vpp-ai-platform

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Author	SHA1	Message	Date
Thomas Bayes	8796faca63	M2: skill contracts, Python skill service, L2 eval harness with baseline - packages/domain: ForecastRequest, BidOptimizationRequest/Result, ReportRequest, SkillReport (+ golden and invalid fixtures, exported to contracts/ and regenerated as pydantic models). - skills-py/vpp_skills: FastAPI service with versioned registry; load/PV/ price forecasts (same-day-type EWM point forecast, conformal residual quantiles — coverage test as acceptance gate); bid-optimization MILP on HiGHS (binary block participation, hard ledger energy bounds, exact Decimal fit of the rounded curve inside the bounds, revenue distribution over quantile paths); report generator whose every figure is a {tool_call_id, path} reference, with a verifier. 48 tests incl. hypothesis property test that bids respect ledger constraints. - packages/services: LedgerService.dayAheadBounds (the P7 cascade band handed to the optimizer); Decimal resolved once for CJS/ESM interop. - packages/evals: L2 metrics (MAPE, nRMSE, coverage, direction accuracy, naive/hindsight revenue baselines), HTTP skill client, rolling-origin harness that pushes each bid through the real ledger, CLI with --check/--write-baseline; committed baseline on the SYNTHETIC dataset (no historical Hubei data yet — baselines measure the harness, not KPI). - CI: evals job boots the skill service and fails on baseline digest drift. - docs/open-questions: A6 (flexibility marginal cost = offer floor); A4/B6 wired as placeholders. README/CLAUDE.md status → M2 done, M3 next. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01UoYoGYzHkFyv3ALenkRPhA	2026-09-02 06:29:08 -04:00
stewart hu	80835138e9	Scaffold repo for implementation handoff - README: orientation, doc map, target package layout (pointers only, no duplicated architecture content) - CLAUDE.md: agent operating manual — invariants as code-review rules, conventions, do-not list, task reading order - ROADMAP: M1-M5 with verifiable acceptance criteria, phase-2 fence - GLOSSARY: canonical Chinese-term → code-name mapping - docs/adr/: eight ADRs recording settled decisions and rejected alternatives - docs/open-questions.md: consolidated TODO(业务) tracker by owner and blocking milestone - .gitignore; untrack .DS_Store Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_019u5SLNweVio6ozJX7yfxQr 🔮 View transcript: https://logs.lojong.info/s/e8u90k3t33w590r7b5y7yzqh	2026-09-01 21:13:00 -04:00

Author

SHA1

Message

Date

Thomas Bayes

8796faca63

M2: skill contracts, Python skill service, L2 eval harness with baseline

- packages/domain: ForecastRequest, BidOptimizationRequest/Result,
  ReportRequest, SkillReport (+ golden and invalid fixtures, exported to
  contracts/ and regenerated as pydantic models).
- skills-py/vpp_skills: FastAPI service with versioned registry; load/PV/
  price forecasts (same-day-type EWM point forecast, conformal residual
  quantiles — coverage test as acceptance gate); bid-optimization MILP on
  HiGHS (binary block participation, hard ledger energy bounds, exact
  Decimal fit of the rounded curve inside the bounds, revenue distribution
  over quantile paths); report generator whose every figure is a
  {tool_call_id, path} reference, with a verifier. 48 tests incl. hypothesis
  property test that bids respect ledger constraints.
- packages/services: LedgerService.dayAheadBounds (the P7 cascade band
  handed to the optimizer); Decimal resolved once for CJS/ESM interop.
- packages/evals: L2 metrics (MAPE, nRMSE, coverage, direction accuracy,
  naive/hindsight revenue baselines), HTTP skill client, rolling-origin
  harness that pushes each bid through the real ledger, CLI with
  --check/--write-baseline; committed baseline on the SYNTHETIC dataset
  (no historical Hubei data yet — baselines measure the harness, not KPI).
- CI: evals job boots the skill service and fails on baseline digest drift.
- docs/open-questions: A6 (flexibility marginal cost = offer floor); A4/B6
  wired as placeholders. README/CLAUDE.md status → M2 done, M3 next.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01UoYoGYzHkFyv3ALenkRPhA

2026-09-02 06:29:08 -04:00

stewart hu

80835138e9

Scaffold repo for implementation handoff

- README: orientation, doc map, target package layout (pointers only,
  no duplicated architecture content)
- CLAUDE.md: agent operating manual — invariants as code-review rules,
  conventions, do-not list, task reading order
- ROADMAP: M1-M5 with verifiable acceptance criteria, phase-2 fence
- GLOSSARY: canonical Chinese-term → code-name mapping
- docs/adr/: eight ADRs recording settled decisions and rejected
  alternatives
- docs/open-questions.md: consolidated TODO(业务) tracker by owner and
  blocking milestone
- .gitignore; untrack .DS_Store

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019u5SLNweVio6ozJX7yfxQr

🔮 View transcript: https://logs.lojong.info/s/e8u90k3t33w590r7b5y7yzqh

2026-09-01 21:13:00 -04:00

2 Commits