Commit Graph

4 Commits

Author SHA1 Message Date
Benjamin Admin 4d225f73a8 feat(ai-sdk): coverage blind-spot proposer (P2 slice 6, type 4)
Completes the proposer's four types.

- FindCoverageGaps (proposer_coverage.go): deterministic — which EN ISO 12100
  hazard groups A-G did the engine leave with zero hazards for this machine? An
  empty group is a structural blind-spot signal (the machine may truly lack it,
  or a pattern/GT case is missing). Useful with no model at all.
- ProposeMissingHazards + BuildCoveragePrompt: optional LLM expansion of each gap
  into specific expected-but-missing hazards a safety assessor would name
  (propose-only, reuses LLMCompleter, degrades to nil on any error).
- Wired into iace-audit propose -> audit-reports/coverage.{md,json}.

On the dishwasher: D. Pneumatik (truly absent — nothing invented), E. Laerm
(borderline), F. Ergonomie (a genuine gap: manual loading the engine did not
produce). P3 (pin an accepted proposal into a GT case) remains as a human-in-the-
loop follow-up.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-26 10:27:01 +02:00
Benjamin Admin c13aa9183a feat(ai-sdk): vocab->tag proposer (P2 slice 5, type 3)
Extends Method C: for each unknown narrative token that pattern text names, suggest
the keyword_dictionary tag = the RequiredComponentTags shared by the naming
patterns (ranked by frequency, kept only when shared by >=40% of them, top 3).
Surfaces real dictionary gaps like "zwischenkreis" -> stored_energy and
"updates" -> has_software, which close coverage without hand-editing the dict.

Two precision fixes to Method C while here:
- patternsMentioning now matches WHOLE WORDS, not substrings — substring matching
  flagged fragments like "stehen" inside "entstehen" and produced nonsensical
  tag suggestions.
- a token is only proposed with a tag if one is shared by >=40% of its naming
  patterns, so diffuse common verbs (spread across categories) drop out.

Wired into iace-audit propose -> audit-reports/vocab.{md,json}. Residual
common-verb noise is left to the human/LLM filter rather than a hand-grown
stopword list. Type 4 (coverage blind spots) + P3 (pin accepted proposals into a
GT case) remain for slice 6.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-26 10:27:01 +02:00
Benjamin Admin 662aec209a feat(ai-sdk): foreign-framing proposer (P2 slice 4, type 2)
Surfaces fired patterns whose zone names terms the machine's narrative never
mentions — foreign framing that leaks through terms not yet in domainGateTerms
(once a term is a gate term, the ghost-pattern invariant already fences it out).

- FindFramingCandidates (proposer_framing.go): per fired pattern, zone terms with
  no narrative echo (minus a generic hazard-location stoplist). Echo matching is
  bidirectional to survive German compounding (narrative "Steuerung" echoes zone
  "Steuerungssystem"). Heuristic verdict foreign (fully orphan) / plausible
  (partial). Over-surfaces by design — human/LLM is the precision filter.
- Wired into iace-audit propose -> audit-reports/framing.{md,json}, threshold via
  IACE_FRAMING_MIN_ORPHAN (default 0.6).

Honest finding: genuine wrong-MACHINE framing (Walzen, Transportbaender) no longer
fires thanks to the machine-type gate; the residual is mostly cyber/control
patterns with generic-industrial zone vocabulary, candidates for re-framing.
Proposal types 3-4 (vocab->tag, coverage blind spots) remain for slice 5.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-26 10:27:01 +02:00
Benjamin Admin 8440ddfecb feat(ai-sdk): runnable iace-audit propose CLI + live LLM wiring (P2 slice 3)
Makes the offline proposer runnable end-to-end.

- BuildProposerInput (proposer_input.go): non-test engine->hazards path. The
  PatternMatch->Hazard converter is lifted out of the GT test files into
  production scope so both the tests and the CLI share one pipeline.
- iace-audit propose <narrative.json> [<ground-truth.json>]: detect candidates ->
  GT-screen survivors (when a ground truth is given) -> judge (HeuristicJudge by
  default, LLMJudge over ollama when IACE_PROPOSE_LLM=1) -> write the human-review
  queue to audit-reports/proposals.{md,json}. Propose-only.

Smoke run on a dishwasher narrative: 32 fired -> 3 candidates -> queue with a
confident duplicate, a confident distinct, and one punted to the LLM judge; GT
wall recall-safe. Live qwen is opt-in via env; the heuristic default keeps the
tool runnable (and CI deterministic) without a model. Proposal types 2-4
(foreign-framing gates, vocab->tag, coverage blind spots) remain for slice 4.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-26 10:27:01 +02:00