What problem does it solve? After a complex agent session, durable learnings about mistakes, tool quirks, and workflow patterns are lost unless someone manually distills them. This Skill mines the active conversation transcript and converts those learnings into concrete, approved edits on existing skills. ## Core Features & Use Cases - Parallel multi-lens review: Spawns three reviewer subagents (judgment, tooling, divergent) over the active transcript, each with a dedicated prompt template in references/. - Structured synthesis: A synthesizer subagent merges findings into an Accepted / Rejected / Backlog list with durability, specificity, and convergence criteria. - Approval-gated application: Accepted edits are presented to the user before landing; trivial edits are applied directly while substantive ones route to the create-skill draft/test/iterate loop. - Use Case: After a debugging session where the agent discovered a non-obvious Gradle flag and a missed skill trigger, run reflect to capture the flag convention in the relevant skill and tune the missed skill's description so it fires next time. ## Quick Start Say "reflect" after a complex task completes to review the session and route durable learnings into skill edits.