vpp-ai-platform/README.md
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

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# VPP AI Platform · 虚拟电厂多时空协同智能运营平台
AI-assisted operations platform for a virtual power plant (VPP) in Hubei, China:
five LLM agents propose market bids, resource dispatch, and load-control plans;
a deterministic safety chain (rule check → simulation → envelope/human approval →
execution permit) governs everything before any external effect. **The LLM never
computes numbers and never touches the second-level control loop.**
**Status: architecture/design phase.** No implementation code yet. The design is
complete and internally consistent (docs 00–13); implementation follows
[ROADMAP.md](ROADMAP.md), starting with M1.
## Orientation
| You are… | Start with |
|---|---|
| A coding agent about to implement | [CLAUDE.md](CLAUDE.md), then docs/00, 01, 09, 11 |
| New to the project | [docs/00-overview.md](docs/00-overview.md) → [docs/07-scenario-walkthrough.md](docs/07-scenario-walkthrough.md) (the end-to-end reference scenario) |
| Reviewing the business case | [proposal.md](proposal.md) (申报材料, source of requirements) |
| Looking for a settled decision | [docs/adr/](docs/adr/) |
| Wondering what's still undecided | [docs/open-questions.md](docs/open-questions.md) |
## Document map (docs are in Chinese; implementation-facing files in English)
| Doc | Content |
|---|---|
| [00-overview](docs/00-overview.md) | System context, two-plane architecture, business objects |
| [01-principles](docs/01-principles.md) | 9 principles + 8 hard invariants (binding for all code) |
| [02-cognitive-plane](docs/02-cognitive-plane.md) | Five agents, Runtime, memory, Case Desk |
| [03-safety-chain](docs/03-safety-chain.md) | Proposal state machine, envelopes, permits, staleness |
| [04-control-plane](docs/04-control-plane.md) | Execution engine, edge autonomy, time/space cascades |
| [05-skills-and-data](docs/05-skills-and-data.md) | Skill contracts, five-store data layer, policy packs |
| [06-integration](docs/06-integration.md) | External system boundaries and degraded channels |
| [07-scenario-walkthrough](docs/07-scenario-walkthrough.md) | Day-ahead spot bidding, D-1 → D → D+1 |
| [08-implementation](docs/08-implementation.md) | Stack, LLM abstraction, deployment, milestones |
| [09-runtime-implementation](docs/09-runtime-implementation.md) | Runtime on Mastra: workflows, suspend/resume, lineage |
| [10-federation](docs/10-federation.md) | Cross-province boundary: signed artifacts only |
| [11-contracts](docs/11-contracts.md) | Ports, canonical objects, TS↔Python contract pipeline |
| [12-evaluation](docs/12-evaluation.md) | Four-layer evals, change gates, KPI definitions |
| [13-risks-failure-modes](docs/13-risks-failure-modes.md) | FMEA, top-5 risks, kill-switch hierarchy |
Supporting: [brainstorming.md](brainstorming.md) is an independent peer review
whose findings were integrated (see docs/01 invariants note);
[GLOSSARY.md](GLOSSARY.md) maps Chinese domain terms to canonical code names.
## Target repository layout (from docs/09 §7)
```
packages/
├── domain/ # zod schemas — single source of truth for all business objects
├── runtime/ # Mastra instance, workflows, agents, tool registry, triggers
├── services/ # deterministic services: policy engine, envelopes, ledger, authority
├── adapters/ # anti-corruption layers: trading platform, dispatch, metering
├── evals/ # eval harness, datasets, judges (docs/12 §5)
└── skills-py/ # Python skill services (forecasting, MILP optimization, simulation)
contracts/ # generated JSON Schema + golden fixtures (cross-language contract)
```