Friction-to-Learning Pipeline

Detect friction signals during agent execution, track them across sessions, and graduate recurring patterns into permanent guidance. Bridges the gap between ephemeral session friction and durable CLAUDE.md rules.

Research backing: Claude Coach (hook-based friction detection with SQLite storage), alirezarezvani's self-improving-agent (three-tier MEMORY to CLAUDE.md graduation), and the ACE framework (arXiv: evolving playbooks from execution feedback, +10.6% on agent tasks).

Current gap: LEARNINGS.md exists but requires manual aggregation via /abstract:aggregate-logs. This skill adds automatic friction detection and a structured promotion path.