Andrew Yim
08cb20fc67
Built from real D.intelligence docs (not the 견적 자료 folder, which has only GA4/GTM + education — confirmed): - digital_branding: TNS 유학원 디지털 브랜딩 진단 컨설팅 → ₩9,000,000 (5 fixed stages) - digital_ads: 디하이브 디지털 광고·퍼포먼스 마케팅 대행 계약 → ₩6,000,000/월 retainer (media-spend commission % is per-deal, kept as a parameter — not invented) effort method now supports fixed-amount tasks (Unit Cost) and monthly retainers (unit: monthly); render shows 고정/—//월 and retainer/commission notes. Validated: branding ₩9.0M, ads ₩6.0M/월; no regression (SEO 25.0M, coaching 1.57M). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
122 lines
6.9 KiB
Markdown
122 lines
6.9 KiB
Markdown
# Design — `ourdigital-estimate-engine` skill
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- **Status**: Approved design (2026-05-28). Implementing.
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- **Origin**: Extracted from `ourdigital-presales-seo`'s estimate engine and generalized to
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cover all OurDigital / D.intelligence professional services via multiple costing methods.
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- **Source data**: real quotes in Google Drive `06_Working Template` (SEO) and `견적 자료`
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(GA4/GTM, education). Company: (주)디인텔리전스 / D.intelligence Lab, info@ourdigital.org.
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## 1. Purpose & scope
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A reusable, **method-aware** estimate engine that produces OurDigital 견적 for any service
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line. Consuming skills (e.g. `ourdigital-presales-seo`) map their context → a generic
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`scope.json` and call the engine CLI. The engine owns the rate card + service catalog
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(single source of truth).
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### Costing methods (from real data)
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1. **effort** — `role_rate × billing_rate(0.70) × hours`, grouped into modules; tiering,
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sub-brand scaling, premium-vertical floor, 절사. (SEO Audit & Treatment, etc.)
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2. **coaching** — `Σ(lesson_type_price × hours)` over a lesson plan, with student-count
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discount. Base type prices reproduce real quotes; optional subject×level list-price
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matrix (`base × level_multiple`). (GA4/GTM courses, workshops, education.)
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3. **procurement** — `unit_cost × qty × (1 + 0.15)` for non-labor items (tools, 3rd-party).
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All methods share: cover-sheet output, 부가세 별도, 유효기간 14d, 현금, 십만 단위 미만 절사
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(500k floor for project quotes), quote no `OD-YYYY-NNN`.
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### Non-goals
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- No invented rates. `digital_ads` / `digital_branding` are built from real docs (디하이브 ads
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대행 계약, TNS 브랜딩 진단 견적); any future service without real data ships as a flagged stub.
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- No GA4/GTM *effort-implementation* catalog (delivered as coaching → a course in education).
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- Does not replace consuming skills' domain logic (e.g. SEO findings→scope mapping stays in
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presales-seo).
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## 2. Structure
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```
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96-ourdigital-estimate-engine/
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SKILL.md
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references/
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rate_card.yaml # UNIVERSAL pricing config (see §3)
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catalog/
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seo.yaml # method: effort — tiers smb/basic/treatment (real)
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education.yaml # method: coaching — courses + per-subject levels (real)
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digital_ads.yaml # method: effort — REAL (₩6.0M/월 retainer + per-deal media commission)
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digital_branding.yaml # method: effort — REAL (fixed 진단 stages → ₩9.0M)
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scripts/
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estimate.py # CLI dispatcher
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methods/effort.py
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methods/coaching.py
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methods/procurement.py
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render.py # md / xlsx / json output (cover-sheet)
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scope.schema.json
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```
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## 3. `rate_card.yaml` (universal)
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- `company`, `quote_prefix: OD`, `currency: KRW`, `rounding_unit: 500000`
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- `terms`: vat 부가세 별도, validity_days 14, payment 현금
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- **effort**: `billing_rate: 0.70` (floor 0.60), `basis {8h/day, 4wk/mo}`,
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`procurement_markup: 0.15`, `role_rates {대표 180k … 과장 70k … 인턴 12k}`,
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`tiering {premium_verticals, premium_min_tier}`, `scaling {driver: subbrands_total,
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bands cap ×2.0}`, `tools`.
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- **coaching**:
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- `lesson_type_prices`: 화상 80,000 · 대면 100,000 · 실습 150,000 · 워크숍 300,000 · 트리트먼트 500,000
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- `level_multiple`: Beginners 1.0 · Intermediate 1.5 · Advanced 2.0 · Expert 2.5 · Trainers 3.0
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- `subject_levels`: {Content Marketing: Beginners, SEO: Beginners, Google Analytics: Intermediate,
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Google Tag Manager: Advanced, Digital Marketing Strategy: Advanced, Digital Communication:
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Intermediate, KPI Setup & Measurement Plan: Expert, Business Model Canvas: Expert,
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e-Commerce Audit: Advanced}
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- `pricing_mode: base` (default; reproduces real quotes) | `matrix` (list price = base×level_multiple)
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- `student_discount_bands`: [[5,0.20],[10,0.0],[20,0.20],[30,0.30]] (30+ = 별도 협의)
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## 4. Catalog entries
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Each file: `service`, `method`, and method-specific body.
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- **seo.yaml** (effort): the current `sow_templates.yaml` verbatim (tiers smb/basic/treatment,
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modules→tasks with role/hours/scale). Validated to reproduce 10.5M/25.0M.
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- **education.yaml** (coaching): `courses:` — named lesson plans, each `lessons: [{subject,
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type, hours}]`. Seed with `ga4_gtm_intermediate` (the real 17-lesson, ₩1,570,000 plan) and
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`ga4_gtm_marketing_analytics`. Subjects resolve levels from rate_card.subject_levels.
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- **digital_ads.yaml / digital_branding.yaml** (effort): STUB — one placeholder tier +
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`_stub: true`, with a header comment to populate from a real quote.
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## 5. `scope.json` (generic input — `scope.schema.json`)
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```jsonc
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// effort
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{"service":"seo","method":"effort","tier":"auto", // or smb|basic|treatment
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"signals":{"properties_total":25,"subbrands_total":5,"vertical":"hotel_resort"},
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"billing_rate":null, "seq":1, "prospect":{"name":"","audit_date":""}}
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// coaching
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{"service":"education","method":"coaching","course":"ga4_gtm_intermediate",
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"students":1, "pricing_mode":"base", "prospect":{...}} // or "lessons":[{subject,type,hours}]
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```
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`tier:"auto"` → engine runs tiering (size + premium floor) from `signals`.
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## 6. CLI
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`python scripts/estimate.py --catalog-dir catalog --rate-card references/rate_card.yaml
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--scope scope.json --out-dir <dir> [--seq N]`
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- Dispatcher loads scope → catalog entry → method module → `render.py`.
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- Outputs `05_estimate_ko.md`, `05_estimate.xlsx`, `data/estimate.json`.
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- **effort `estimate.json` keeps the current shape** (modules + 제안가 + scope + terms) so
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`ourdigital-presales-seo/build_deck.py` keeps working unchanged.
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## 7. `ourdigital-presales-seo` refactor (consumption = CLI)
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- **Move** `references/rate_card.yaml` + `references/sow_templates.yaml` → engine
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(`catalog/seo.yaml`). Delete `scripts/estimate.py` from presales-seo.
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- **Add** `scripts/findings_to_scope.py` (thin): findings.json → scope.json (tier signals,
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vertical, prospect). Keeps SEO-specific mapping out of the engine.
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- **Stage 5** in SKILL.md: `findings_to_scope.py` → call engine
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`estimate.py --service seo --scope scope.json`.
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- `build_deck.py`, `kg_query.py`, `render_pdf.sh`, `findings_to_service.md`,
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`findings.schema.json`, templates → unchanged.
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## 8. Validation (before commit)
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- effort: SEO basic ₩10.5M, treatment ₩25.0M (1 property); SHR ₩29.5M; L'Escape `basic` ₩10.5M
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— identical to pre-refactor.
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- coaching: `ga4_gtm_intermediate` (17 lessons, 1 student) → **₩1,570,000** exactly.
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- procurement: unit_cost × qty × 1.15 sanity check.
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- presales-seo end-to-end: findings→scope→engine→견적 + deck reproduces SHR/L'Escape.
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## 9. Future
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`digital_ads` / `digital_branding` now real (effort: monthly retainer / fixed stages). Next:
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optional **commission** line for ad media spend (per-deal %); add `content_marketing` as a
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project-service if effort quotes emerge (currently a coaching subject); optional matrix-mode
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coaching quotes; more education courses.
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