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8 Commits

Author SHA1 Message Date
Andrew Yim
6f69a6a484 Route estimate outputs to central archive (ourdigital-space/estimates) 
All estimates now archive to ~/Workspaces/ourdigital-space/estimates/
<YYYY-MM-DD>_<prospect|account>_<service>/ (single 견적 archive). Engine
SKILL.md documents the output-home convention (engine stays --out-dir-agnostic).
presales-seo Stage 5 writes the estimate to $EST (archive); Stage 6 deck reads
from $EST but stays in the engagement bundle.

(Workspace side, not in this repo: SHR estimate moved to the archive, pointer
left in the engagement, ourdigital-space/CLAUDE.md documents estimates/.)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 02:22:33 +09:00
Andrew Yim
c9bdbb57f7 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>
 2026-05-28 01:54:11 +09:00
Andrew Yim
95d6fdf499 Add luxury/vertical signal to auto-tiering 
pick_baseline now applies a premium floor: if prospect.vertical matches
rate_card.tiering.premium_verticals (luxury/premium/deluxe/5성/특1급…), the
auto-selected tier is floored to premium_min_tier (default basic) so a premium
single property won't drop to the smb entry tier.

Validated: L'Escape (hotel_luxury, 1 property) smb -> basic (₩10.5M);
non-luxury single -> smb (₩3.0M); SHR chain -> treatment (₩29.5M) unchanged.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 01:15:55 +09:00
Andrew Yim
60734dbde7 Recalibrate estimate for SMB acceptability 
Real-world feedback: list-rate calc overshot SMB-acceptable levels.
- scaling: driver properties_total -> subbrands_total (chains share templates),
  cap x6.5 -> x2.0, applied to On-page only (Technical now fixed site-wide)
- add 'smb' entry tier (lean hours @ 0.55 billing); 3-tier auto-select
  (smb/basic/treatment) by portfolio size; per-tier billing; --baseline smb enabled
- docs (findings_to_service.md, SKILL.md) synced to 3-tier model

Effect: SHR 25-property chain 71.5M -> 29.5M; SMB single hotel ~3.0M;
basic/treatment still reproduce real 10.5M/25.0M at 1 property.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 01:13:38 +09:00
Andrew Yim
5f66f57a8e Rebuild estimate engine to effort-based SOW model 
Replace flat per-service ranges with OurDigital's real quoting model
(role_rate × billing_rate 0.70 × standard hours), sourced from the
06_Working Template quotes:
- rate_card.yaml: role rate card, billing/basis/terms, tools, scaling bands
- sow_templates.yaml: basic + treatment task-hour templates
- estimate.py: assemble SOW from findings, scale Technical/On-page hours by
  properties_total, 제안가 = 합계 floored to 500k
- build_deck.py: estimate slide shows module 소계 + 제안가 (point)
- findings_to_service.md / SKILL.md / DESIGN.md: synced to new model

Validated: reproduces real Basic ₩10.5M and Treatment ₩25.0M exactly;
SHR (25 properties) scales to ₩71.5M, L'Escape (1) = ₩25.0M.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 00:51:52 +09:00
Andrew Yim
3a8edebfef estimate.py: scale local_seo/onpage_entity by portfolio size 
Add configurable sub-linear scope-scaling bands to rate_card.yaml; estimate.py
now multiplies monthly line-item rates by properties_total (local_seo) and
subbrands_total (onpage_entity), with the scope note written into the 견적.

Validated: L'Escape (1 property) stays at base 23-47M; SHR (25 properties,
5 sub-brands) scales to 54.8-110.6M (local ×4.5, on-page ×2.2).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 00:24:33 +09:00
Andrew Yim
ba88247496 Implement ourdigital-presales-seo skill 
SKILL.md orchestration (8 gated stages), references (rate_card.yaml,
findings_to_service rubric, competitor sets), findings.schema.json contract,
and scripts: kg_query.py (generalized KG examination), estimate.py
(findings→rate-card 견적 md/xlsx/json), build_deck.py (9-slide branded PPTX),
render_pdf.sh (Korean PDF via headless Chrome), plus client_brief.html template.

Validated on Sono Hotels & Resorts findings: estimate OD-2026-001
(23-47M KRW) and a 9-slide deck generated cleanly.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-27 23:10:53 +09:00
Andrew Yim
a55e77d1b0 Add design spec for ourdigital-presales-seo skill 
Standardizes the pre-sales SEO + Knowledge Graph diagnostic (origin: Sono
Hotels & Resorts) into a reusable skill with findings→rate-card estimate,
editable PPTX sales deck, and Notion SEO Audit DB archiving.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-27 22:58:22 +09:00