8796faca63
- 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
81 lines
4.4 KiB
Markdown
81 lines
4.4 KiB
Markdown
# CLAUDE.md — agent operating manual
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Design docs live in `docs/` (00–13, Chinese). They are the specification; this
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file distills what is **binding** when writing code. When code and docs conflict,
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docs win — or write an ADR changing the doc first.
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## Current phase
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Docs complete; M1 and M2 implemented (schemas + contracts pipeline; ledger,
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snapshot, time-series, relational, ingestion services; Python skill service
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with forecast/MILP/report skills; L2 eval harness with committed baseline).
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Storage is in-memory reference semantics — persistent adapters arrive with M3.
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The eval dataset is synthetic until historical data lands. Next is M3. Build
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order is ROADMAP.md (M1→M5). A skill change that moves an L2 metric must
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update the baseline in the same change (`npm run eval -w @vpp/evals -- --write-baseline`).
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Do not start a milestone's work before its predecessor's acceptance criteria are
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testable, and do not build phase-2 items (edge control links, federation,
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interaction/load-control agents) unless explicitly asked.
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## Hard rules (from docs/01 invariants — treat as review criteria)
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1. **LLM never computes numbers.** Any numeric field in a `Proposal` payload must
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be a `{toolCallId, path}` reference into recorded tool-call lineage,
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dereferenced by the assembler. If you find yourself parsing a number out of
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LLM text into a payload, stop — that's the architecture's one forbidden move.
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2. **No LLM in any control path.** Nothing under `services/` or the execution
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path may import or await an LLM call. Periodic workflows must run with the
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LLM backend down (invariant I6 — there is a test for this).
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3. **External effects only via `(Proposal, ExecutionPermit)`.** Gateways/adapters
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never accept a bare plan. Permits are short-lived and revocable.
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4. **AI cannot approve.** No code path may transition a Proposal to
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APPROVED/AUTHORIZED without either a matched envelope + passing checks, or a
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human `resume()` with an approver identity distinct from the origination chain.
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5. **Everything auditable.** State transitions, tool calls, approvals, permits,
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and gateway receipts are event-sourced. Snapshots referenced by lineage are
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immutable.
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6. **Schemas live in `packages/domain` only.** Python models are generated from
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`contracts/*.schema.json` — never hand-edit generated files, never define a
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business object schema anywhere else.
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## Conventions
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- **Naming**: use the canonical code names in GLOSSARY.md. Do not invent new
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English names for domain terms that already have one.
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- **Language**: architecture docs Chinese; code, identifiers, comments, commit
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messages, ADRs English.
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- **Data representation** (docs/11 §3.3): money/energy/prices as fixed-point
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decimal **strings**; units in field names (`power_mw`, `price_yuan_per_mwh`);
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timestamps ISO8601 UTC; market intervals as `{date, interval_index}` with
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`interval_minutes` explicit; all IDs strings; enums UPPER_SNAKE string literals.
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- **Mastra**: do not trust memorized APIs — check `node_modules/@mastra/*/dist/docs/`
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(or the mastra skill) against the installed version before writing framework code.
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- **Testing floor**: every invariant above has at least one automated test;
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schema changes run golden-fixture validation on both TS and Python sides;
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policy pack changes require their rule tests green.
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## Do not
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- Do not invent business parameters (market deadlines, envelope bounds, loss
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budgets, buffer coefficients). Check `docs/open-questions.md`; if a needed
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parameter is listed there, wire it as named config with a placeholder value
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and a `// OPEN-QUESTION:` comment, and say so in your summary.
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- Do not relitigate decisions recorded in `docs/adr/`. If a decision must
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change, propose a superseding ADR.
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- Do not create root-level summary docs that duplicate `docs/` content
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(no architecture.md / tech-stack.md — README points to the sources of truth).
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- Do not add a sixth agent, merge the safety chain into business workflows, or
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bypass the proposal lifecycle for "internal" effects — these were considered
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and rejected (see ADRs 0005–0007).
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## Reading order for common tasks
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| Task | Read first |
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|---|---|
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| Domain schemas / contracts | docs/11, docs/00 §4, GLOSSARY.md |
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| Runtime, workflows, agents | docs/09, docs/02 |
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| Safety chain, approvals, permits | docs/03, docs/01 invariants |
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| Skill services (Python) | docs/05 §1–2, docs/11 §3 |
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| Anything touching money or bids | docs/07 (scenario), docs/13 §1 |
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| Eval harness | docs/12 |
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