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
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export * from './metrics.js'
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export * from './dataset.js'
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M3: Mastra runtime, safety chain, two agents, Case Desk v1
- packages/domain: safety-chain objects (ValidationResult, SimulationResult,
EnvelopeMatch, StaleDenial, ExecutionReceipt, LineageRef/BidProposalDraft,
RouterDecision, BidExportFile) + fixtures on both sides.
- packages/services: proposal digest; PolicyEngine + hubei-spot-bidding pack
(digest-valid, bid-format, price-limits, quantity-non-negative,
ledger-consistency, lineage-integrity, originator-permission — each with
pass/fail tests); EnvelopeService; AuthorityService (fresh check, permits,
revoke, gateway validate); FileExportGateway (idempotent receipts);
Memory/File EventBus; LineageRecorder + P2 assembler; RevenueScenario
simulator; CaseDeskService; FsRepository; skill HTTP client moved here.
- packages/runtime: createRuntime (LibSQL storage, per-runtime workflow
factories), proposal-lifecycle (rule check → simulation → envelope gate
with suspend/resume → fresh check + permit → release), day-ahead-situation,
day-ahead-bid, TriggerService (scheduled/event/manual), LlmPort
(Mastra/Scripted/Null), Case Desk HTTP API, dev entry point.
- Tests: all eight docs/01 invariants, docs/07 06:00→08:30 end to end with
LLM down, restart survival of a suspended approval, permit expiry and
revocation, replay of a released proposal, trigger scheduling. 141 TS +
60 Python tests.
- Known gaps: ledger not yet persisted (replayed on restart); STALE ends the
run instead of looping to rule check; synthetic data stands in for
historical replay.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01UoYoGYzHkFyv3ALenkRPhA
2026-09-02 06:55:55 -04:00
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export { HttpSkillClient, SkillHttpError } from '@vpp/services'
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export type { SkillClient } from '@vpp/services'
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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
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export * from './harness.js'
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