 호텔 프로퍼티 | `Hotel` (= LocalBusiness 계열) |
+  | 임원/인물 | `Person` |
+  | 채용공고 | `JobPosting` |
+  | 공식 영상 | `VideoObject` |
+  | FAQ/프레스킷 Q&A | `FAQPage` |
+  | 사이트 내비게이션 | `BreadcrumbList` |
+
+- **산출**: 엔티티-타입 맵(엔티티별 타입 + 필수 속성 목록).
+- **AC**: 모든 대상 엔티티에 타입과 Google 필수 속성 목록이 배정됨.
+- **리스크**: 과잉 타입 부여(불필요한 타입은 검증 부담만 가중) → "리치결과 가치 있는 타입" 우선.
+- 참고: `references/entity-and-type-map.md`
+
+### 6단계. 타입별 템플릿 설정 & 초안 추출 (자동화)
+- **목적**: 확정 클레임 + 타입 템플릿으로 JSON-LD 초안을 **자동 생성**한다.
+- **입력**: 확정 클레임 레지스터(`status=CONFIRMED`), `scripts/type_templates.json`.
+- **절차**:
+  ```bash
+  python scripts/build_schema_drafts.py path/to/claims_register.csv \
+      --templates scripts/type_templates.json --out drafts_out
+  ```
+  - CONFIRMED·비충돌 클레임만 스키마가 됨. PENDING/REJECTED/conflict/공란은 **제외 후 보고**.
+  - 미충족 슬롯은 **키 자체를 삭제**(placeholder 누출 원천 차단).
+  - 엔티티 간 `@id` 참조로 엔티티 그래프 형성(Hotel→parentOrganization 등).
+- **산출**: `drafts/*.jsonld`, 검증기 입력용 `schema_drafts_dataset.csv`, `build_report.md`(제외 클레임 목록).
+- **AC**: 초안에 placeholder/빈 객체 0건; 모든 제외 클레임이 보고서에 사유와 함께 기재.
+- **리스크**: 템플릿 누락 타입은 건너뜀(보고됨) → 5단계 맵과 템플릿 동기화.
+
+### 7단계. 리뷰·검토·수정 + 리뷰 가이드
+- **목적**: 초안을 사람·고객이 검토하되, **원본 JSON이 아니라 결함 리포트**로 검토하게 한다.
+- **입력**: 6단계 초안 + 검증기 결과.
+- **절차**:
+  1. 초안을 **즉시 검증기에 통과**(아래 8단계)시켜 P0=0 게이트부터 확보
+  2. 남은 항목을 `templates/review-guide.md` 기준으로 검토(사실 정확성·표기·번역)
+  3. 고객 검토는 P0가 0인 깨끗한 초안에 대해서만, 결함 리포트 기준으로 진행
+- **산출**: 수정 반영 초안 + 리뷰 가이드 체크 결과.
+- **AC**: 모든 P0 해소; 사실 정확성 검토 서명(저작자·검수자).
+- **리스크**: 사람이 원본 JSON을 직접 보면 "오류 과다" 문제 재발 → 반드시 리포트 기반 검토.
+- 참고: `templates/review-guide.md`
+
+### 8단계. 수정 초안의 rich result 적격성 점검
+- **목적**: 리치결과 적격성을 (1) 오프라인 게이트 + (2) Google 온라인 테스트로 이중 확인.
+- **입력**: 수정 초안 데이터셋.
+- **절차**:
+  ```bash
+  # 오프라인 게이트 (반드시 zero P0)
+  python ../16-seo-schema-validator/scripts/validate_schema.py drafts_out/schema_drafts_dataset.csv --out qa_out
+  ```
+  - 게이트 PASS 후, **표본 엔트리**를 Google Rich Results Test에 통과(이 런타임은 오프라인이라 온라인 테스트는 사용자가 수행)시켜 캡처.
+- **산출**: 검증기 리포트(Gate PASS) + Rich Results Test 표본 통과 캡처.
+- **AC**: P0=0, P1 트리아지 완료, 온라인 테스트 표본 green.
+- **리스크**: 오프라인 규칙은 호텔 도메인 큐레이션 부분집합 → 온라인 표본 검사로 보완.
+
+### 9단계. 발행 후 유효성 검증 & KG 변화 측정
+- **목적**: 배포된 스키마가 저작 초안과 일치하는지 확인하고, 4단계의 KG 개선과제 달성도를 측정한다.
+- **입력**: 라이브 URL.
+- **절차**:
+  1. 검증기 **Mode B**(라이브 URL)로 렌더링된 스키마 재검증 → `seo-comprehensive-audit` 4단계 연계
+  2. GSC "리치 결과" 리포트 모니터링(신규 오류 0 유지)
+  3. 4단계 KG 메모 대비 Knowledge Panel/Wikidata 노출·정확도 변화 측정
+- **산출**: 발행 후 검증 리포트 + KG 변화 측정(전/후 비교).
+- **AC**: 라이브 스키마 = 저작 초안; GSC 신규 구조화데이터 오류 0; KG 개선과제 진척 기록.
+- **리스크**: 렌더링 단계에서 JS로 스키마 누락/변형 → Mode B로 실측.
+
+---
+
+## 스테이지 게이트 (설계→개발→테스트→안정화→런칭 후)
+
+| 게이트 | 단계 | DoD(완료 정의) |
+|--------|------|----------------|
+| **G1 설계** | 1·2·5 | 소스 레지스터 완료(엔티티당 ≥2출처), 엔티티-타입 맵 확정(타입+필수속성) |
+| **G2 개발** | 3·4·6 | 클레임 레지스터 CONFIRMED·conflict 0, 빌더 실행 → 초안 placeholder 0 |
+| **G3 테스트** | 7·8 | 검증기 **zero P0**, P1 트리아지(`decision-log`), 사실정확성 검수 서명 |
+| **G4 안정화** | 8 | Google Rich Results Test 표본 green, 재실행 무회귀 |
+| **G5 런칭 후** | 9 | 라이브=초안 일치, GSC 신규오류 0, KG 변화 측정 기록 |
+
+---
+
+## 산출물 일람
+- `templates/source-register.csv` — 1·2단계 출처 대장
+- `templates/claims-register.csv` — 3·4단계 사실 대장(스키마의 원천)
+- `templates/review-guide.md` — 7단계 검토 기준
+- `scripts/type_templates.json` — 6단계 타입별 JSON-LD 템플릿
+- `scripts/build_schema_drafts.py` — 6단계 초안 자동 생성
+- (검증) `16-seo-schema-validator` — 7·8·9단계 게이트

custom-skills/17-seo-schema-generator/scripts/build_schema_drafts.py

@@ -0,0 +1,305 @@
+#!/usr/bin/env python3
+"""
+build_schema_drafts.py  —  Source-to-Schema draft generator (skill 17, pre-launch)
+
+WHAT IT DOES
+  Turns a *claims register* (reconciled, provenance-tracked facts) into JSON-LD
+  drafts, then writes a dataset CSV that feeds straight into
+  16-seo-schema-validator/scripts/validate_schema.py.
+
+WHY A CLAIMS REGISTER FIRST (the core idea)
+  Authoring schema for a site that does not exist yet is error-prone because the
+  facts live in many conflicting sources (DART, Wikipedia, brochures...). If you
+  pour raw, unreconciled facts straight into JSON-LD you reproduce every conflict
+  and gap as a schema defect. So we reconcile facts FIRST (one confirmed value per
+  property, with sources recorded), and only CONFIRMED, non-conflicting claims are
+  allowed to become schema. Everything else is reported, not shipped.
+
+THE PRUNING RULE (placeholder leakage is the #1 pre-launch defect)
+  A template slot that has no confirmed value is DELETED — never emitted as
+  "{{...}}" or "TODO". An empty nested object (only @type left) is dropped too.
+  This guarantees drafts contain only backed facts.
+
+INPUT (claims register): .csv or .xlsx with columns (case-insensitive, KR/EN aliases ok)
+  entity_id      e.g. org:shilla, hotel:theshilla-seoul   (groups rows into one node)
+  entity_type    Organization | Hotel | Person | JobPosting | VideoObject | WebSite | FAQPage
+  property       schema.org property, dotted for nesting: address.streetAddress
+                 append nothing for scalars; arrays are handled automatically
+  value          the confirmed value (pipe-separate multiple values: a|b|c)
+  lang           optional (ko/en/ja/zh) -> produces one draft per language
+  url            optional target URL (provisional ok) -> carried to validator
+  source_ids     optional pipe-separated refs into the source register (provenance)
+  authority      optional 1..n (1 = most authoritative) — for your audit trail
+  confidence     optional high|med|low
+  conflict       optional — any truthy value (Y/1/true/충돌) EXCLUDES the claim
+  status         CONFIRMED (default if blank) | PENDING | REJECTED  — only CONFIRMED ships
+  note           optional
+
+USAGE
+  python scripts/build_schema_drafts.py path/to/claims_register.csv \
+      --templates scripts/type_templates.json --out drafts_out
+  # then hand off to the validator:
+  python ../16-seo-schema-validator/scripts/validate_schema.py \
+      drafts_out/schema_drafts_dataset.csv --out qa_out
+"""
+
+import argparse, csv, json, os, sys, copy, re
+from collections import defaultdict, OrderedDict
+
+# ----------------------------------------------------------------------------- #
+# Column aliasing — accept Korean/English header variants                        #
+# ----------------------------------------------------------------------------- #
+COL_ALIASES = {
+    "entity_id":   ["entity_id", "entity", "엔티티", "엔티티id", "id"],
+    "entity_type": ["entity_type", "type", "타입", "유형", "스키마타입"],
+    "property":    ["property", "prop", "속성", "프로퍼티", "path"],
+    "value":       ["value", "값", "내용"],
+    "lang":        ["lang", "language", "언어", "언어코드"],
+    "url":         ["url", "메뉴 url", "메뉴url", "주소"],
+    "source_ids":  ["source_ids", "source", "sources", "출처", "출처id"],
+    "authority":   ["authority", "권위", "권위순위"],
+    "confidence":  ["confidence", "신뢰도"],
+    "conflict":    ["conflict", "충돌", "conflict_flag"],
+    "status":      ["status", "상태"],
+    "note":        ["note", "notes", "비고", "메모"],
+}
+TRUTHY = {"y", "yes", "1", "true", "t", "충돌", "conflict", "o"}
+PLACEHOLDER_RE = re.compile(r"^\{\{(.+?)\}\}$")          # matches an entire-string slot
+UNFILLED = object()                                      # sentinel: slot had no value
+
+
+def _norm(s):
+    return (s or "").strip().lower().replace(" ", "")
+
+
+def map_columns(headers):
+    """Return {canonical_name: actual_header} using the alias table."""
+    lookup = {_norm(h): h for h in headers}
+    out = {}
+    for canon, aliases in COL_ALIASES.items():
+        for a in aliases:
+            if _norm(a) in lookup:
+                out[canon] = lookup[_norm(a)]
+                break
+    return out
+
+
+# ----------------------------------------------------------------------------- #
+# Loading the claims register                                                    #
+# ----------------------------------------------------------------------------- #
+def load_rows(path):
+    """Yield dict rows from .csv or .xlsx. Keeps original header names."""
+    ext = os.path.splitext(path)[1].lower()
+    if ext in (".csv", ".tsv"):
+        delim = "\t" if ext == ".tsv" else ","
+        with open(path, encoding="utf-8-sig", newline="") as f:
+            for row in csv.DictReader(f, delimiter=delim):
+                yield row
+    elif ext in (".xlsx", ".xlsm"):
+        try:
+            from openpyxl import load_workbook
+        except ImportError:
+            sys.exit("openpyxl required for .xlsx — pip install openpyxl")
+        wb = load_workbook(path, read_only=True, data_only=True)
+        for ws in wb.worksheets:
+            rows = ws.iter_rows(values_only=True)
+            try:
+                headers = [str(h) if h is not None else "" for h in next(rows)]
+            except StopIteration:
+                continue
+            if not map_columns(headers).get("entity_id"):
+                continue                                  # sheet without our schema -> skip
+            for r in rows:
+                yield {headers[i]: ("" if v is None else str(v))
+                       for i, v in enumerate(r) if i < len(headers)}
+    else:
+        sys.exit(f"Unsupported claims register format: {ext}")
+
+
+# ----------------------------------------------------------------------------- #
+# Distil rows -> per-(entity, lang) confirmed claim maps + exclusion log         #
+# ----------------------------------------------------------------------------- #
+def collect_claims(path):
+    rows = list(load_rows(path))
+    if not rows:
+        sys.exit("Claims register is empty.")
+    cmap = map_columns(rows[0].keys())
+    for req in ("entity_id", "entity_type", "property", "value"):
+        if req not in cmap:
+            sys.exit(f"Missing required column '{req}'. Found: {list(rows[0].keys())}")
+
+    def g(row, key):
+        col = cmap.get(key)
+        return (row.get(col, "") if col else "").strip()
+
+    # claims[(entity_id, lang)] -> {"type":..., "url":..., "props": {path: [values]}}
+    claims = OrderedDict()
+    excluded = []                                          # (entity, prop, reason, detail)
+    for row in rows:
+        eid = g(row, "entity_id")
+        if not eid:
+            continue
+        etype = g(row, "entity_type")
+        prop = g(row, "property")
+        val = g(row, "value")
+        lang = g(row, "lang") or ""
+        status = (g(row, "status") or "CONFIRMED").upper()
+        conflict = _norm(g(row, "conflict")) in TRUTHY
+
+        if conflict:
+            excluded.append((eid, prop, "CONFLICT", f"sources disagree -> resolve first"))
+            continue
+        if status == "REJECTED":
+            excluded.append((eid, prop, "REJECTED", g(row, "note")))
+            continue
+        if status == "PENDING":
+            excluded.append((eid, prop, "PENDING", "not yet confirmed by an authoritative source"))
+            continue
+        if not val:
+            excluded.append((eid, prop, "EMPTY", "confirmed row but value is blank"))
+            continue
+
+        key = (eid, lang)
+        node = claims.setdefault(key, {"type": etype, "url": g(row, "url"),
+                                       "props": defaultdict(list)})
+        if etype and not node["type"]:
+            node["type"] = etype
+        if g(row, "url") and not node["url"]:
+            node["url"] = g(row, "url")
+        # pipe-separated value -> multiple values (array support)
+        for v in (val.split("|") if "|" in val else [val]):
+            v = v.strip()
+            if v:
+                node["props"][prop].append(v)
+    return claims, excluded
+
+
+# ----------------------------------------------------------------------------- #
+# Fill a template, pruning every unfilled slot                                   #
+# ----------------------------------------------------------------------------- #
+def fill(node_template, props):
+    """Recursively fill {{slots}}; return UNFILLED when a branch has no real data."""
+    if isinstance(node_template, str):
+        m = PLACEHOLDER_RE.match(node_template.strip())
+        if not m:
+            return node_template                            # literal (e.g. "@type":"Hotel")
+        path = m.group(1)
+        is_array = path.endswith("[]")
+        if is_array:
+            path = path[:-2]
+        vals = props.get(path, [])
+        if not vals:
+            return UNFILLED
+        if is_array:
+            return list(vals)
+        if len(vals) > 1:
+            print(f"  ! multiple values for scalar '{path}' — using first ({len(vals)} given)")
+        return vals[0]
+
+    if isinstance(node_template, dict):
+        out = OrderedDict()
+        for k, v in node_template.items():
+            filled = fill(v, props)
+            if filled is UNFILLED:
+                continue
+            out[k] = filled
+        # an object that only carries @type/@context (no real data, no @id ref) is empty
+        meaningful = [k for k in out if k not in ("@type", "@context")]
+        if not meaningful:
+            return UNFILLED
+        return out
+
+    if isinstance(node_template, list):
+        out = [x for x in (fill(i, props) for i in node_template) if x is not UNFILLED]
+        return out if out else UNFILLED
+
+    return node_template
+
+
+# ----------------------------------------------------------------------------- #
+# Main                                                                           #
+# ----------------------------------------------------------------------------- #
+def main():
+    ap = argparse.ArgumentParser(description="Build JSON-LD drafts from a claims register.")
+    ap.add_argument("claims", help="claims register .csv/.xlsx")
+    ap.add_argument("--templates", default=os.path.join(os.path.dirname(__file__), "type_templates.json"))
+    ap.add_argument("--out", default="drafts_out")
+    args = ap.parse_args()
+
+    templates = json.load(open(args.templates, encoding="utf-8"))["templates"]
+    claims, excluded = collect_claims(args.claims)
+
+    os.makedirs(os.path.join(args.out, "drafts"), exist_ok=True)
+    dataset_rows = []
+    built, skipped_type = 0, []
+
+    for (eid, lang), node in claims.items():
+        etype = node["type"]
+        if etype not in templates:
+            skipped_type.append((eid, etype))
+            continue
+        filled = fill(copy.deepcopy(templates[etype]["tpl"]), node["props"])
+        if filled is UNFILLED or not filled:
+            skipped_type.append((eid, f"{etype} (no usable claims)"))
+            continue
+        jsonld = json.dumps(filled, ensure_ascii=False, indent=2)
+        safe = re.sub(r"[^A-Za-z0-9]+", "_", eid).strip("_")
+        fname = f"{safe}__{lang}.jsonld" if lang else f"{safe}.jsonld"
+        with open(os.path.join(args.out, "drafts", fname), "w", encoding="utf-8") as f:
+            f.write(jsonld)
+        dataset_rows.append(OrderedDict([
+            ("entity_id", eid), ("entity_type", etype),
+            ("url", node["url"]), ("lang", lang),
+            ("jsonld", json.dumps(filled, ensure_ascii=False)),
+        ]))
+        built += 1
+
+    # dataset CSV — directly consumable by validate_schema.py (auto-detects 'jsonld')
+    ds_path = os.path.join(args.out, "schema_drafts_dataset.csv")
+    with open(ds_path, "w", encoding="utf-8-sig", newline="") as f:
+        w = csv.DictWriter(f, fieldnames=["entity_id", "entity_type", "url", "lang", "jsonld"])
+        w.writeheader()
+        w.writerows(dataset_rows)
+
+    # build report
+    rep = [
+        "# Schema Draft Build Report",
+        "",
+        f"- Entities built: **{built}**",
+        f"- Claims excluded (not shipped): **{len(excluded)}**",
+        f"- Entities skipped (no template / no usable claims): **{len(skipped_type)}**",
+        "",
+        "## Excluded claims (resolve before they can become schema)",
+    ]
+    if excluded:
+        rep.append("| entity | property | reason | detail |")
+        rep.append("|--------|----------|--------|--------|")
+        for eid, prop, reason, detail in excluded:
+            rep.append(f"| {eid} | {prop} | **{reason}** | {detail} |")
+    else:
+        rep.append("_None._")
+    if skipped_type:
+        rep += ["", "## Skipped entities", ""]
+        for eid, why in skipped_type:
+            rep.append(f"- {eid} — {why}")
+    rep += [
+        "", "## Next step",
+        "1. Resolve every excluded claim (confirm an authoritative value, clear conflicts).",
+        "2. Re-run this builder.",
+        "3. Validate the output (the QA gate):",
+        "   ```bash",
+        f"   python ../16-seo-schema-validator/scripts/validate_schema.py {ds_path} --out qa_out",
+        "   ```",
+        "4. Fix all P0 from the validator, then proceed to client review.",
+    ]
+    rep_path = os.path.join(args.out, "build_report.md")
+    open(rep_path, "w", encoding="utf-8").write("\n".join(rep))
+
+    print(f"Built {built} drafts | excluded {len(excluded)} claims | skipped {len(skipped_type)} entities")
+    print(f"Wrote: {ds_path}")
+    print(f"       {rep_path}")
+    print(f"       {os.path.join(args.out, 'drafts')}/*.jsonld")
+
+
+if __name__ == "__main__":
+    main()

custom-skills/17-seo-schema-generator/scripts/extract_site_claims.py

@@ -0,0 +1,346 @@
+#!/usr/bin/env python3
+"""
+extract_site_claims.py  —  Scenario 1 adapter: an EXISTING website → claims register.
+
+THE MERGE, IN ONE SENTENCE
+  Schema generation has two scenarios that differ only in WHERE facts come from:
+    1) from a given website   — the live pages ARE the source of truth (this script)
+    2) from collected sources — a not-yet-published site, facts scattered & conflicting
+  Both emit the SAME claims_register.csv, which build_schema_drafts.py then turns into
+  drafts and 16-seo-schema-validator gates. The claims register is the shared pivot
+  that lets one skill cover both scenarios.
+
+WHAT THIS DOES
+  Reads pages of an existing site and seeds a claims register from them:
+    - existing JSON-LD (<script type="application/ld+json">)  -> CONFIRMED (authority 1):
+      the site already published these facts about itself.
+    - <title> / meta description / OpenGraph / <html lang> / canonical -> PENDING:
+      inferred, not authoritative. The builder EXCLUDES PENDING claims until a human
+      confirms them — so inference never silently ships (the skill's core principle).
+
+  You then review/edit claims_register.csv, run build_schema_drafts.py, and validate.
+
+INPUT  (any mix):  URLs (needs `requests`), local .html files, or a directory of .html
+OUTPUT (in --out): claims_register.csv  +  extraction_report.md
+
+USAGE
+  python extract_site_claims.py https://example.com/ https://example.com/about --out site_claims
+  python extract_site_claims.py ./snapshot/ --out site_claims          # offline, local HTML
+  # then:
+  python build_schema_drafts.py site_claims/claims_register.csv --out drafts_out
+  python ../16-seo-schema-validator/scripts/validate_schema.py drafts_out/schema_drafts_dataset.csv --out qa_out
+"""
+
+import argparse
+import csv
+import json
+import os
+import re
+import sys
+from collections import OrderedDict
+from html.parser import HTMLParser
+from pathlib import Path
+from urllib.parse import urlparse
+
+JSONLD_RE = re.compile(
+    r'<script[^>]+type=["\']application/ld\+json["\'][^>]*>(.*?)</script>',
+    re.IGNORECASE | re.DOTALL,
+)
+
+# entity_id prefix per schema type — keeps ids readable and groupable.
+TYPE_PREFIX = {
+    "Organization": "org", "Corporation": "org", "LocalBusiness": "biz",
+    "WebSite": "site", "WebPage": "page",
+    "Hotel": "hotel", "LodgingBusiness": "hotel", "Resort": "hotel",
+    "Restaurant": "dining", "FoodEstablishment": "dining", "BarOrPub": "dining",
+    "Person": "person", "Product": "product", "Article": "article",
+    "NewsArticle": "article", "BlogPosting": "article", "Event": "event",
+    "FAQPage": "faq", "BreadcrumbList": "crumb",
+}
+# OpenGraph og:type -> our seed @type for the meta-only fallback.
+OG_TYPE_MAP = {"website": "WebSite", "article": "Article", "product": "Product",
+               "business.business": "LocalBusiness", "profile": "Person"}
+
+CLAIM_FIELDS = ["entity_id", "entity_type", "property", "value", "lang", "url",
+                "source_ids", "authority", "confidence", "conflict", "status", "note"]
+
+
+# --------------------------------------------------------------------------- #
+# Lightweight HTML meta extraction (stdlib only)
+# --------------------------------------------------------------------------- #
+class MetaParser(HTMLParser):
+    """Pull <title>, <html lang>, <link rel=canonical>, and <meta> name/property."""
+
+    def __init__(self):
+        super().__init__()
+        self.title_parts = []
+        self._in_title = False
+        self.lang = ""
+        self.canonical = ""
+        self.meta = {}  # name/property (lowercased) -> content
+
+    def handle_starttag(self, tag, attrs):
+        a = {k.lower(): (v or "") for k, v in attrs}
+        if tag == "html" and a.get("lang"):
+            self.lang = a["lang"].strip()
+        elif tag == "title":
+            self._in_title = True
+        elif tag == "link" and a.get("rel", "").lower() == "canonical" and a.get("href"):
+            self.canonical = a["href"].strip()
+        elif tag == "meta":
+            key = (a.get("property") or a.get("name") or "").lower().strip()
+            if key and "content" in a:
+                self.meta.setdefault(key, a["content"].strip())
+
+    def handle_endtag(self, tag):
+        if tag == "title":
+            self._in_title = False
+
+    def handle_data(self, data):
+        if self._in_title:
+            self.title_parts.append(data)
+
+    @property
+    def title(self):
+        return re.sub(r"\s+", " ", "".join(self.title_parts)).strip()
+
+
+# --------------------------------------------------------------------------- #
+# Page acquisition
+# --------------------------------------------------------------------------- #
+def gather_pages(inputs):
+    """Yield (url, html). Accepts http(s) URLs, .html files, and directories."""
+    for item in inputs:
+        if re.match(r"^https?://", item, re.IGNORECASE):
+            try:
+                import requests
+            except ImportError:
+                sys.exit("Fetching URLs needs requests: pip install requests "
+                         "(or pass local .html files / a directory instead).")
+            try:
+                r = requests.get(item, timeout=20,
+                                 headers={"User-Agent": "Mozilla/5.0 (SchemaGen/1.0)"})
+                r.raise_for_status()
+                yield item, r.text
+            except Exception as exc:  # noqa: BLE001 — best-effort fetch
+                print(f"  ! could not fetch {item}: {exc}", file=sys.stderr)
+        else:
+            p = Path(item)
+            if p.is_dir():
+                for hp in sorted(p.rglob("*.html")):
+                    hp = hp.resolve()
+                    yield hp.as_uri(), hp.read_text(encoding="utf-8", errors="replace")
+            elif p.is_file():
+                p = p.resolve()
+                yield p.as_uri(), p.read_text(encoding="utf-8", errors="replace")
+            else:
+                print(f"  ! not a URL/file/dir, skipped: {item}", file=sys.stderr)
+
+
+# --------------------------------------------------------------------------- #
+# JSON-LD node -> flat (dotted-path, value) claims
+# --------------------------------------------------------------------------- #
+def primary_type(node):
+    t = node.get("@type")
+    if isinstance(t, list):
+        return t[0] if t else ""
+    return t or ""
+
+
+def top_level_nodes(parsed):
+    """Return the ENTITY nodes only — @graph members, array items, or a single object.
+
+    Deliberately NOT recursive: nested objects (PostalAddress, GeoCoordinates, …) belong
+    to their parent and are captured by flatten() as dotted paths. Recursing here would
+    wrongly promote a nested address into its own entity.
+    """
+    if isinstance(parsed, dict) and "@graph" in parsed:
+        graph = parsed["@graph"]
+        return [n for n in graph if isinstance(n, dict) and "@type" in n]
+    if isinstance(parsed, list):
+        return [n for n in parsed if isinstance(n, dict) and "@type" in n]
+    if isinstance(parsed, dict) and "@type" in parsed:
+        return [parsed]
+    return []
+
+
+def flatten(node, prefix=""):
+    """Yield (property_path, value) pairs matching the template {{dotted.path}} slots.
+
+    - scalars        -> ("name", "X")
+    - scalar arrays  -> ("sameAs", "a|b|c")   (pipe-joined; builder splits on '|')
+    - nested objects -> recurse with dotted prefix ("address.streetAddress", ...)
+    - @type inside a nested object is structural (templates hard-code it) -> skipped
+    - a bare {"@id": "..."} reference -> ("parentOrganization.@id", "...")
+    """
+    for key, val in node.items():
+        if key == "@type":
+            continue
+        path = f"{prefix}{key}"
+        if isinstance(val, (str, int, float, bool)):
+            yield path, str(val)
+        elif isinstance(val, list):
+            scalars = [str(v) for v in val if isinstance(v, (str, int, float, bool))]
+            if scalars:
+                yield path, "|".join(scalars)
+            for v in val:  # objects inside arrays -> recurse (best-effort)
+                if isinstance(v, dict):
+                    yield from flatten(v, prefix=f"{path}.")
+        elif isinstance(val, dict):
+            yield from flatten(val, prefix=f"{path}.")
+
+
+def slugify(text, maxlen=40):
+    s = re.sub(r"^https?://", "", text or "")
+    s = re.sub(r"[^A-Za-z0-9]+", "-", s).strip("-").lower()
+    return s[:maxlen] or "node"
+
+
+def entity_id_for(node, url, idx):
+    """Readable, groupable id like `hotel:westin-hotel` from an @id or URL."""
+    etype = primary_type(node)
+    prefix = TYPE_PREFIX.get(etype, "node")
+    nid = node.get("@id")
+    if nid:
+        pr = urlparse(str(nid))
+        tail = [s for s in pr.path.split("/") if s]
+        parts = (tail[-1:] if tail else []) + ([pr.fragment] if pr.fragment else [])
+        base = "-".join(parts) or pr.netloc or str(nid)
+    else:
+        base = url or f"n{idx}"
+    return f"{prefix}:{slugify(base)}"
+
+
+# --------------------------------------------------------------------------- #
+# Build claims rows from one page
+# --------------------------------------------------------------------------- #
+def claims_from_page(url, html, default_lang, rows, seen_props):
+    """Append claim rows for one page. seen_props tracks (entity_id, property)
+    already taken from authoritative JSON-LD, so meta only fills genuine gaps."""
+    page_lang = ""
+    found_jsonld = False
+
+    # --- 1) existing JSON-LD -> CONFIRMED (authority 1) ---
+    for block in JSONLD_RE.findall(html):
+        try:
+            parsed = json.loads(block.strip())
+        except json.JSONDecodeError:
+            continue
+        for i, node in enumerate(top_level_nodes(parsed)):
+            etype = primary_type(node)
+            if not etype:
+                continue
+            found_jsonld = True
+            eid = entity_id_for(node, url, i)
+            node_lang = node.get("inLanguage") if isinstance(node.get("inLanguage"), str) else ""
+            lang = node_lang or default_lang
+            for prop, value in flatten(node):
+                rows.append(_row(eid, etype, prop, value, lang, url,
+                                 "S-SITE", 1, "high", "CONFIRMED",
+                                 "extracted from existing JSON-LD"))
+                seen_props.add((eid, prop))
+
+    # --- 2) meta / OpenGraph -> PENDING (inferred, needs confirmation) ---
+    mp = MetaParser()
+    try:
+        mp.feed(html)
+    except Exception:  # noqa: BLE001 — tolerate malformed HTML
+        pass
+    page_lang = mp.lang or default_lang
+    og_type = mp.meta.get("og:type", "").lower()
+    etype = OG_TYPE_MAP.get(og_type, "WebPage")
+    eid = f"{TYPE_PREFIX.get(etype, 'page')}:{slugify(mp.canonical or url)}"
+
+    inferred = {
+        "name": mp.meta.get("og:title") or mp.title,
+        "url": mp.meta.get("og:url") or mp.canonical or (url if url.startswith("http") else ""),
+        "description": mp.meta.get("og:description") or mp.meta.get("description"),
+        "image": mp.meta.get("og:image"),
+        "inLanguage": page_lang,
+    }
+    # Only emit meta claims when this page contributed NO JSON-LD (else JSON-LD wins).
+    if not found_jsonld:
+        for prop, value in inferred.items():
+            if value and (eid, prop) not in seen_props:
+                rows.append(_row(eid, etype, prop, value, page_lang, url,
+                                 "S-SITE-META", 2, "med", "PENDING",
+                                 "inferred from <title>/OpenGraph — confirm before shipping"))
+
+
+def _row(eid, etype, prop, value, lang, url, src, authority, conf, status, note):
+    return OrderedDict([
+        ("entity_id", eid), ("entity_type", etype), ("property", prop),
+        ("value", value), ("lang", lang or ""), ("url", url if url.startswith("http") else ""),
+        ("source_ids", src), ("authority", authority), ("confidence", conf),
+        ("conflict", ""), ("status", status), ("note", note),
+    ])
+
+
+# --------------------------------------------------------------------------- #
+# Main
+# --------------------------------------------------------------------------- #
+def main(argv=None):
+    ap = argparse.ArgumentParser(
+        description="Scenario-1 adapter: existing website -> claims register.")
+    ap.add_argument("inputs", nargs="+", help="URLs, .html files, or a directory")
+    ap.add_argument("--out", default="site_claims", help="output directory")
+    ap.add_argument("--default-lang", default="", help="fallback language code (e.g. ko)")
+    args = ap.parse_args(argv)
+
+    rows, seen = [], set()
+    pages = 0
+    for url, html in gather_pages(args.inputs):
+        pages += 1
+        before = len(rows)
+        claims_from_page(url, html, args.default_lang, rows, seen)
+        print(f"  · {url} → {len(rows) - before} claims")
+
+    if not rows:
+        print("No claims extracted (no JSON-LD or usable meta on the given pages).",
+              file=sys.stderr)
+        return 1
+
+    outdir = Path(args.out)
+    outdir.mkdir(parents=True, exist_ok=True)
+    reg = outdir / "claims_register.csv"
+    with open(reg, "w", encoding="utf-8-sig", newline="") as f:
+        w = csv.DictWriter(f, fieldnames=CLAIM_FIELDS)
+        w.writeheader()
+        w.writerows(rows)
+
+    confirmed = sum(1 for r in rows if r["status"] == "CONFIRMED")
+    pending = sum(1 for r in rows if r["status"] == "PENDING")
+    entities = sorted({r["entity_id"] for r in rows})
+    rep = [
+        "# Site Extraction Report", "",
+        f"- Pages read: **{pages}**",
+        f"- Claims extracted: **{len(rows)}** "
+        f"(CONFIRMED from JSON-LD: {confirmed} · PENDING from meta: {pending})",
+        f"- Entities seeded: **{len(entities)}**", "",
+        "## Entities", "",
+    ]
+    rep += [f"- `{e}`" for e in entities]
+    rep += [
+        "", "## Review before building",
+        "1. **CONFIRMED** rows came from the site's own JSON-LD — spot-check accuracy.",
+        "2. **PENDING** rows were inferred from `<title>`/OpenGraph and will NOT ship until "
+        "you set `status=CONFIRMED` (and clear any `conflict`).",
+        "3. Add anything the pages didn't expose (telephone, address, geo, sameAs).",
+        "", "## Next step",
+        "```bash",
+        f"python build_schema_drafts.py {reg} --out drafts_out",
+        "python ../16-seo-schema-validator/scripts/validate_schema.py "
+        "drafts_out/schema_drafts_dataset.csv --out qa_out",
+        "```",
+    ]
+    (outdir / "extraction_report.md").write_text("\n".join(rep), encoding="utf-8")
+
+    print(f"\nWrote {len(rows)} claims ({confirmed} CONFIRMED, {pending} PENDING) "
+          f"for {len(entities)} entities → {reg}")
+    print(f"      {outdir / 'extraction_report.md'}")
+    print("Review the register (confirm PENDING rows), then run build_schema_drafts.py.")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())

custom-skills/17-seo-schema-generator/scripts/make_sample.py

@@ -0,0 +1,87 @@
+#!/usr/bin/env python3
+"""
+make_sample.py — generate fixtures/sample_claims.csv
+
+A small, realistic claims register for the Shilla context. It exercises:
+  - 5 entity types: Organization, WebSite, Hotel, Person, JobPosting, VideoObject
+  - dotted nested paths (address.*, geo.*) and an array (sameAs[])
+  - @id cross-references between entities (Hotel.parentOrganization -> org:shilla)
+  - the EXCLUSION gate: one PENDING claim, one CONFLICT claim, one EMPTY value
+Run, then: python scripts/build_schema_drafts.py fixtures/sample_claims.csv
+"""
+import csv, os
+
+ROWS = [
+    # entity_id, entity_type, property, value, lang, url, source_ids, authority, confidence, conflict, status, note
+    # ---- Organization (DART + official + Wikidata) ----
+    ("org:shilla", "Organization", "@id", "https://www.shillahotels.com/#org", "", "", "", "1", "high", "", "CONFIRMED", ""),
+    ("org:shilla", "Organization", "name", "The Shilla Hotels & Resorts", "", "", "S-OFF|S-WIKI", "1", "high", "", "CONFIRMED", ""),
+    ("org:shilla", "Organization", "legalName", "주식회사 호텔신라", "", "", "S-DART", "1", "high", "", "CONFIRMED", "DART 법인명"),
+    ("org:shilla", "Organization", "url", "https://www.shillahotels.com/", "", "", "S-OFF", "1", "high", "", "CONFIRMED", ""),
+    ("org:shilla", "Organization", "foundingDate", "1973-05-09", "", "", "S-DART", "1", "high", "", "CONFIRMED", ""),
+    ("org:shilla", "Organization", "sameAs", "https://www.wikidata.org/wiki/Q494845|https://en.wikipedia.org/wiki/The_Shilla", "", "", "S-WIKI|S-WD", "2", "high", "", "CONFIRMED", "array via pipe"),
+    ("org:shilla", "Organization", "address.streetAddress", "동호로 249", "", "", "S-DART", "1", "high", "", "CONFIRMED", ""),
+    ("org:shilla", "Organization", "address.addressLocality", "중구", "", "", "S-DART", "1", "high", "", "CONFIRMED", ""),
+    ("org:shilla", "Organization", "address.addressRegion", "서울", "", "", "S-DART", "1", "high", "", "CONFIRMED", ""),
+    ("org:shilla", "Organization", "address.addressCountry", "KR", "", "", "S-DART", "1", "high", "", "CONFIRMED", ""),
+    # ---- WebSite (per-language) ----
+    ("site:ko", "WebSite", "@id", "https://www.shillahotels.com/ko#website", "ko", "https://www.shillahotels.com/ko/", "S-OFF", "1", "high", "", "CONFIRMED", ""),
+    ("site:ko", "WebSite", "name", "신라호텔", "ko", "", "S-OFF", "1", "high", "", "CONFIRMED", ""),
+    ("site:ko", "WebSite", "url", "https://www.shillahotels.com/ko/", "ko", "", "S-OFF", "1", "high", "", "CONFIRMED", ""),
+    ("site:ko", "WebSite", "inLanguage", "ko", "ko", "", "S-OFF", "1", "high", "", "CONFIRMED", ""),
+    ("site:ko", "WebSite", "publisher.@id", "https://www.shillahotels.com/#org", "ko", "", "", "1", "high", "", "CONFIRMED", "ref to org"),
+    # ---- Hotel (property; @id ref back to org) ----
+    ("hotel:theshilla-seoul", "Hotel", "@id", "https://www.shillahotels.com/ko/theshilla/seoul#hotel", "ko", "https://www.shillahotels.com/ko/theshilla/seoul/index.do", "S-OFF|S-BROCH", "1", "high", "", "CONFIRMED", ""),
+    ("hotel:theshilla-seoul", "Hotel", "name", "The Shilla Seoul", "ko", "", "S-OFF", "1", "high", "", "CONFIRMED", ""),
+    ("hotel:theshilla-seoul", "Hotel", "telephone", "+82-2-2233-3131", "ko", "", "S-OFF|S-GBP", "1", "high", "", "CONFIRMED", ""),
+    ("hotel:theshilla-seoul", "Hotel", "priceRange", "$$$$", "ko", "", "S-OFF", "2", "med", "", "CONFIRMED", ""),
+    ("hotel:theshilla-seoul", "Hotel", "brand.name", "The Shilla", "ko", "", "S-OFF", "1", "high", "", "CONFIRMED", ""),
+    ("hotel:theshilla-seoul", "Hotel", "parentOrganization.@id", "https://www.shillahotels.com/#org", "ko", "", "", "1", "high", "", "CONFIRMED", "entity graph link"),
+    ("hotel:theshilla-seoul", "Hotel", "address.streetAddress", "동호로 249", "ko", "", "S-OFF|S-GBP", "1", "high", "", "CONFIRMED", ""),
+    ("hotel:theshilla-seoul", "Hotel", "address.addressLocality", "서울", "ko", "", "S-OFF", "1", "high", "", "CONFIRMED", ""),
+    ("hotel:theshilla-seoul", "Hotel", "address.addressCountry", "KR", "ko", "", "S-OFF", "1", "high", "", "CONFIRMED", ""),
+    ("hotel:theshilla-seoul", "Hotel", "geo.latitude", "37.5564", "ko", "", "S-GBP", "1", "high", "", "CONFIRMED", ""),
+    ("hotel:theshilla-seoul", "Hotel", "geo.longitude", "127.0058", "ko", "", "S-GBP", "1", "high", "", "CONFIRMED", ""),
+    # ---- Person (executive bio) ----
+    ("person:ceo", "Person", "@id", "https://www.shillahotels.com/#ceo", "", "", "S-DART|S-NEWS", "1", "high", "", "CONFIRMED", ""),
+    ("person:ceo", "Person", "name", "이부진", "", "", "S-DART", "1", "high", "", "CONFIRMED", ""),
+    ("person:ceo", "Person", "jobTitle", "대표이사 사장", "", "", "S-DART", "1", "high", "", "CONFIRMED", ""),
+    ("person:ceo", "Person", "worksFor.@id", "https://www.shillahotels.com/#org", "", "", "", "1", "high", "", "CONFIRMED", ""),
+    # ---- JobPosting (recruitment site) ----
+    ("job:fo-manager", "JobPosting", "title", "프런트오피스 매니저", "ko", "https://recruit.shilla.net/job/1234", "S-RECRUIT", "1", "high", "", "CONFIRMED", ""),
+    ("job:fo-manager", "JobPosting", "description", "더 신라 서울 프런트오피스 운영 총괄 및 VIP 응대.", "ko", "", "S-RECRUIT", "1", "high", "", "CONFIRMED", ""),
+    ("job:fo-manager", "JobPosting", "datePosted", "2026-05-01", "ko", "", "S-RECRUIT", "1", "high", "", "CONFIRMED", ""),
+    ("job:fo-manager", "JobPosting", "employmentType", "FULL_TIME", "ko", "", "S-RECRUIT", "1", "high", "", "CONFIRMED", ""),
+    ("job:fo-manager", "JobPosting", "hiringOrganization.@id", "https://www.shillahotels.com/#org", "ko", "", "", "1", "high", "", "CONFIRMED", ""),
+    ("job:fo-manager", "JobPosting", "jobLocation.addressLocality", "서울", "ko", "", "S-RECRUIT", "1", "high", "", "CONFIRMED", ""),
+    ("job:fo-manager", "JobPosting", "jobLocation.addressCountry", "KR", "ko", "", "S-RECRUIT", "1", "high", "", "CONFIRMED", ""),
+    # ---- VideoObject (official YouTube) ----
+    ("video:brand-film", "VideoObject", "name", "The Shilla — Authentic Indulgence", "", "https://www.youtube.com/watch?v=XXXX", "S-YT", "1", "high", "", "CONFIRMED", ""),
+    ("video:brand-film", "VideoObject", "description", "더 신라 브랜드 필름.", "", "", "S-YT", "1", "high", "", "CONFIRMED", ""),
+    ("video:brand-film", "VideoObject", "thumbnailUrl", "https://i.ytimg.com/vi/XXXX/maxresdefault.jpg", "", "", "S-YT", "1", "high", "", "CONFIRMED", ""),
+    ("video:brand-film", "VideoObject", "uploadDate", "2025-11-20", "", "", "S-YT", "1", "high", "", "CONFIRMED", ""),
+    ("video:brand-film", "VideoObject", "duration", "PT1M45S", "", "", "S-YT", "1", "high", "", "CONFIRMED", ""),
+    ("video:brand-film", "VideoObject", "publisher.@id", "https://www.shillahotels.com/#org", "", "", "", "1", "high", "", "CONFIRMED", ""),
+    # ---- EXCLUSION GATE demonstrations (these must NOT appear in drafts) ----
+    ("hotel:theshilla-seoul", "Hotel", "image", "https://example.com/seoul.jpg", "ko", "", "S-OFF", "3", "low", "", "PENDING", "이미지 최종본 미확정"),
+    ("org:shilla", "Organization", "telephone", "+82-2-2233-3131", "", "", "S-OFF", "2", "med", "Y", "CONFIRMED", "대표번호 vs IR번호 출처 충돌"),
+    ("person:ceo", "Person", "image", "", "", "", "", "", "", "", "CONFIRMED", "값 공란 -> 제외"),
+]
+
+HEADERS = ["entity_id", "entity_type", "property", "value", "lang", "url",
+           "source_ids", "authority", "confidence", "conflict", "status", "note"]
+
+
+def main():
+    here = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+    out = os.path.join(here, "fixtures", "sample_claims.csv")
+    os.makedirs(os.path.dirname(out), exist_ok=True)
+    with open(out, "w", encoding="utf-8-sig", newline="") as f:
+        w = csv.writer(f)
+        w.writerow(HEADERS)
+        w.writerows(ROWS)
+    print("Wrote", out, f"({len(ROWS)} claim rows)")
+
+
+if __name__ == "__main__":
+    main()

custom-skills/17-seo-schema-generator/scripts/requirements.txt

@@ -0,0 +1,6 @@
+# build_schema_drafts.py and extract_site_claims.py run on the Python standard
+# library alone for CSV input and local-HTML extraction (the offline default).
+#
+# Optional extras, installed only when you need them:
+openpyxl>=3.1   # read .xlsx claims registers
+requests>=2.31  # fetch live URLs in extract_site_claims.py (Mode 1 over the network)

custom-skills/17-seo-schema-generator/scripts/type_templates.json

@@ -0,0 +1,136 @@
+{
+  "_meta": {
+    "purpose": "JSON-LD draft templates for source-to-schema authoring (pre-launch).",
+    "placeholder_syntax": "{{property.path}} — dotted paths map to claims-register 'property' column. Lines whose value stays unfilled are dropped (never shipped as placeholder).",
+    "aligned_with": "16-seo-schema-validator/scripts/schema_rules.json (required props match Google rich-result requirements)"
+  },
+  "templates": {
+    "Organization": {
+      "_source_hint": "DART, official site footer/about, sustainability report, Wikidata, newsroom",
+      "tpl": {
+        "@context": "https://schema.org",
+        "@type": "Organization",
+        "@id": "{{@id}}",
+        "name": "{{name}}",
+        "legalName": "{{legalName}}",
+        "url": "{{url}}",
+        "logo": "{{logo}}",
+        "sameAs": "{{sameAs[]}}",
+        "foundingDate": "{{foundingDate}}",
+        "address": {
+          "@type": "PostalAddress",
+          "streetAddress": "{{address.streetAddress}}",
+          "addressLocality": "{{address.addressLocality}}",
+          "addressRegion": "{{address.addressRegion}}",
+          "postalCode": "{{address.postalCode}}",
+          "addressCountry": "{{address.addressCountry}}"
+        },
+        "contactPoint": {
+          "@type": "ContactPoint",
+          "telephone": "{{contactPoint.telephone}}",
+          "contactType": "{{contactPoint.contactType}}"
+        }
+      }
+    },
+    "WebSite": {
+      "_source_hint": "official homepage; one per language site",
+      "tpl": {
+        "@context": "https://schema.org",
+        "@type": "WebSite",
+        "@id": "{{@id}}",
+        "name": "{{name}}",
+        "url": "{{url}}",
+        "inLanguage": "{{inLanguage}}",
+        "publisher": { "@id": "{{publisher.@id}}" }
+      }
+    },
+    "Hotel": {
+      "_source_hint": "property pages, brochure PDF, GBP, booking data; one per property per language",
+      "tpl": {
+        "@context": "https://schema.org",
+        "@type": "Hotel",
+        "@id": "{{@id}}",
+        "name": "{{name}}",
+        "url": "{{url}}",
+        "telephone": "{{telephone}}",
+        "priceRange": "{{priceRange}}",
+        "image": "{{image[]}}",
+        "brand": { "@type": "Brand", "name": "{{brand.name}}" },
+        "parentOrganization": { "@id": "{{parentOrganization.@id}}" },
+        "address": {
+          "@type": "PostalAddress",
+          "streetAddress": "{{address.streetAddress}}",
+          "addressLocality": "{{address.addressLocality}}",
+          "addressRegion": "{{address.addressRegion}}",
+          "postalCode": "{{address.postalCode}}",
+          "addressCountry": "{{address.addressCountry}}"
+        },
+        "geo": {
+          "@type": "GeoCoordinates",
+          "latitude": "{{geo.latitude}}",
+          "longitude": "{{geo.longitude}}"
+        }
+      }
+    },
+    "Person": {
+      "_source_hint": "executive bios, people-info sites, Wikipedia, press kit; one per person",
+      "tpl": {
+        "@context": "https://schema.org",
+        "@type": "Person",
+        "@id": "{{@id}}",
+        "name": "{{name}}",
+        "jobTitle": "{{jobTitle}}",
+        "worksFor": { "@id": "{{worksFor.@id}}" },
+        "url": "{{url}}",
+        "image": "{{image}}",
+        "sameAs": "{{sameAs[]}}"
+      }
+    },
+    "JobPosting": {
+      "_source_hint": "recruitment sites (채용공고); one per open role",
+      "tpl": {
+        "@context": "https://schema.org",
+        "@type": "JobPosting",
+        "title": "{{title}}",
+        "description": "{{description}}",
+        "datePosted": "{{datePosted}}",
+        "validThrough": "{{validThrough}}",
+        "employmentType": "{{employmentType}}",
+        "hiringOrganization": { "@id": "{{hiringOrganization.@id}}" },
+        "jobLocation": {
+          "@type": "Place",
+          "address": {
+            "@type": "PostalAddress",
+            "addressLocality": "{{jobLocation.addressLocality}}",
+            "addressCountry": "{{jobLocation.addressCountry}}"
+          }
+        }
+      }
+    },
+    "VideoObject": {
+      "_source_hint": "official YouTube channel; one per featured video",
+      "tpl": {
+        "@context": "https://schema.org",
+        "@type": "VideoObject",
+        "name": "{{name}}",
+        "description": "{{description}}",
+        "thumbnailUrl": "{{thumbnailUrl[]}}",
+        "uploadDate": "{{uploadDate}}",
+        "duration": "{{duration}}",
+        "contentUrl": "{{contentUrl}}",
+        "embedUrl": "{{embedUrl}}",
+        "publisher": { "@id": "{{publisher.@id}}" }
+      }
+    },
+    "FAQPage": {
+      "_source_hint": "press kit FAQ, newsroom, distilled common questions; one per FAQ page",
+      "tpl": {
+        "@context": "https://schema.org",
+        "@type": "FAQPage",
+        "url": "{{url}}",
+        "inLanguage": "{{inLanguage}}",
+        "mainEntity": "{{mainEntity[]}}"
+      }
+    }
+  }
+}

custom-skills/17-seo-schema-generator/templates/claims-register.csv

@@ -0,0 +1,8 @@
+entity_id,entity_type,property,value,lang,url,source_ids,authority,confidence,conflict,status,note
+org:example,Organization,@id,https://www.example.com/#org,,,S-OFF,1,high,,CONFIRMED,
+org:example,Organization,name,Example Corp,,,S-OFF|S-DART,1,high,,CONFIRMED,
+org:example,Organization,url,https://www.example.com/,,,S-OFF,1,high,,CONFIRMED,
+org:example,Organization,address.addressLocality,Seoul,,,S-DART,1,high,,CONFIRMED,
+org:example,Organization,address.addressCountry,KR,,,S-DART,1,high,,CONFIRMED,
+org:example,Organization,sameAs,https://www.wikidata.org/wiki/Q000|https://en.wikipedia.org/wiki/Example,,,S-WD|S-WIKI,2,high,,CONFIRMED,array via pipe
+org:example,Organization,foundingDate,1998-01-01,,,S-DART,1,high,Y,PENDING,두 출처 연도 충돌 -> 해소 필요

custom-skills/17-seo-schema-generator/templates/review-guide.md

@@ -0,0 +1,40 @@
+# Schema 초안 리뷰 가이드 (7단계)
+
+> 원칙: **사람은 원본 JSON을 직접 보지 않는다.** 기계가 잡을 수 있는 결함은 검증기 게이트(8단계)가
+> 먼저 0건으로 만들고, 사람은 "기계가 못 잡는 것"만 본다. 그래야 "오류 과다" 문제가 재발하지 않는다.
+
+## 검토 순서
+1. **먼저 검증기 통과** → `zero P0` 확보 (P0가 남은 초안은 검토 대상 아님)
+2. 아래 항목은 사람만 판단 가능 → 검토
+3. 고객 검토는 P0=0인 깨끗한 초안 + 결함 리포트로만 진행
+
+## 사람이 검토할 항목 (기계가 못 잡는 것)
+
+### A. 사실 정확성 (출처 대조)
+- [ ] `name` / `legalName` 이 공식 표기와 정확히 일치하는가 (공백·영문병기 포함)
+- [ ] 주소·전화가 **현재 유효한** 값인가 (출처가 오래되지 않았는가)
+- [ ] `foundingDate` 등 날짜가 공시값과 일치하는가
+- [ ] 인물의 `jobTitle` 이 **현직** 기준인가
+
+### B. 엔티티 정합
+- [ ] `sameAs` 가 **정확히 그 엔티티**를 가리키는가 (동명 오정합 없는가)
+- [ ] `@id` 참조가 의도한 엔티티로 연결되는가 (Hotel→올바른 Organization)
+- [ ] 브랜드 티어(`brand.name`)가 프로퍼티와 일치하는가 (The Shilla/Monogram/Stay)
+
+### C. 언어·번역
+- [ ] 언어별 초안의 `inLanguage` 와 실제 값 언어가 일치하는가
+- [ ] 번역값이 공식 다국어 표기와 일치하는가 (임의 번역 아님)
+
+### D. 범위 적절성
+- [ ] 스키마를 붙이면 안 되는 페이지(mypage/login/booking)에 초안이 없는가
+- [ ] 누락된 핵심 엔티티가 없는가 (엔티티-타입 맵 대조)
+
+## 검토 결과 처리
+- 수정 필요 → 클레임 레지스터에서 값 수정 후 **빌더 재실행**(JSON 직접 수정 금지: 원천은 항상 클레임)
+- 충돌 발견 → `conflict=Y`, `status=PENDING` → 출처 권위로 해소
+- 검토 완료 → 저작자·검수자 서명, P1은 `decision-log`에 기록
+
+## 서명
+- 저작(빌드): ______  / 일자: 2026-__-__
+- 검수(사실확인): ______ / 일자: 2026-__-__
+- 게이트(검증기 PASS) 확인: ______ / 일자: 2026-__-__

custom-skills/17-seo-schema-generator/templates/source-register.csv

@@ -0,0 +1,11 @@
+source_id,source_type,title_or_name,url_or_filepath,retrieved_date,authority,language,entities_covered,note
+S-DART,corporate_disclosure,DART 사업보고서,https://dart.fss.or.kr/...,2026-05-__,1,ko,org:shilla,법인명/설립일/주소/대표자
+S-OFF,official_site,공식 홈페이지 About/푸터,https://www.shillahotels.com/,2026-05-__,1,ko,org:shilla|hotel:*|site:ko,공식 표기/연락처/URL
+S-SUSTAIN,sustainability_report,지속가능경영보고서 2025,/path/to/esg.pdf,2026-05-__,2,ko,org:shilla,서사/정책
+S-WD,wikidata,Wikidata 항목,https://www.wikidata.org/wiki/Q______,2026-05-__,2,en,org:shilla,Q-ID/sameAs
+S-WIKI,wikipedia,위키백과,https://en.wikipedia.org/wiki/______,2026-05-__,2,en,org:shilla,sameAs/국제표기
+S-RECRUIT,recruitment,채용 사이트 공고,https://recruit._____,2026-05-__,1,ko,job:*,JobPosting 원천
+S-YT,youtube,공식 YouTube 채널,https://www.youtube.com/@______,2026-05-__,1,ko,video:*,VideoObject 원천
+S-GBP,google_business_profile,Google Business Profile,,2026-05-__,1,ko,hotel:*,NAP/geo
+S-BROCH,brochure_pdf,프로퍼티 브로셔,/path/to/brochure.pdf,2026-05-__,2,ko,hotel:*,시설 스펙
+S-NEWS,media_article,주요 미디어 기사,https://_____,2026-05-__,3,ko,person:ceo,교차검증

custom-skills/18-seo-local-audit/SKILL.md

@@ -0,0 +1,239 @@
+---
+name: seo-local-audit
+description: |
+  Local business SEO auditor for Korean-market businesses. Covers business identity extraction,
+  NAP consistency, Google Business Profile, Naver Smart Place, Kakao Map, local citations,
+  and LocalBusiness schema validation.
+  Triggers: local SEO, NAP audit, Google Business Profile, GBP optimization, local citations,
+  네이버 스마트플레이스, 카카오맵, 로컬 SEO.
+---
+
+# SEO Local Audit
+
+## Purpose
+
+Audit local business SEO for Korean-market businesses: business identity extraction, NAP consistency, GBP optimization, Naver Smart Place, Kakao Map, local citations, and LocalBusiness schema markup.
+
+## Core Capabilities
+
+1. **Business Identity** - Extract official names, address, phone from website schema/content
+2. **NAP Consistency** - Cross-platform verification against canonical NAP
+3. **GBP Optimization** - Layered discovery + profile completeness audit
+4. **Naver Smart Place** - Layered discovery + listing completeness audit
+5. **Kakao Map** - Presence verification + NAP check
+6. **Citation Audit** - Korean-first directory presence
+7. **Schema Validation** - LocalBusiness JSON-LD markup
+
+## MCP Tool Usage
+
+```
+mcp__firecrawl__scrape: Extract NAP and schema from website
+mcp__perplexity__search: Find citations, GBP, Naver Place listings
+mcp__notion__create-page: Save audit findings
+```
+
+## Workflow
+
+### Step 0: Business Identity (MANDATORY FIRST STEP)
+
+Before any audit, establish the official business identity.
+
+**Sources (in priority order):**
+1. Website schema markup (JSON-LD `Organization`, `Hospital`, `LocalBusiness`) — `name` field is authoritative
+2. Contact page / About page
+3. Footer (address, phone, social links)
+4. User-provided information
+
+**Data to collect:**
+
+| Field | Example |
+|-------|---------|
+| Official name (Korean) | 제이미성형외과의원 |
+| Official name (English) | Jamie Plastic Surgery Clinic |
+| Brand/display name | Jamie Clinic |
+| Website URL | https://www.jamie.clinic |
+| Address (Korean) | 서울특별시 강남구 ... |
+| Phone | 02-XXX-XXXX |
+| Known GBP URL | (if available) |
+| Known Naver Place URL | (if available) |
+| Known Kakao Map URL | (if available) |
+
+Look for these URL patterns in `sameAs`, footer links, or embedded iframes:
+- GBP: `maps.app.goo.gl/*`, `google.com/maps/place/*`, `g.page/*`
+- Naver Place: `naver.me/*`, `map.naver.com/*/place/*`, `m.place.naver.com/*`
+- Kakao Map: `place.map.kakao.com/*`, `kko.to/*`
+
+### Step 1: Website NAP Extraction
+
+Scrape header, footer, contact page, about page. Cross-reference with schema markup. Establish the **canonical NAP** baseline.
+
+### Step 2: GBP Verification & Audit
+
+**Layered discovery (try in order, stop when found):**
+1. Use provided GBP URL (from Step 0 or user input)
+2. Check website for GBP link (footer, contact, schema `sameAs`, embedded Google Maps iframe)
+3. Search: `"[Korean Name]" "[City/District]" Google Maps`
+4. Search: `"[English Name]" Google Maps [City]`
+5. Search: `"[exact phone number]" site:google.com/maps`
+
+**Important**: Google Maps is JS-rendered — scraping tools cannot extract business data. Use search for discovery, verify via search result snippets.
+
+**If found — audit checklist (score /10):**
+- [ ] Business name matches canonical NAP
+- [ ] Address is complete and accurate
+- [ ] Phone number matches
+- [ ] Business hours are current
+- [ ] Primary + secondary categories appropriate
+- [ ] Business description complete
+- [ ] 10+ photos uploaded
+- [ ] Posts are recent (within 7 days)
+- [ ] Reviews are responded to
+- [ ] Q&A section is active
+
+**If NOT found:** Report as **"not discoverable via web search"** (distinct from "does not exist").
+
+### Step 3: Naver Smart Place Verification & Audit
+
+**Layered discovery (try in order, stop when found):**
+1. Use provided Naver Place URL (from Step 0 or user input)
+2. Check website for Naver Place link (footer, contact, schema `sameAs`)
+3. Search: `"[Korean Name]" site:map.naver.com`
+4. Search: `"[Korean Name]" 네이버 지도 [district]`
+5. Search: `"[Korean Name]" 네이버 스마트플레이스`
+6. Search: `"[exact phone number]" site:map.naver.com`
+
+**Important**: Naver Map is JS-rendered — scraping tools cannot extract data. Use search for discovery, verify via snippets.
+
+**If found — audit checklist (score /10):**
+- [ ] Business name matches canonical NAP
+- [ ] Address is complete and accurate
+- [ ] Phone number matches
+- [ ] Business hours are current
+- [ ] Place is "claimed" (owner-managed / 업주 등록)
+- [ ] Keywords/tags are set
+- [ ] Booking/reservation link present
+- [ ] Recent blog reviews linked
+- [ ] Photos uploaded and current
+- [ ] Menu/service/price information present
+
+**If NOT found:** Report as **"not discoverable via web search"** (not "does not exist" or "not registered").
+
+### Step 4: Kakao Map Verification
+
+**Discovery:**
+1. Use provided Kakao Map URL (from Step 0)
+2. Check website for Kakao Map link (`place.map.kakao.com/*`, `kko.to/*`)
+3. Search: `"[Korean Name]" site:place.map.kakao.com`
+4. Search: `"[Korean Name]" 카카오맵 [district]`
+
+**If found:** Verify NAP consistency against canonical NAP.
+
+### Step 5: Citation Discovery
+
+**Korean market platform priorities:**
+
+| Platform | Priority | Market |
+|----------|----------|--------|
+| Google Business Profile | Critical | Global |
+| Naver Smart Place (네이버 스마트플레이스) | Critical | Korea |
+| Kakao Map (카카오맵) | High | Korea |
+| Industry-specific directories | High | Varies |
+| Apple Maps | Medium | Global |
+| Bing Places | Low | Global |
+
+**Korean medical/cosmetic industry directories:**
+- 강남언니 (Gangnam Unni)
+- 바비톡 (Babitalk)
+- 성예사 (Sungyesa)
+- 굿닥 (Goodoc)
+- 똑닥 (Ddocdoc)
+- 모두닥 (Modoodoc)
+- 하이닥 (HiDoc)
+
+### Step 6: NAP Consistency Report
+
+Cross-reference all sources against canonical NAP.
+
+**Common inconsistency points:**
+- Building/landmark names — authoritative source is the **business registration certificate** (사업자등록증)
+- Phone format variations (02-XXX-XXXX vs +82-2-XXX-XXXX)
+- Address format (road-name vs lot-number / 도로명 vs 지번)
+- Korean vs English name spelling variations
+- Suite/floor number omissions
+
+### Step 7: LocalBusiness Schema Validation
+
+Validate JSON-LD completeness: @type, name, address, telephone, openingHours, geo (GeoCoordinates), sameAs (GBP, Naver, Kakao, social), url, image.
+
+## Scoring
+
+| Component | Weight | Max Score |
+|-----------|--------|-----------|
+| Business Identity completeness | 5% | /10 |
+| NAP Consistency | 20% | /10 |
+| GBP Optimization | 20% | /10 |
+| Naver Smart Place | 20% | /10 |
+| Kakao Map presence | 10% | /10 |
+| Citations (directories) | 10% | /10 |
+| LocalBusiness Schema | 15% | /10 |
+
+**Overall Local SEO Score** = weighted average, normalized to /100.
+
+## Output Format
+
+```markdown
+## Local SEO Audit: [Business]
+
+### Business Identity
+| Field | Value |
+|-------|-------|
+| Korean Name | ... |
+| English Name | ... |
+| Address | ... |
+| Phone | ... |
+
+### NAP Consistency: X/10
+| Source | Name | Address | Phone | Status |
+|--------|------|---------|-------|--------|
+| Website | OK/Issue | OK/Issue | OK/Issue | Match/Mismatch |
+| GBP | OK/Issue | OK/Issue | OK/Issue | Match/Mismatch |
+| Naver Place | OK/Issue | OK/Issue | OK/Issue | Match/Mismatch |
+| Kakao Map | OK/Issue | OK/Issue | OK/Issue | Match/Mismatch |
+
+### GBP Score: X/10
+[Checklist results]
+
+### Naver Smart Place: X/10
+[Checklist results]
+
+### Kakao Map: X/10
+[Status + NAP check]
+
+### Citations: X/10
+| Platform | Found | NAP Match |
+|----------|-------|-----------|
+| ... | | |
+
+### LocalBusiness Schema: X/10
+- Present: Yes/No
+- Valid: Yes/No
+- Missing fields: [list]
+
+### Overall Score: XX/100 (Grade)
+### Priority Actions
+1. [Recommendations]
+```
+
+## Notes
+
+- GBP and Naver Map are JS-rendered — scraping tools cannot extract listing data. Always use search for discovery.
+- "Not discoverable via web search" != "does not exist." Always use this precise language.
+- For Korean businesses, Naver Smart Place is as important as GBP (often more so for domestic traffic).
+
+## Notion Output (Required)
+
+All audit reports MUST be saved to OurDigital SEO Audit Log:
+- **Database ID**: `2c8581e5-8a1e-8035-880b-e38cefc2f3ef`
+- **Properties**: Issue (title), Site (url), Category (Local SEO), Priority, Found Date, Audit ID
+- **Language**: Korean with English technical terms
+- **Audit ID Format**: LOCAL-YYYYMMDD-NNN

custom-skills/19-seo-keyword-strategy/SKILL.md

@@ -0,0 +1,148 @@
+---
+name: seo-keyword-strategy
+description: |
+  Keyword strategy and research for SEO campaigns.
+  Triggers: keyword research, keyword analysis, keyword gap, search volume,
+  keyword clustering, intent classification, 키워드 전략, 키워드 분석,
+  키워드 리서치, 검색량 분석, 키워드 클러스터링.
+---
+
+# SEO Keyword Strategy & Research
+
+## Purpose
+
+Expand seed keywords, classify search intent, cluster topics, and identify competitor keyword gaps for comprehensive keyword strategy development.
+
+## Core Capabilities
+
+1. **Keyword Expansion** - Matching terms, related terms, search suggestions
+2. **Korean Market** - Suffix expansion, Naver autocomplete, Korean intent patterns
+3. **Intent Classification** - Informational, navigational, commercial, transactional
+4. **Topic Clustering** - Group keywords into semantic clusters
+5. **Gap Analysis** - Find competitor keywords missing from target site
+
+## Data Source Selection
+
+This skill can pull keyword data from multiple backends. **Pick one per task** — don't fan out to every backend by default (cost + rate limits).
+
+| Backend | Best for | Notes |
+|---|---|---|
+| **Semrush MCP** (`mcp__semrush__*`) | Default for keyword volume, related/matching terms, organic competitor pulls | Call pattern: `keyword_research` → `get_report_schema` → `execute_report`. `database="us"` default; `"kr"` for Korean market. |
+| **Ahrefs MCP** (`mcp__ahrefs__*`) | Ahrefs DR/UR weighting; first-party `gsc-keywords` (only Ahrefs integrates GSC inside its MCP) | `keywords-explorer-overview`, `-matching-terms`, `-related-terms`, `-search-suggestions`, `-volume-by-country`, `gsc-keywords`. |
+| **OurSEO Agent CLI** (`our keywords *`) | DataForSEO under the hood — cheapest per call, batch-friendly, Korean-aware via `--location 2410` | Claude Code only (needs Bash). Wrap calls: `our keywords volume`, `ideas`, `for-site`, `intent`, `difficulty`. |
+| **OurSEO Agent MCP** (`mcp__ourseo__*`) | Claude Desktop equivalent for crawl-derived keywords + Knowledge Graph entity expansion | `search_knowledge_graph` for entity seeding; `crawl_website` to extract on-page keyword inventory from the target site itself. |
+| **DataForSEO MCP** (`mcp__dfs-mcp__*`) | Direct fallback when `our` CLI isn't available | Same data as `our keywords *`. |
+| **GSC** (via `our research search-console` or Ahrefs `gsc-*`) | First-party queries the site actually ranks for — ground truth, not estimates | Use to validate/prune Semrush or Ahrefs lists with real impressions/CTR. |
+
+### How to pick
+
+Apply these in order; stop at the first match:
+
+1. **User named a backend explicitly** in the prompt → use it.
+2. **User preference memory** — read `feedback_seo_tool_preferences.md`; honor the task-type default there.
+3. **Task needs a capability only one backend has** (e.g., `gsc-keywords` first-party data, or `mcp__ourseo__search_knowledge_graph` entity expansion) → use that backend.
+4. **Default by market**:
+   - English-market or unspecified → **Semrush MCP** with `database="us"`.
+   - Korean market → **OurSEO CLI** `our keywords <subcmd> --location 2410 --language ko` (Claude Code), or **Semrush MCP** with `database="kr"` (Claude Desktop).
+5. **Still ambiguous on a non-trivial task** → ask once via `AskUserQuestion` listing the top 2–3 candidates.
+
+### Backend call patterns
+
+**Semrush MCP (default):**
+```
+mcp__semrush__keyword_research(query="<seed>", database="us")
+mcp__semrush__get_report_schema(report_id="...")
+mcp__semrush__execute_report(report_id="...", params={...})
+```
+
+**OurSEO CLI (Korean default, Claude Code):**
+```bash
+our keywords volume "<keyword>" --location 2410 --language ko
+our keywords ideas "<keyword>" --location 2410 --limit 50
+our keywords for-site <competitor.com> --location 2410 --limit 100
+our keywords intent "<kw1>" "<kw2>" "<kw3>"
+our keywords difficulty "<kw1>" "<kw2>"
+```
+
+**Ahrefs MCP (when user requests, or for GSC first-party):**
+```
+mcp__ahrefs__keywords-explorer-overview(keyword="<seed>", country="us")
+mcp__ahrefs__keywords-explorer-matching-terms(keyword="<seed>", country="us")
+mcp__ahrefs__keywords-explorer-volume-by-country(keyword="<seed>")
+mcp__ahrefs__gsc-keywords(...)
+```
+
+**OurSEO Agent MCP (Claude Desktop, KG/entity expansion):**
+```
+mcp__ourseo__search_knowledge_graph(query="<brand or entity>")
+mcp__ourseo__crawl_website(url="<target>", max_pages=50)
+```
+
+### Common parameters across backends
+
+| Concept | Semrush | Ahrefs | DataForSEO / `our` CLI |
+|---|---|---|---|
+| Korean market | `database="kr"` | `country="kr"` | `--location 2410` |
+| US market | `database="us"` | `country="us"` | `--location 2840` |
+| Japan | `database="jp"` | `country="jp"` | `--location 2392` |
+| Language | (database-bound) | (country-bound) | `--language ko`/`en`/`ja` |
+
+## Workflow
+
+### 1. Seed Keyword Expansion
+1. Determine backend via **Data Source Selection** above.
+2. Fetch search volume for the seed.
+3. Expand via the chosen backend's "related" / "ideas" / "matching-terms" endpoint.
+4. Apply Korean suffix expansion if Korean market (regardless of backend).
+5. Deduplicate and merge.
+
+### 2. Intent Classification & Clustering
+1. Classify each keyword by search intent (informational / navigational / commercial / transactional).
+2. Group keywords into topic clusters.
+3. Identify pillar topics and supporting terms.
+4. Calculate cluster-level metrics (total volume, avg KD).
+
+### 3. Gap Analysis
+1. Pull organic keywords for target via chosen backend.
+2. Pull organic keywords for competitors (parallel).
+3. Identify keywords present in competitors but missing from target.
+4. Score opportunities by volume/difficulty ratio.
+5. Prioritize by intent alignment with business goals.
+
+## Output Format
+
+```markdown
+## Keyword Strategy Report: [seed keyword]
+
+### Overview
+- Data source: [Semrush | Ahrefs | OurSEO CLI | OurSEO MCP | GSC]
+- Market: [database/location code]
+- Total keywords discovered: [count]
+- Topic clusters: [count]
+- Total search volume: [sum]
+
+### Top Clusters
+| Cluster | Keywords | Total Volume | Avg KD |
+|---|---|---|---|
+| ... | ... | ... | ... |
+
+### Top Opportunities
+| Keyword | Volume | KD | Intent | Cluster |
+|---|---|---|---|---|
+| ... | ... | ... | ... | ... |
+
+### Keyword Gaps (vs competitors)
+| Keyword | Volume | Competitor Position | Opportunity Score |
+|---|---|---|---|
+| ... | ... | ... | ... |
+```
+
+Always record the chosen data source in the **Overview** so future audits can compare apples to apples.
+
+## Notion Output (Required)
+
+All audit reports MUST be saved to OurDigital SEO Audit Log:
+- **Database ID**: `2c8581e5-8a1e-8035-880b-e38cefc2f3ef`
+- **Properties**: Issue (title), Site (url), Category, Priority, Found Date, Audit ID
+- **Language**: Korean with English technical terms
+- **Audit ID Format**: KW-YYYYMMDD-NNN

custom-skills/19-seo-keyword-strategy/desktop/SKILL.md

@@ -21,11 +21,41 @@ Expand seed keywords, classify search intent, cluster topics, and identify compe
 4. **Topic Clustering** - Group keywords into semantic clusters
 5. **Gap Analysis** - Find competitor keywords missing from target site
 
-## MCP Tool Usage
+## Data Source Selection
 
-### SEO Data (DataForSEO)
+This skill can pull keyword data from multiple backends. **Pick one per task** — don't fan out to every backend by default (cost + rate limits).
 
-**Primary — our-seo-agent CLI:**
+| Backend | Best for | Notes |
+|---|---|---|
+| **Semrush MCP** (`mcp__semrush__*`) | Default for keyword volume, related/matching terms, organic competitor pulls | Call pattern: `keyword_research` → `get_report_schema` → `execute_report`. `database="us"` default; `"kr"` for Korean market. |
+| **Ahrefs MCP** (`mcp__ahrefs__*`) | Ahrefs DR/UR weighting; first-party `gsc-keywords` (only Ahrefs integrates GSC inside its MCP) | `keywords-explorer-overview`, `-matching-terms`, `-related-terms`, `-search-suggestions`, `-volume-by-country`, `gsc-keywords`. |
+| **OurSEO Agent CLI** (`our keywords *`) | DataForSEO under the hood — cheapest per call, batch-friendly, Korean-aware via `--location 2410` | Claude Code only (needs Bash). Wrap calls: `our keywords volume`, `ideas`, `for-site`, `intent`, `difficulty`. |
+| **OurSEO Agent MCP** (`mcp__ourseo__*`) | Claude Desktop equivalent for crawl-derived keywords + Knowledge Graph entity expansion | `search_knowledge_graph` for entity seeding; `crawl_website` to extract on-page keyword inventory from the target site itself. |
+| **DataForSEO MCP** (`mcp__dfs-mcp__*`) | Direct fallback when `our` CLI isn't available | Same data as `our keywords *`. |
+| **GSC** (via `our research search-console` or Ahrefs `gsc-*`) | First-party queries the site actually ranks for — ground truth, not estimates | Use to validate/prune Semrush or Ahrefs lists with real impressions/CTR. |
+
+### How to pick
+
+Apply these in order; stop at the first match:
+
+1. **User named a backend explicitly** in the prompt → use it.
+2. **User preference memory** — read `feedback_seo_tool_preferences.md`; honor the task-type default there.
+3. **Task needs a capability only one backend has** (e.g., `gsc-keywords` first-party data, or `mcp__ourseo__search_knowledge_graph` entity expansion) → use that backend.
+4. **Default by market**:
+   - English-market or unspecified → **Semrush MCP** with `database="us"`.
+   - Korean market → **OurSEO CLI** `our keywords <subcmd> --location 2410 --language ko` (Claude Code), or **Semrush MCP** with `database="kr"` (Claude Desktop).
+5. **Still ambiguous on a non-trivial task** → ask once via `AskUserQuestion` listing the top 2–3 candidates.
+
+### Backend call patterns
+
+**Semrush MCP (default):**
+```
+mcp__semrush__keyword_research(query="<seed>", database="us")
+mcp__semrush__get_report_schema(report_id="...")
+mcp__semrush__execute_report(report_id="...", params={...})
+```
+
+**OurSEO CLI (Korean default, Claude Code):**
 ```bash
 our keywords volume "<keyword>" --location 2410 --language ko
 our keywords ideas "<keyword>" --location 2410 --limit 50
@@ -34,48 +64,50 @@ our keywords intent "<kw1>" "<kw2>" "<kw3>"
 our keywords difficulty "<kw1>" "<kw2>"
 ```
 
-**Interactive fallback — DataForSEO MCP:**
+**Ahrefs MCP (when user requests, or for GSC first-party):**
 ```
-mcp__dfs-mcp__dataforseo_labs_google_keyword_overview
+mcp__ahrefs__keywords-explorer-overview(keyword="<seed>", country="us")
-mcp__dfs-mcp__dataforseo_labs_google_keyword_ideas
+mcp__ahrefs__keywords-explorer-matching-terms(keyword="<seed>", country="us")
-mcp__dfs-mcp__dataforseo_labs_google_keyword_suggestions
+mcp__ahrefs__keywords-explorer-volume-by-country(keyword="<seed>")
-mcp__dfs-mcp__dataforseo_labs_search_intent
+mcp__ahrefs__gsc-keywords(...)
-mcp__dfs-mcp__dataforseo_labs_bulk_keyword_difficulty
-mcp__dfs-mcp__kw_data_google_ads_search_volume
-mcp__dfs-mcp__dataforseo_labs_google_keywords_for_site
 ```
 
-### Common Parameters
+**OurSEO Agent MCP (Claude Desktop, KG/entity expansion):**
-- **location_code**: 2410 (Korea), 2840 (US), 2392 (Japan)
+```
-- **language_code**: ko, en, ja
+mcp__ourseo__search_knowledge_graph(query="<brand or entity>")
+mcp__ourseo__crawl_website(url="<target>", max_pages=50)
+```
 
-### Web Search for Naver Discovery
+### Common parameters across backends
-```
+
-WebSearch: Naver autocomplete and trend discovery
+| Concept | Semrush | Ahrefs | DataForSEO / `our` CLI |
-```
+|---|---|---|---|
+| Korean market | `database="kr"` | `country="kr"` | `--location 2410` |
+| US market | `database="us"` | `country="us"` | `--location 2840` |
+| Japan | `database="jp"` | `country="jp"` | `--location 2392` |
+| Language | (database-bound) | (country-bound) | `--language ko`/`en`/`ja` |
 
 ## Workflow
 
 ### 1. Seed Keyword Expansion
-1. Input seed keyword (Korean or English)
+1. Determine backend via **Data Source Selection** above.
-2. Fetch search volume via `our keywords volume "<seed>" --location 2410 --language ko`
+2. Fetch search volume for the seed.
-3. Expand with `our keywords ideas "<seed>" --location 2410 --limit 50`
+3. Expand via the chosen backend's "related" / "ideas" / "matching-terms" endpoint.
-4. Get autocomplete suggestions via MCP: `mcp__dfs-mcp__dataforseo_labs_google_keyword_suggestions`
+4. Apply Korean suffix expansion if Korean market (regardless of backend).
-5. Apply Korean suffix expansion if Korean market
+5. Deduplicate and merge.
-6. Deduplicate and merge results
 
 ### 2. Intent Classification & Clustering
-1. Classify each keyword by search intent
+1. Classify each keyword by search intent (informational / navigational / commercial / transactional).
-2. Group keywords into topic clusters
+2. Group keywords into topic clusters.
-3. Identify pillar topics and supporting terms
+3. Identify pillar topics and supporting terms.
-4. Calculate cluster-level metrics (total volume, avg KD)
+4. Calculate cluster-level metrics (total volume, avg KD).
 
 ### 3. Gap Analysis
-1. Pull organic keywords for target: `our keywords for-site <target.com> --location 2410 --limit 100`
+1. Pull organic keywords for target via chosen backend.
-2. Pull organic keywords for competitors: `our keywords for-site <competitor.com> --location 2410 --limit 100`
+2. Pull organic keywords for competitors (parallel).
-3. Identify keywords present in competitors but missing from target
+3. Identify keywords present in competitors but missing from target.
-4. Score opportunities by volume/difficulty ratio
+4. Score opportunities by volume/difficulty ratio.
-5. Prioritize by intent alignment with business goals
+5. Prioritize by intent alignment with business goals.
 
 ## Output Format
 
@@ -83,26 +115,30 @@ WebSearch: Naver autocomplete and trend discovery
 ## Keyword Strategy Report: [seed keyword]
 
 ### Overview
+- Data source: [Semrush | Ahrefs | OurSEO CLI | OurSEO MCP | GSC]
+- Market: [database/location code]
 - Total keywords discovered: [count]
 - Topic clusters: [count]
 - Total search volume: [sum]
 
 ### Top Clusters
 | Cluster | Keywords | Total Volume | Avg KD |
-|---------|----------|-------------|--------|
+|---|---|---|---|
 | ... | ... | ... | ... |
 
 ### Top Opportunities
 | Keyword | Volume | KD | Intent | Cluster |
-|---------|--------|-----|--------|---------|
+|---|---|---|---|---|
 | ... | ... | ... | ... | ... |
 
 ### Keyword Gaps (vs competitors)
 | Keyword | Volume | Competitor Position | Opportunity Score |
-|---------|--------|-------------------|-------------------|
+|---|---|---|---|
 | ... | ... | ... | ... |
 ```
 
+Always record the chosen data source in the **Overview** so future audits can compare apples to apples.
+
 ## Notion Output (Required)
 
 All audit reports MUST be saved to OurDigital SEO Audit Log:

custom-skills/19-seo-keyword-strategy/desktop/skill.yaml

@@ -2,8 +2,17 @@ name: seo-keyword-strategy
 description: |
   Keyword strategy and research for SEO campaigns. Triggers: keyword research, keyword analysis, keyword gap, search volume, keyword clustering, intent classification.
 
+# Allowed tools list every backend the skill can pull keyword data from.
+# Per-task selection happens in SKILL.md > Data Source Selection — NOT here.
 allowed-tools:
-  - mcp__ahrefs__*
+  # SEO data backends
+  - mcp__semrush__*               # default for keyword/SERP/organic
+  - mcp__ahrefs__*                # Ahrefs (Claude Desktop namespace)
+  - mcp__claude_ai_Ahrefs__*      # Ahrefs (Claude.ai namespace) — same backend
+  - mcp__ourseo__*                # OurSEO Agent MCP (KG, crawl-derived keywords)
+  - mcp__dfs-mcp__*               # DataForSEO MCP fallback
+  - Bash                          # `our keywords *` CLI (Claude Code only)
+  # Output / supplementary
   - mcp__notion__*
   - WebSearch
   - WebFetch