Extract ourdigital-estimate-engine; presales-seo now calls it

New skill 96-ourdigital-estimate-engine: method-aware quoting engine
(effort / coaching / procurement) with universal rate_card + per-service
catalog. Real catalogs: seo (effort), education (coaching); stubs:
digital_ads, digital_branding. Validated to reproduce real quotes —
SEO basic ₩10.5M / treatment ₩25.0M, SHR chain ₩29.5M, L'Escape basic
₩10.5M, GA4/GTM coaching ₩1,570,000, procurement +15%.

Refactor 95-ourdigital-presales-seo: remove rate_card.yaml, sow_templates.yaml,
estimate.py (migrated to engine); add findings_to_scope.py; Stage 5 now maps
findings→scope.json and calls the engine CLI. build_deck/kg_query unchanged;
end-to-end validated on SHR (29.5M) + deck renders engine estimate.json.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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2026-05-28 01:54:11 +09:00
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# Design — `ourdigital-estimate-engine` skill
- **Status**: Approved design (2026-05-28). Implementing.
- **Origin**: Extracted from `ourdigital-presales-seo`'s estimate engine and generalized to
cover all OurDigital / D.intelligence professional services via multiple costing methods.
- **Source data**: real quotes in Google Drive `06_Working Template` (SEO) and `견적 자료`
(GA4/GTM, education). Company: (주)디인텔리전스 / D.intelligence Lab, info@ourdigital.org.
## 1. Purpose & scope
A reusable, **method-aware** estimate engine that produces OurDigital 견적 for any service
line. Consuming skills (e.g. `ourdigital-presales-seo`) map their context → a generic
`scope.json` and call the engine CLI. The engine owns the rate card + service catalog
(single source of truth).
### Costing methods (from real data)
1. **effort**`role_rate × billing_rate(0.70) × hours`, grouped into modules; tiering,
sub-brand scaling, premium-vertical floor, 절사. (SEO Audit & Treatment, etc.)
2. **coaching**`Σ(lesson_type_price × hours)` over a lesson plan, with student-count
discount. Base type prices reproduce real quotes; optional subject×level list-price
matrix (`base × level_multiple`). (GA4/GTM courses, workshops, education.)
3. **procurement**`unit_cost × qty × (1 + 0.15)` for non-labor items (tools, 3rd-party).
All methods share: cover-sheet output, 부가세 별도, 유효기간 14d, 현금, 십만 단위 미만 절사
(500k floor for project quotes), quote no `OD-YYYY-NNN`.
### Non-goals
- No invented rates. `digital_ads` / `digital_branding` ship as **effort stubs** (clearly
marked) until real quotes exist.
- No GA4/GTM *effort-implementation* catalog (delivered as coaching → a course in education).
- Does not replace consuming skills' domain logic (e.g. SEO findings→scope mapping stays in
presales-seo).
## 2. Structure
```
96-ourdigital-estimate-engine/
SKILL.md
references/
rate_card.yaml # UNIVERSAL pricing config (see §3)
catalog/
seo.yaml # method: effort — tiers smb/basic/treatment (real)
education.yaml # method: coaching — courses + per-subject levels (real)
digital_ads.yaml # method: effort — STUB
digital_branding.yaml # method: effort — STUB
scripts/
estimate.py # CLI dispatcher
methods/effort.py
methods/coaching.py
methods/procurement.py
render.py # md / xlsx / json output (cover-sheet)
scope.schema.json
```
## 3. `rate_card.yaml` (universal)
- `company`, `quote_prefix: OD`, `currency: KRW`, `rounding_unit: 500000`
- `terms`: vat 부가세 별도, validity_days 14, payment 현금
- **effort**: `billing_rate: 0.70` (floor 0.60), `basis {8h/day, 4wk/mo}`,
`procurement_markup: 0.15`, `role_rates {대표 180k … 과장 70k … 인턴 12k}`,
`tiering {premium_verticals, premium_min_tier}`, `scaling {driver: subbrands_total,
bands cap ×2.0}`, `tools`.
- **coaching**:
- `lesson_type_prices`: 화상 80,000 · 대면 100,000 · 실습 150,000 · 워크숍 300,000 · 트리트먼트 500,000
- `level_multiple`: Beginners 1.0 · Intermediate 1.5 · Advanced 2.0 · Expert 2.5 · Trainers 3.0
- `subject_levels`: {Content Marketing: Beginners, SEO: Beginners, Google Analytics: Intermediate,
Google Tag Manager: Advanced, Digital Marketing Strategy: Advanced, Digital Communication:
Intermediate, KPI Setup & Measurement Plan: Expert, Business Model Canvas: Expert,
e-Commerce Audit: Advanced}
- `pricing_mode: base` (default; reproduces real quotes) | `matrix` (list price = base×level_multiple)
- `student_discount_bands`: [[5,0.20],[10,0.0],[20,0.20],[30,0.30]] (30+ = 별도 협의)
## 4. Catalog entries
Each file: `service`, `method`, and method-specific body.
- **seo.yaml** (effort): the current `sow_templates.yaml` verbatim (tiers smb/basic/treatment,
modules→tasks with role/hours/scale). Validated to reproduce 10.5M/25.0M.
- **education.yaml** (coaching): `courses:` — named lesson plans, each `lessons: [{subject,
type, hours}]`. Seed with `ga4_gtm_intermediate` (the real 17-lesson, ₩1,570,000 plan) and
`ga4_gtm_marketing_analytics`. Subjects resolve levels from rate_card.subject_levels.
- **digital_ads.yaml / digital_branding.yaml** (effort): STUB — one placeholder tier +
`_stub: true`, with a header comment to populate from a real quote.
## 5. `scope.json` (generic input — `scope.schema.json`)
```jsonc
// effort
{"service":"seo","method":"effort","tier":"auto", // or smb|basic|treatment
"signals":{"properties_total":25,"subbrands_total":5,"vertical":"hotel_resort"},
"billing_rate":null, "seq":1, "prospect":{"name":"","audit_date":""}}
// coaching
{"service":"education","method":"coaching","course":"ga4_gtm_intermediate",
"students":1, "pricing_mode":"base", "prospect":{...}} // or "lessons":[{subject,type,hours}]
```
`tier:"auto"` → engine runs tiering (size + premium floor) from `signals`.
## 6. CLI
`python scripts/estimate.py --catalog-dir catalog --rate-card references/rate_card.yaml
--scope scope.json --out-dir <dir> [--seq N]`
- Dispatcher loads scope → catalog entry → method module → `render.py`.
- Outputs `05_estimate_ko.md`, `05_estimate.xlsx`, `data/estimate.json`.
- **effort `estimate.json` keeps the current shape** (modules + 제안가 + scope + terms) so
`ourdigital-presales-seo/build_deck.py` keeps working unchanged.
## 7. `ourdigital-presales-seo` refactor (consumption = CLI)
- **Move** `references/rate_card.yaml` + `references/sow_templates.yaml` → engine
(`catalog/seo.yaml`). Delete `scripts/estimate.py` from presales-seo.
- **Add** `scripts/findings_to_scope.py` (thin): findings.json → scope.json (tier signals,
vertical, prospect). Keeps SEO-specific mapping out of the engine.
- **Stage 5** in SKILL.md: `findings_to_scope.py` → call engine
`estimate.py --service seo --scope scope.json`.
- `build_deck.py`, `kg_query.py`, `render_pdf.sh`, `findings_to_service.md`,
`findings.schema.json`, templates → unchanged.
## 8. Validation (before commit)
- effort: SEO basic ₩10.5M, treatment ₩25.0M (1 property); SHR ₩29.5M; L'Escape `basic` ₩10.5M
— identical to pre-refactor.
- coaching: `ga4_gtm_intermediate` (17 lessons, 1 student) → **₩1,570,000** exactly.
- procurement: unit_cost × qty × 1.15 sanity check.
- presales-seo end-to-end: findings→scope→engine→견적 + deck reproduces SHR/L'Escape.
## 9. Future
Populate `digital_ads` / `digital_branding` from real quotes; add `content_marketing` as a
project-service if effort quotes emerge (currently a coaching subject); optional matrix-mode
quotes; more education courses.

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---
name: ourdigital-estimate-engine
description: Method-aware estimate/견적 engine for OurDigital / D.intelligence professional services (SEO, GA4/GTM, education/coaching, digital ads, branding, …). Generates a Korean 견적 (md/xlsx/json) from a generic scope.json using the real company rate card. Use for "OurDigital 견적", "estimate", "quote", "proposal pricing", "cost estimate", "견적서 생성", or when another skill needs to price a service. Costing methods: effort (role×billing×hours), coaching (lesson×hours), procurement (+15%).
---
# OurDigital Estimate Engine
Single source of truth for OurDigital/D.intelligence pricing. Consuming skills map their
context into a `scope.json` and call the engine CLI; the engine owns the rate card + service
catalog and renders the 견적.
## Costing methods (catalog entry declares its `method`)
- **effort** — `role_rate × 청구율(0.70) × 표준 업무시간`, by module; auto-tier (smb/basic/treatment)
by portfolio size + premium-vertical floor; On-page hours scale by sub-brands (cap ×2.0);
제안가 = 합계 절사. Reproduces real SEO quotes (basic ₩10.5M / treatment ₩25.0M).
- **coaching** — `Σ(lesson_type_price × hours)` over a lesson plan; student discount opt-in.
Reproduces real GA4/GTM 코칭 (₩1,570,000). Base prices default; subject×level matrix optional.
- **procurement** — `unit_cost × qty × (1 + 0.15)` for non-labor items.
## Files
- `references/rate_card.yaml` — universal: role rates, billing, basis, terms, tiering, scaling,
procurement, coaching prices/levels/discounts, tools. **Private.**
- `catalog/<service>.yaml` — per-service: `service`, `method`, body. Real: `seo` (effort),
`education` (coaching). Stubs: `digital_ads`, `digital_branding` (effort — `_stub: true`).
- `scripts/estimate.py` — CLI dispatcher; `scripts/methods/{effort,coaching,procurement}.py`;
`scripts/render.py` (md/xlsx/json). `scope.schema.json` — input contract.
## Usage
```
python scripts/estimate.py \
--rate-card references/rate_card.yaml --catalog-dir catalog \
--scope scope.json --out-dir <engagement> [--seq N]
```
`scope.json` examples (see `scope.schema.json`):
- effort: `{"service":"seo","tier":"auto","signals":{"properties_total":25,"subbrands_total":5,"vertical":"hotel_resort"},"prospect":{"name":"…","audit_date":"YYYY-MM-DD"}}`
- coaching: `{"service":"education","course":"ga4_gtm_intermediate","students":1,"prospect":{…}}`
- procurement: `{"service":"seo","method":"procurement","items":[{"label":"SEMrush Guru","unit_cost":330000,"qty":6}]}`
Outputs `05_estimate_ko.md`, `05_estimate.xlsx`, `data/estimate.json`. The effort `estimate.json`
shape is consumed by `ourdigital-presales-seo/build_deck.py`.
## Consuming from another skill (CLI)
1. Map your context → `scope.json` (service, tier signals or lessons, prospect).
2. Call `estimate.py`. 3. Use the rendered 견적; for SEO, feed `data/estimate.json` to the deck.
Example consumer: `ourdigital-presales-seo` (`findings_to_scope.py` → engine → 견적 + deck).
## Adding / editing services
- New real service: add `catalog/<service>.yaml` with `method` + body from a **real quote**.
- Stubs (`digital_ads`, `digital_branding`) carry `_stub: true` and placeholder hours — replace
with real quote data before client use (the 견적 prints a ⚠STUB banner).
- Rates change in `rate_card.yaml` only (single source). Validate against a known real quote.
## Conventions
Korean-first output · 부가세 별도 · 유효기간 14d · 현금 · `OD-YYYY-NNN`. Don't invent rates —
stub and flag instead. Legal entity (주)디인텔리전스 / info@ourdigital.org.

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# Digital Ads catalog — method: effort. STUB — placeholder hours, NOT real rates.
# TODO: populate tiers/modules/hours from a real OurDigital digital-ads quote (Drive),
# the same way seo.yaml was built. Until then estimates here are illustrative only.
service: digital_ads
method: effort
_stub: true
tiers:
basic:
label: "Digital Ads Setup & Management (STUB)"
modules:
- name: "Planning & Management"
tasks:
- {task: "캠페인 전략·계정 구조 설계", desc: "STUB — replace with real SOW", role: senior_manager, hours: 16, scale: false}
- name: "Ads Operation"
tasks:
- {task: "캠페인 셋업·태깅·전환 추적", desc: "STUB", role: manager, hours: 24, scale: false}
- {task: "운영·최적화·리포팅", desc: "STUB (월 운영)", role: manager, hours: 24, scale: true}

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# Digital Branding catalog — method: effort. STUB — placeholder hours, NOT real rates.
# TODO: populate from a real OurDigital digital-branding quote (Drive). Illustrative only.
service: digital_branding
method: effort
_stub: true
tiers:
basic:
label: "Digital Branding (STUB)"
modules:
- name: "Planning & Management"
tasks:
- {task: "브랜드 전략·포지셔닝", desc: "STUB — replace with real SOW", role: director, hours: 16, scale: false}
- name: "Branding Execution"
tasks:
- {task: "브랜드 아이덴티티·가이드", desc: "STUB", role: senior_manager, hours: 24, scale: false}
- {task: "디지털 자산·채널 적용", desc: "STUB", role: manager, hours: 24, scale: true}

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# Education / coaching catalog — method: coaching.
# Cost = Σ(lesson_type_prices[type] × hours) from rate_card.coaching (pricing_mode: base).
# Subjects resolve levels from rate_card.coaching.subject_levels (used only in matrix mode).
service: education
method: coaching
courses:
# Real quote: GA4/GTM 중급 과정 1:1 코칭 → ₩1,570,000 (7 대면×100k + 9 화상×80k + 1 실습×150k).
ga4_gtm_intermediate:
title: "GA4/GTM 중급 과정 1:1 코칭"
lessons:
- {subject: "Google Analytics", title: "설치-설정 진단", type: 대면, hours: 1}
- {subject: "Google Analytics", title: "측정 계획 수립", type: 대면, hours: 1}
- {subject: "Google Analytics", title: "기본 리포트 설정", type: 대면, hours: 1}
- {subject: "Google Analytics", title: "맞춤 리포트 구성", type: 대면, hours: 1}
- {subject: "Google Analytics", title: "획득 보고서의 이해", type: 화상, hours: 1}
- {subject: "Google Analytics", title: "참여도 보고서 해석", type: 화상, hours: 1}
- {subject: "Google Analytics", title: "수익창출 보고서 관리", type: 화상, hours: 1}
- {subject: "Google Analytics", title: "주요 이벤트와 전환", type: 화상, hours: 1}
- {subject: "Google Analytics", title: "탐색 분석 활용", type: 화상, hours: 1}
- {subject: "Google Tag Manager", title: "이벤트 태깅 관리 준비", type: 화상, hours: 1}
- {subject: "Google Tag Manager", title: "GTM 설정 분석과 검수", type: 대면, hours: 1}
- {subject: "Google Tag Manager", title: "이벤트 태깅 실습", type: 대면, hours: 1}
- {subject: "Google Tag Manager", title: "마케팅 태그 설정", type: 대면, hours: 1}
- {subject: "Google Tag Manager", title: "e-Commerce 태그 설정", type: 화상, hours: 1}
- {subject: "Google Analytics", title: "잠재 고객 설정과 활용", type: 화상, hours: 1}
- {subject: "Google Analytics", title: "캠페인 성과 분석", type: 화상, hours: 1}
- {subject: "Google Analytics", title: "Looker Studio 대시보드", type: 실습, hours: 1}
# Add more courses (workshops, SEO/Content Marketing coaching, etc.) as real lesson plans arrive.
# For an ad-hoc plan, pass scope.lessons directly instead of a named course.

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# SEO service catalog — method: effort. Tiers priced via rate_card (role×billing×hours).
# Reproduces real quotes: basic ₩10.5M, treatment ₩25.0M (1 property, billing 0.70).
# Only On-page tasks (scale:true) scale by sub-brands; Technical/P&M/Growth fixed.
service: seo
method: effort
tiers:
smb:
label: "SEO Quick Audit (SMB)"
billing_rate: 0.55
modules:
- name: "Planning & Management"
tasks:
- {task: "업무 관리·착수", desc: "과업 정의·일정·리포팅", role: senior_manager, hours: 8, scale: false}
- {task: "웹 사이트 분석", desc: "유입·행동·전환 flow 요약 분석", role: senior_manager, hours: 8, scale: false}
- name: "Technical SEO"
tasks:
- {task: "Crawling·Indexing 점검", desc: "검색사이트 등록·수집·Site Health 점검", role: manager, hours: 8, scale: false}
- {task: "속도·CWV 점검", desc: "로딩속도·Core Web Vitals·모바일 점검", role: manager, hours: 8, scale: false}
- {task: "구조·메타·사이트맵 점검", desc: "사이트/URL 구조·메타·사이트맵·색인", role: manager, hours: 8, scale: false}
- name: "On-page SEO"
tasks:
- {task: "키워드·메타 진단", desc: "중점 키워드·페이지 메타·템플릿 진단", role: manager, hours: 12, scale: true}
- {task: "on-page 퀵윈 가이드", desc: "타이틀·메타·헤더·링크·이미지 핵심 개선 가이드", role: manager, hours: 16, scale: true}
- name: "SEO Growth"
tasks:
- {task: "기본 성과 지표 설정", desc: "핵심 SEO 지표·중점 키워드 트래킹 설정", role: manager, hours: 8, scale: false}
basic:
label: "SEO Audit & Basic Treatment"
modules:
- name: "Planning & Management"
tasks:
- {task: "업무 관리", desc: "프로젝트 설계·과업 정의·일정/산출물 관리·리포팅", role: senior_manager, hours: 20, scale: false}
- {task: "웹 사이트 분석", desc: "사용자 유입·채널 내 행동·전환 flow 분석", role: senior_manager, hours: 12, scale: false}
- name: "Technical SEO"
tasks:
- {task: "Crawling & Indexing 설정", desc: "검색사이트 등록/수집 관리·Site Health Check 도구 설정", role: technical_advisor, hours: 16, scale: false}
- {task: "속도·UX·수집 설정", desc: "로딩속도·페이지 UX·링크·수집 제외 설정", role: manager, hours: 16, scale: false}
- {task: "사이트/URL 구조·메타", desc: "구조·URL·메타데이터·사이트맵·리다이렉션", role: senior_manager, hours: 12, scale: false}
- {task: "색인·CWV 진단", desc: "GSC·SEO Tools 활용 색인/크롤오류/Core Web Vitals 진단", role: senior_manager, hours: 16, scale: false}
- name: "On-page SEO"
tasks:
- {task: "키워드·템플릿·메타 진단", desc: "중점 키워드·페이지 템플릿·메타·개체 활용 진단", role: manager, hours: 24, scale: true}
- {task: "링크·콘텐츠 도구 진단", desc: "내외부 링크·공유 메타·콘텐츠 생성-관리 도구", role: manager, hours: 12, scale: true}
- {task: "on-page 관리 가이드", desc: "타이틀·메타·헤더태그·링크·이미지 메타 가이드", role: manager, hours: 36, scale: true}
- name: "SEO Growth"
tasks:
- {task: "성과 지표 관리", desc: "SEO 관리지표·중점 키워드·포지셔닝 트래킹·3rd party 데이터 설정", role: manager, hours: 24, scale: false}
treatment:
label: "SEO Audit & Treatment"
modules:
- name: "Planning & Management"
tasks:
- {task: "업무 관리", desc: "프로젝트 설계·과업 정의·일정/산출물 관리·리포팅", role: senior_manager, hours: 36, scale: false}
- {task: "웹 사이트 분석", desc: "사용자 유입·채널 내 행동·전환 flow 분석", role: senior_manager, hours: 60, scale: false}
- {task: "측정 계획 수립", desc: "채널 운영 목적·사용자 세그먼트·기대행동 가설 도출", role: senior_manager, hours: 20, scale: false}
- name: "Technical SEO"
tasks:
- {task: "Crawling & Indexing 설정", desc: "검색사이트 등록/수집 관리·Site Health Check 도구 설정", role: manager, hours: 24, scale: false}
- {task: "속도·UX·리다이렉트", desc: "로딩속도·페이지 UX·링크·리다이렉트·수집 제외 설정", role: technical_advisor, hours: 30, scale: false}
- {task: "사이트/URL 구조·보안", desc: "구조·URL·메타데이터·사이트맵·보안 관리 진단", role: senior_manager, hours: 24, scale: false}
- {task: "모바일·CWV·개선과제", desc: "모바일 최적화·Core Web Vitals 진단·개선 과제 도출", role: manager, hours: 20, scale: false}
- name: "On-page SEO"
tasks:
- {task: "키워드·템플릿·메타 진단", desc: "중점 키워드·페이지 템플릿·메타·개체 활용 진단", role: manager, hours: 48, scale: true}
- {task: "링크·콘텐츠 도구 진단", desc: "내외부 링크·공유 메타·콘텐츠 생성-관리 도구", role: manager, hours: 36, scale: true}
- {task: "on-page 관리 가이드", desc: "타이틀·메타·헤더태그·링크·이미지 메타 가이드", role: manager, hours: 60, scale: true}
- name: "SEO Growth"
tasks:
- {task: "핵심 성과 지표 설정", desc: "중점과제·목표·SEO 핵심성과지표·모니터링 지표 설정", role: senior_manager, hours: 20, scale: false}
- {task: "지표 정의·리포팅 설계", desc: "데이터 소스·지표 산식·리포팅/진단 주기 설정", role: manager, hours: 16, scale: false}
- {task: "성과 대시보드 지표", desc: "관리 지표·중점 키워드·포지셔닝 트래킹·3rd party 데이터", role: manager, hours: 20, scale: false}
- {task: "GSC 대시보드·파이프라인", desc: "GSC 대시보드 구성·연관 데이터 파이프라인 구축", role: manager, hours: 36, scale: false}

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# OurDigital / D.intelligence — UNIVERSAL rate card (shared across all service lines).
# Methods: effort (role×billing×hours), coaching (lesson_type×hours), procurement (+15%).
# Source: real quotes (06_Working Template = SEO; 견적 자료 = GA4/GTM, education). Keep PRIVATE.
company:
legal_name: "(주)디인텔리전스 (D.intelligence Lab)"
brand: "OurDigital"
ceo: "임명재"
contact: "info@ourdigital.org"
address: "경기도 성남시 수정구 창업로 43 판교글로벌비즈센터 업무동 1층 128호"
quote_prefix: OD
currency: KRW
rounding_unit: 500000 # 제안가 절사 단위(효과 기반 프로젝트 견적). 실제 견적 25,340,000→25,000,000 재현.
terms:
vat: "부가세 별도"
validity_days: 14
payment: "현금"
# ── effort method (project services: SEO Audit & Treatment 등) ──────────────
billing_rate: 0.70 # 청구율 표준 70%
billing_rate_floor: 0.60 # 협상 시 -10%p 까지(>10%p 는 CEO/CFO 승인)
basis: {hours_per_day: 8, weeks_per_month: 4}
procurement_markup: 0.15 # 외부 조달 물품/서비스 수수료
role_rates: # 시간 단가 KRW/hr (직급 기준)
ceo: 180000
evp: 150000
svp: 120000
technical_advisor: 120000
director: 100000
senior_manager: 90000 # 부장 (Senior SEO·PM·Senior Analyst·Account Director)
deputy_manager: 80000 # 차장
manager: 70000 # 과장 (SEO·Data Analyst·Engineer|Developer)
assistant_manager: 60000 # 대리
junior: 50000 # 주임
associate: 30000 # 사원
intern: 12000
tiering: # 자동 티어 선택 보정(effort 카탈로그가 tier 를 가질 때)
premium_verticals: ["luxury", "premium", "deluxe", "5_star", "5성", "특1급", "boutique_luxury"]
premium_min_tier: basic # 프리미엄 단일 프로퍼티 최소 티어
scaling: # On-page(scale:true) 시간 스케일 — 브랜드/템플릿 수 기준, 캡 ×2.0
driver: subbrands_total
bands: [[1, 1.0], [3, 1.3], [6, 1.6], [999999, 2.0]]
tools:
semrush_guru: {label: "Advanced SEO Tools — SEMrush Guru", unit: "월간 구독", price_usd: 249.95, note: "고객사 별도 구독(TBD)"}
# ── coaching method (education: 1:1 코칭, 워크숍) ────────────────────────────
# 실제 견적 재현: 비용 = Σ(lesson_type_prices[type] × hours). subject 행렬은 base×level_multiple
# (list price) 이나 실제 견적은 base 가격으로 청구되므로 pricing_mode 기본값 base.
coaching:
pricing_mode: base # base | matrix
lesson_type_prices: {화상: 80000, 대면: 100000, 실습: 150000, 워크숍: 300000, 트리트먼트: 500000}
level_multiple: {Beginners: 1.0, Intermediate: 1.5, Advanced: 2.0, Expert: 2.5, Trainers: 3.0}
subject_levels: # matrix 모드에서 subject×type 단가 = base × level_multiple[level]
"Content Marketing": Beginners
"SEO": Beginners
"Google Analytics": Intermediate
"Google Tag Manager": Advanced
"Digital Marketing Strategy": Advanced
"Digital Communication": Intermediate
"KPI Setup & Measurement Plan": Expert
"Business Model Canvas": Expert
"e-Commerce Audit": Advanced
student_discount:
apply_default: false # 실제 1:1 견적은 할인 미적용 → 기본 off (opt-in)
bands: [[5, 0.20], [10, 0.0], [20, 0.20], [30, 0.30]] # 30+ = 별도 협의

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{
"$schema": "http://json-schema.org/draft-07/schema#",
"title": "ourdigital-estimate-engine scope input",
"description": "Generic estimate request. Consuming skills map their context into this.",
"type": "object",
"required": ["service"],
"properties": {
"service": {"type": "string", "description": "catalog entry name, e.g. seo | education | digital_ads"},
"method": {"type": "string", "enum": ["effort", "coaching", "procurement"], "description": "optional; defaults to the catalog entry's method"},
"prospect": {
"type": "object",
"properties": {
"name": {"type": "string"}, "domain": {"type": "string"},
"audit_date": {"type": "string"}, "account_code": {"type": "string"}
}
},
"seq": {"type": "integer", "default": 1},
"tier": {"type": "string", "description": "effort: smb|basic|treatment|auto (default auto)"},
"billing_rate": {"type": ["number", "null"], "description": "effort: override billing rate"},
"signals": {
"type": "object",
"description": "effort auto-tiering inputs",
"properties": {
"properties_total": {"type": "integer"},
"subbrands_total": {"type": "integer"},
"vertical": {"type": "string"},
"severity": {"type": "array", "items": {"type": "string"}}
}
},
"course": {"type": "string", "description": "coaching: named course in catalog (else use lessons)"},
"lessons": {
"type": "array",
"description": "coaching: explicit lesson plan",
"items": {
"type": "object",
"required": ["type", "hours"],
"properties": {
"subject": {"type": "string"}, "title": {"type": "string"},
"type": {"type": "string", "enum": ["화상", "대면", "실습", "워크숍", "트리트먼트"]},
"hours": {"type": "number"}
}
}
},
"students": {"type": "integer", "default": 1},
"pricing_mode": {"type": "string", "enum": ["base", "matrix"]},
"apply_student_discount": {"type": "boolean"},
"items": {
"type": "array",
"description": "procurement: non-labor line items",
"items": {
"type": "object",
"required": ["label", "unit_cost"],
"properties": {
"label": {"type": "string"}, "unit_cost": {"type": "number"},
"qty": {"type": "number", "default": 1}, "currency": {"type": "string"}
}
}
}
}
}

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#!/usr/bin/env python3
"""OurDigital estimate engine — method-aware 견적 generator (CLI dispatcher).
Loads a generic scope.json + the universal rate_card + the service catalog entry,
routes to the costing method (effort | coaching | procurement), enriches with
quote metadata/terms, and renders 05_estimate_ko.md / .xlsx / data/estimate.json.
Usage:
python estimate.py --rate-card references/rate_card.yaml --catalog-dir catalog \
--scope scope.json --out-dir <dir> [--seq N]
scope.json: see scope.schema.json. Consuming skills (e.g. ourdigital-presales-seo)
map their context into scope.json and call this CLI.
"""
import argparse
import datetime
import json
import os
import sys
import yaml
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from methods import coaching, effort, procurement # noqa: E402
import render # noqa: E402
METHODS = {"effort": effort, "coaching": coaching, "procurement": procurement}
DISCLAIMER = {
"effort": ("본 견적은 공개/사전 정보 기반 추정이며 표준 업무시간(SOW)·청구율 {billing}% 기준입니다. "
"권한 확보 후 정밀 진단을 통해 과업 시간과 범위를 확정합니다. 외부 조달 항목은 인력비와 별도, 조달 수수료 15%가 적용될 수 있습니다."),
"coaching": ("본 견적은 레슨 시간 기준으로 작성되었으며(대면 100,000원/h, 화상 80,000원/h 등), 1:1 레슨 전제입니다. "
"그룹 레슨·단체 워크숍/실습은 별도 협의가 필요합니다. 수업 구성은 사전상담으로 맞춤 조율됩니다."),
"procurement": "조달 물품/서비스 견적이며 조달-관리 수수료 15%를 포함합니다. 실제 공급가는 계약 시점에 확정됩니다.",
}
def main():
ap = argparse.ArgumentParser(description="OurDigital estimate engine")
ap.add_argument("--rate-card", required=True)
ap.add_argument("--catalog-dir", required=True)
ap.add_argument("--scope", required=True)
ap.add_argument("--out-dir", default=".")
ap.add_argument("--seq", type=int, default=None)
args = ap.parse_args()
with open(args.rate_card, encoding="utf-8") as fh:
rate = yaml.safe_load(fh)
with open(args.scope, encoding="utf-8") as fh:
scope = json.load(fh)
service = scope["service"]
cat_path = os.path.join(args.catalog_dir, f"{service}.yaml")
if not os.path.exists(cat_path):
sys.exit(f"ERROR: no catalog for service '{service}' at {cat_path}")
with open(cat_path, encoding="utf-8") as fh:
catalog = yaml.safe_load(fh)
method = scope.get("method") or catalog.get("method")
if method not in METHODS:
sys.exit(f"ERROR: unknown method '{method}' (have {list(METHODS)})")
q = METHODS[method].build(scope, rate, catalog)
# enrich with universal metadata
prospect = scope.get("prospect", {})
date = prospect.get("audit_date") or datetime.date.today().isoformat()
d0 = datetime.date.fromisoformat(date)
seq = args.seq if args.seq is not None else scope.get("seq", 1)
q.update({
"quote_no": f"{rate.get('quote_prefix', 'OD')}-{date[:4]}-{seq:03d}",
"date": date,
"valid_until": (d0 + datetime.timedelta(days=rate["terms"]["validity_days"])).isoformat(),
"prospect": prospect, "company": rate["company"], "terms": rate["terms"],
"disclaimer": DISCLAIMER[method].format(billing=int(q.get("billing_rate", rate["billing_rate"]) * 100)),
})
render.write_all(q, args.out_dir)
print(f"견적 {q['quote_no']} [{service}/{method}"
+ (f"/{q['tier']}" if q['kind'] == 'effort' else "")
+ f"] 제안가 {q['proposal']:,}원 (합계 {int(round(q['subtotal_sum'])):,}원)"
+ (" ⚠STUB" if q.get("stub") else ""))
if __name__ == "__main__":
main()

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# estimate-engine costing methods: effort, coaching, procurement.

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"""Coaching method: cost = Σ(lesson_type_price × hours) over a lesson plan.
Base lesson-type prices reproduce real quotes (GA4/GTM 중급 → ₩1,570,000).
Optional matrix mode prices by subject level (base × level_multiple).
Student-count discount is opt-in (real 1:1 quotes apply none).
"""
def _discount(rate, students, apply):
if not apply:
return 0.0
for mx, r in rate["coaching"]["student_discount"]["bands"]:
if students <= mx:
return float(r)
return 0.0 # 30+ → 별도 협의
def _unit_price(rate, lesson, mode):
c = rate["coaching"]
base = c["lesson_type_prices"][lesson["type"]]
if mode == "matrix":
lvl = c.get("subject_levels", {}).get(lesson.get("subject"))
if lvl:
base = base * c["level_multiple"].get(lvl, 1.0)
return base
def build(scope, rate, catalog):
c = rate["coaching"]
mode = scope.get("pricing_mode") or c.get("pricing_mode", "base")
if scope.get("lessons"):
lessons = scope["lessons"]
title = scope.get("course") or "맞춤 코칭"
else:
cname = scope.get("course")
courses = catalog.get("courses", {})
if cname not in courses:
raise SystemExit(f"course '{cname}' not in catalog {list(courses)}")
lessons = courses[cname]["lessons"]
title = courses[cname].get("title", cname)
items, subtotal = [], 0.0
for L in lessons:
up = _unit_price(rate, L, mode)
amt = up * L["hours"]
items.append({"subject": L.get("subject", ""), "title": L.get("title", ""),
"type": L["type"], "hours": L["hours"], "unit_price": up, "amount": amt})
subtotal += amt
students = scope.get("students", 1)
apply = scope.get("apply_student_discount", c["student_discount"]["apply_default"])
disc = _discount(rate, students, apply)
disc_amt = subtotal * disc
total = subtotal - disc_amt
return {
"kind": "coaching", "service": catalog["service"], "label": title,
"pricing_mode": mode, "students": students,
"discount_rate": disc, "discount_amount": disc_amt,
"lessons": items, "subtotal_sum": subtotal, "proposal": int(round(total)),
"stub": bool(catalog.get("_stub", False)),
}

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"""Effort method: cost = role_rate × billing_rate × hours, grouped by module.
Tier auto-selection (size + premium-vertical floor) and sub-brand hours scaling
are driven by rate_card config. Reproduces real SEO quotes (10.5M/25.0M).
"""
import math
TIER_ORDER = {"smb": 0, "basic": 1, "treatment": 2}
def _higher(a, b):
return a if TIER_ORDER.get(a, 0) >= TIER_ORDER.get(b, 0) else b
def _is_premium(signals, rate):
v = (signals.get("vertical") or "").lower()
return any(t.lower() in v for t in rate.get("tiering", {}).get("premium_verticals", []))
def _scope_mult(rate, signals):
sc = rate.get("scaling", {})
driver = sc.get("driver", "subbrands_total")
bands = sc.get("bands", [[1, 1.0]])
count = max(int(signals.get(driver, 0) or 0), 1)
for mx, m in bands:
if count <= mx:
return float(m), driver, count
return float(bands[-1][1]), driver, count
def _pick_tier(signals, rate, available):
props = signals.get("properties_total", 0) or 0
subs = signals.get("subbrands_total", 0) or 0
if props > 5 or subs > 3:
tier = "treatment"
elif props <= 1 and subs == 0:
tier = "smb"
else:
tier = "basic"
if _is_premium(signals, rate):
tier = _higher(tier, rate.get("tiering", {}).get("premium_min_tier", "basic"))
if tier not in available:
tier = "basic" if "basic" in available else sorted(available, key=lambda t: TIER_ORDER.get(t, 9))[0]
return tier
def build(scope, rate, catalog):
tiers = catalog["tiers"]
signals = scope.get("signals", {})
tier = scope.get("tier") or "auto"
if tier == "auto":
tier = _pick_tier(signals, rate, set(tiers))
if tier not in tiers:
raise SystemExit(f"tier '{tier}' not in catalog tiers {list(tiers)}")
t = tiers[tier]
billing = scope.get("billing_rate") or t.get("billing_rate") or rate["billing_rate"]
mult, driver, dcount = _scope_mult(rate, signals)
roles = rate["role_rates"]
modules, grand = [], 0.0
for mod in t["modules"]:
tasks, sub = [], 0.0
for task in mod["tasks"]:
applied = mult if (task.get("scale") and mult != 1.0) else 1.0
hours = round(task["hours"] * applied, 1)
rr = roles[task["role"]]
amt = rr * billing * hours
tasks.append({"task": task["task"], "desc": task.get("desc", ""), "role": task["role"],
"role_rate": rr, "hours": hours, "amount": amt, "scaled": applied != 1.0})
sub += amt
modules.append({"name": mod["name"], "subtotal": sub, "tasks": tasks})
grand += sub
rounding = rate["rounding_unit"]
proposal = int(math.floor(grand / rounding) * rounding)
return {
"kind": "effort", "service": catalog["service"], "label": t.get("label", catalog["service"]),
"tier": tier, "billing_rate": billing,
"scope": {"driver": driver, "driver_count": dcount,
"properties_total": signals.get("properties_total", 0),
"subbrands_total": signals.get("subbrands_total", 0), "hours_multiplier": mult},
"modules": modules, "subtotal_sum": grand, "proposal": proposal,
"rounding_unit": rounding, "stub": bool(catalog.get("_stub", False)),
}

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"""Procurement method: cost = Σ(unit_cost × qty × (1 + markup)) for non-labor items."""
def build(scope, rate, catalog):
markup = rate.get("procurement_markup", 0.15)
items, total = [], 0.0
for it in scope.get("items", []):
qty = it.get("qty", 1)
amt = it["unit_cost"] * qty * (1 + markup)
items.append({"label": it["label"], "unit_cost": it["unit_cost"], "qty": qty,
"markup": markup, "amount": amt, "currency": it.get("currency", "KRW")})
total += amt
return {
"kind": "procurement", "service": catalog.get("service", "procurement"),
"label": "조달 항목 (Buying & Supplying)", "markup": markup,
"items": items, "subtotal_sum": total, "proposal": int(round(total)),
"stub": bool(catalog.get("_stub", False)),
}

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"""Render an enriched quote dict to 05_estimate_ko.md, 05_estimate.xlsx, data/estimate.json.
Handles all kinds: effort (modules), coaching (lessons), procurement (items)."""
import json
import os
from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill
ROLE_KO = {"ceo": "대표", "evp": "전무", "svp": "상무", "technical_advisor": "기술고문",
"director": "이사", "senior_manager": "부장", "deputy_manager": "차장",
"manager": "과장", "assistant_manager": "대리", "junior": "주임",
"associate": "사원", "intern": "인턴"}
NAVY = "11243D"
def won(n):
return f"{int(round(n)):,}"
def _header_md(q):
svc = q.get("label", q["service"])
if q["kind"] == "effort":
svc += f" ({q['tier']})"
L = [f"# 견적서 — {q['prospect'].get('name', '(prospect)')}", "",
f"- **제공 서비스**: {svc}",
f"- **견적번호**: {q['quote_no']} · **작성일**: {q['date']} · **유효기간**: ~{q['valid_until']}",
f"- **공급자**: {q['company']['legal_name']} (대표 {q['company']['ceo']}, {q['company']['contact']})"]
if q.get("stub"):
L.append("- ⚠️ **STUB 카탈로그** — 실제 단가 미반영(placeholder). 실제 견적 자료로 교체 필요.")
L.append("")
return L
def _md(q, path):
L = _header_md(q)
if q["kind"] == "effort":
if q["scope"]["hours_multiplier"] != 1.0:
dl = "브랜드/템플릿" if q["scope"]["driver"] == "subbrands_total" else "프로퍼티"
L += [f"> 규모 반영: {dl} {q['scope']['driver_count']}개 기준 On-page 업무시간 ×{q['scope']['hours_multiplier']:g}", ""]
L += ["## 견적 내역", "", "| 구분 | 세부 업무 | 담당 | 시간(h) | 합계 |", "|---|---|:--:|--:|--:|"]
for m in q["modules"]:
for i, t in enumerate(m["tasks"]):
grp = m["name"] if i == 0 else ""
mark = " *" if t["scaled"] else ""
L.append(f"| {grp} | {t['task']}{mark} | {ROLE_KO.get(t['role'], t['role'])} | {t['hours']:g} | {won(t['amount'])} |")
L.append(f"| | **{m['name']} 소계** | | | **{won(m['subtotal'])}** |")
L += ["", f"- 합계: **{won(q['subtotal_sum'])}** · 청구율 {int(q['billing_rate']*100)}% · 일8h/월4주",
f"- **제안가(절사 적용): {won(q['proposal'])}** ({q['terms']['vat']})"]
elif q["kind"] == "coaching":
L += ["## 견적 내역", "", "| 구분 | 세부 | 방식 | 시간 | 단가 | 합계 |", "|---|---|:--:|--:|--:|--:|"]
for it in q["lessons"]:
L.append(f"| {it['subject']} | {it['title']} | {it['type']} | {it['hours']:g} | {won(it['unit_price'])} | {won(it['amount'])} |")
L += ["", f"- 합계: **{won(q['subtotal_sum'])}** ({q['pricing_mode']} 단가, 수강생 {q['students']}명)"]
if q["discount_rate"]:
L.append(f"- 할인({int(q['discount_rate']*100)}%): -{won(q['discount_amount'])}")
L.append(f"- **제안가: {won(q['proposal'])}** ({q['terms']['vat']})")
elif q["kind"] == "procurement":
L += ["## 조달 내역", "", "| 항목 | 단가 | 수량 | 수수료 | 합계 |", "|---|--:|--:|:--:|--:|"]
for it in q["items"]:
L.append(f"| {it['label']} | {it['unit_cost']:,}{it['currency']} | {it['qty']:g} | {int(it['markup']*100)}% | {won(it['amount'])} |")
L += ["", f"- **합계: {won(q['proposal'])}** ({q['terms']['vat']})"]
L += ["", "---", f"> {q['disclaimer']}"]
if q["kind"] == "effort" and any(t["scaled"] for m in q["modules"] for t in m["tasks"]):
L.append("> \\* 포트폴리오 규모에 따라 업무시간이 스케일된 항목.")
with open(path, "w", encoding="utf-8") as fh:
fh.write("\n".join(L) + "\n")
def _xlsx(q, path):
wb = Workbook()
ws = wb.active
ws.title = "견적"
ws.append([f"견적서 — {q['prospect'].get('name', '(prospect)')} ({q.get('label', q['service'])})"])
ws.append([f"견적번호 {q['quote_no']}", f"작성일 {q['date']}", f"유효 ~{q['valid_until']}", q["terms"]["vat"]])
ws.append([])
def hdr(cols):
ws.append(cols)
for c in range(1, len(cols) + 1):
cell = ws.cell(row=ws.max_row, column=c)
cell.fill = PatternFill("solid", fgColor=NAVY)
cell.font = Font(color="FFFFFF", bold=True)
if q["kind"] == "effort":
hdr(["구분", "세부 업무", "담당", "시간(h)", "합계(원)"])
for m in q["modules"]:
for i, t in enumerate(m["tasks"]):
ws.append([m["name"] if i == 0 else "", t["task"], ROLE_KO.get(t["role"], t["role"]), t["hours"], int(round(t["amount"]))])
ws.append(["", f"{m['name']} 소계", "", "", int(round(m["subtotal"]))])
ws.append([])
ws.append(["", "제안가(절사 적용)", "", "", int(q["proposal"])])
widths = [22, 40, 8, 8, 16]
elif q["kind"] == "coaching":
hdr(["구분", "세부", "방식", "시간", "단가", "합계(원)"])
for it in q["lessons"]:
ws.append([it["subject"], it["title"], it["type"], it["hours"], int(it["unit_price"]), int(round(it["amount"]))])
ws.append([])
ws.append(["", "제안가", "", "", "", int(q["proposal"])])
widths = [18, 34, 8, 6, 12, 14]
else: # procurement
hdr(["항목", "단가", "수량", "수수료", "합계(원)"])
for it in q["items"]:
ws.append([it["label"], it["unit_cost"], it["qty"], it["markup"], int(round(it["amount"]))])
ws.append([])
ws.append(["", "합계", "", "", int(q["proposal"])])
widths = [34, 14, 8, 10, 16]
ws.cell(row=ws.max_row, column=2).font = Font(bold=True)
ws.cell(row=ws.max_row, column=len(widths)).font = Font(bold=True, color="C0392B")
ws.append([])
ws.append([q["disclaimer"]])
for idx, w in enumerate(widths, 1):
ws.column_dimensions[chr(64 + idx)].width = w
wb.save(path)
def write_all(q, out_dir):
os.makedirs(out_dir, exist_ok=True)
ddir = os.path.join(out_dir, "data")
os.makedirs(ddir, exist_ok=True)
with open(os.path.join(ddir, "estimate.json"), "w", encoding="utf-8") as fh:
json.dump(q, fh, ensure_ascii=False, indent=2)
_md(q, os.path.join(out_dir, "05_estimate_ko.md"))
_xlsx(q, os.path.join(out_dir, "05_estimate.xlsx"))