What problem does it solve? After a long Claude Code session, it is hard to know where time actually went, what caused friction, and what should change next time. This Skill turns a finished session into a structured retrospective with measured timing data, concrete improvement actions, and a persistent log. ## Core Features & Use Cases - Transcript Time Analysis: Runs a deterministic Python script over the session JSONL transcript to compute hands-on time, agent time, per-turn costs, and error counts, rendered as a phase breakdown table. - Actionable Improvements: Converts observations and user feedback into specific deliverables such as skill edits, CLAUDE.md updates, doc changes, or tickets, with a parallel subagent auditing CLAUDE.md files. - Persistent Logging: Appends a formatted entry to docs/process/retrospective.md, elevates reusable insights into docs/process/learnings.md, and commits everything. - Use Case: After completing a multi-hour feature implementation, invoke /retro to see that 60 minutes went to hands-on review while the agent spent 30 minutes in fix cycles, then log a CLAUDE.md rule to prevent the repeated bug pattern. ## Quick Start Ask the agent to run /retro to analyze the current session transcript and log a retrospective with improvement actions.