What problem does it solve? Valuable lessons from a working session—corrections, tool quirks, missed triggers—are usually lost when the conversation ends. This Skill mines the active Claude Code transcript for durable learnings and turns them into concrete, approved edits to existing skills. ## Core Features & Use Cases - Parallel multi-lens review: Launches three reviewer subagents (judgment, tooling, divergent) over the session transcript, each with a dedicated prompt template and model tier. - Structured synthesis: A synthesizer subagent merges findings into an Accepted / Rejected / Backlog list with durability, specificity, and convergence criteria. - Approval-gated application: Edits are applied only after explicit user approval, routed to existing skill sections, description tuning, or new skill creation via skill-creator. - Use Case: After a long debugging session where the agent discovered a non-obvious test command and the user corrected its approach twice, say "reflect" to capture those lessons as permanent improvements to the relevant skills. ## Quick Start Say "reflect" after a complex task completes to review the session and apply approved learnings to your skills.