What problem does it solve? After a coding run or session ends, the lessons it produced are lost, so the next run repeats the same mistakes and re-derives the same solutions. This Skill mines a finished run's trajectory for high-signal lessons and persists them to AGENTS.md or machine-readable memory so future runs start smarter. ## Core Features & Use Cases - Correction Mining: Detects failed-then-succeeded command pairs, classifies the error type, and records wrong-pattern to right-pattern mappings. - Precedent & Bug Pattern Storage: Stores solved-problem fingerprints and structured root-cause entries in .orchestrator/patterns.jsonl so recurring issues are reused, not re-diagnosed. - Incremental, Deduped Memory: Processes only new trajectory segments via an index file, dedups semantically, and caps memory sections at ~12 bullets with eviction. - Use Case: After simplicio-tasks finishes its self-audit, run this Skill to write the top corrections and stable workspace facts into AGENTS.md so the next session pre-empts known failures. ## Quick Start Ask the agent to run a retrospective on this session and write any durable lessons to the project memory.