vpp-ai-platform/skills-py/vpp_skills/__init__.py
Thomas Bayes 23fdf49ff2
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M4: resource agent, envelopes live, review loop, insight cards
- packages/domain: AwardNotice, DISPATCH_PLAN proposal payload, ExecutionReport,
  MeteringRecord, potential-assessment and dispatch-optimization contracts,
  ReviewFinding (+ typed writebacks), SemanticMemoryEntry,
  EnvelopeChangeRequest, InsightCard — exported with fixtures on both sides.
- skills-py: potential-assessment (certified × rolling fulfilment, evidence
  days) and dispatch-optimization (per-interval LP on HiGHS, shortfall
  reported) skills + routes + tests.
- packages/services: dispatch rules in the policy pack (over-allocation,
  award anchor, lineage integrity for allocations); PowerBalanceSimulator;
  SimulationGateway (permit-only, idempotent, seeded execute → ExecutionReports);
  envelope deviation-streak suspension + apply(); ReviewService (attribution,
  reliability EWMA writeback, semantic memory, envelope recommendations as
  change requests); dispatch assembler; skill client methods.
- packages/runtime: resource agent; award-decomposition, review and
  envelope-review workflows; lifecycle selects simulator/gateway by proposal
  type; trigger hooks for awards, execution reports, metering; decide()
  resumes either lifecycle or envelope-review runs; insight cards API.
- Tests: docs/07 D-1 16:00 and D+1 end to end; reliability score 0.9 → 0.880
  and the next assessment de-rates capacity; envelope suspension on a seeded
  3-day streak; WIDEN request applied only by a human. 184 TS + 80 Python.
- docs/open-questions: B10 (reliability/potential parameters). README and
  CLAUDE.md status → M4 done, M5 next.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01UoYoGYzHkFyv3ALenkRPhA
2026-09-02 19:31:12 -04:00

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"""Python skill services (docs/05 §1–2, ADR-0001).
Every skill is typed (generated pydantic contracts in ``vpp_contracts``),
versioned (``SKILL_VERSIONS``) and stateless. No module here may import or call
an LLM: skills are deterministic numeric services and sit on the control path
(CLAUDE.md hard rule 2).
"""
SKILL_VERSIONS: dict[str, str] = {
"load-forecast": "1.0.0",
"pv-forecast": "1.0.0",
"price-forecast": "1.0.0",
"bid-optimization-milp": "1.0.0",
"report-generator": "1.0.0",
"potential-assessment": "1.0.0",
"dispatch-optimization": "1.0.0",
}