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[email protected]andClaude Opus 4.6
8e2349d12e
Extract the skills system into a standalone `ironclaw_skills` crate (following the ironclaw_safety pattern) and wire it into the v2 engine for deterministic skill selection, CodeAct code injection, and confidence tracking. **ironclaw_skills crate** (94 tests): - Core types: SkillManifest, ActivationCriteria, LoadedSkill, SkillTrust - V2 types: V2SkillMetadata, CodeSnippet, SkillMetrics, V2SkillSource - Deterministic 4-phase selector (gating→scoring→budget→attenuation) - apply_confidence_factor() for extracted skill scoring - SKILL.md parser, validation/escaping, gating, registry, catalog - Feature-gated: catalog (reqwest), registry (filesystem) **Engine integration** (14 new tests): - DocType::Skill with retrieval weight 0.45 - SkillSelector bridges MemoryDoc→LoadedSkill for shared scoring - SkillTracker for usage/version/rollback confidence tracking - System prompt injection via <skill> XML blocks - CodeAct snippet injection via Monty NameLookup - Skill extraction mission replaces playbook extraction - ThreadManager.set_skill_selector() for runtime wiring **Bridge + migration**: - skill_migration.rs: v1 SKILL.md → v2 MemoryDoc (idempotent) - init_engine() migrates v1 skills, builds SkillSelector - src/skills/mod.rs → re-export shim **E2E test** (tests/engine_v2_skill_codeact.rs): - Full CodeAct loop: skill selected → LLM returns Python code → Monty executes http() → mock returns canned GitHub JSON → FINAL() terminates → thread completes with canned data - GitHub SKILL.md in skills/github/ as reference implementation Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>