v0.2.3 - procedural memory: lessons, failures, auto-distill

Full Changelog: v0.2.2...v0.2.3

Procedural memory layer - PMB now learns lessons and avoids repeating failures, on top of factual recall. The 94.5% LoCoMo recall@10 is unchanged.

Added

• pmb learn "..." + pmb lessons - teach durable lessons ("this repo uses pnpm, never npm"); review them. Surfaced via the hybrid + predicate-aware ranker.
• pmb learn --failed - negative memory: record failures ("numpy 2.x broke lancedb") that recall flags so they're not repeated.
• pmb distill + auto-distill on session end - an LLM extracts durable lessons/failures from a session automatically (zero-command when lessons.auto_distill_on_session_end is on). Reuses Claude CLI / Anthropic / Ollama.
• Lesson-intent boost - on how-to/convention queries, lessons & failures are gently boosted. Scoped to lesson/failure events only, so recall on datasets without them (LoCoMo) is unchanged.
• Trust signals in recall - source attribution, confidence (high/med/low), staleness flag.
• pmb audit memory-health - lessons / failures / stale / low-confidence / conflicts.
• pmb note instant capture; pmb watch auto-ingest a notes file/folder.

Notes

• LoCoMo recall@10 = 94.5% (full 10-conv run) - unchanged.
• 50+ new regression tests; all green.

Install: pip install --upgrade pmb-ai