vpp-ai-platform/CLAUDE.md

CLAUDE.md — agent operating manual

Design docs live in docs/ (00–13, Chinese). They are the specification; this file distills what is binding when writing code. When code and docs conflict, docs win — or write an ADR changing the doc first.

Current phase

Docs complete; M1 implemented (schemas, contracts pipeline, ledger, snapshot, time-series, relational and ingestion services, dual-side CI). Storage is in-memory reference semantics — persistent adapters arrive with M3. Next is M2. Build order is ROADMAP.md (M1→M5). Do not start a milestone's work before its predecessor's acceptance criteria are testable, and do not build phase-2 items (edge control links, federation, interaction/load-control agents) unless explicitly asked.

Hard rules (from docs/01 invariants — treat as review criteria)

1. LLM never computes numbers. Any numeric field in a Proposal payload must be a {toolCallId, path} reference into recorded tool-call lineage, dereferenced by the assembler. If you find yourself parsing a number out of LLM text into a payload, stop — that's the architecture's one forbidden move.
2. No LLM in any control path. Nothing under services/ or the execution path may import or await an LLM call. Periodic workflows must run with the LLM backend down (invariant I6 — there is a test for this).
3. External effects only via (Proposal, ExecutionPermit). Gateways/adapters never accept a bare plan. Permits are short-lived and revocable.
4. AI cannot approve. No code path may transition a Proposal to APPROVED/AUTHORIZED without either a matched envelope + passing checks, or a human resume() with an approver identity distinct from the origination chain.
5. Everything auditable. State transitions, tool calls, approvals, permits, and gateway receipts are event-sourced. Snapshots referenced by lineage are immutable.
6. Schemas live in packages/domain only. Python models are generated from contracts/*.schema.json — never hand-edit generated files, never define a business object schema anywhere else.

Conventions

• Naming: use the canonical code names in GLOSSARY.md. Do not invent new English names for domain terms that already have one.
• Language: architecture docs Chinese; code, identifiers, comments, commit messages, ADRs English.
• Data representation (docs/11 §3.3): money/energy/prices as fixed-point decimal strings; units in field names (power_mw, price_yuan_per_mwh); timestamps ISO8601 UTC; market intervals as {date, interval_index} with interval_minutes explicit; all IDs strings; enums UPPER_SNAKE string literals.
• Mastra: do not trust memorized APIs — check node_modules/@mastra/*/dist/docs/ (or the mastra skill) against the installed version before writing framework code.
• Testing floor: every invariant above has at least one automated test; schema changes run golden-fixture validation on both TS and Python sides; policy pack changes require their rule tests green.

Do not

• Do not invent business parameters (market deadlines, envelope bounds, loss budgets, buffer coefficients). Check docs/open-questions.md; if a needed parameter is listed there, wire it as named config with a placeholder value and a // OPEN-QUESTION: comment, and say so in your summary.
• Do not relitigate decisions recorded in docs/adr/. If a decision must change, propose a superseding ADR.
• Do not create root-level summary docs that duplicate docs/ content (no architecture.md / tech-stack.md — README points to the sources of truth).
• Do not add a sixth agent, merge the safety chain into business workflows, or bypass the proposal lifecycle for "internal" effects — these were considered and rejected (see ADRs 0005–0007).

Reading order for common tasks

Task	Read first
Domain schemas / contracts	docs/11, docs/00 §4, GLOSSARY.md
Runtime, workflows, agents	docs/09, docs/02
Safety chain, approvals, permits	docs/03, docs/01 invariants
Skill services (Python)	docs/05 §1–2, docs/11 §3
Anything touching money or bids	docs/07 (scenario), docs/13 §1
Eval harness	docs/12