What problem does it solve? After finishing a task, valuable insights about what worked and what went wrong are often lost. This Skill guides a structured retrospective over a completed activity, turning discussion logs and decisions into durable lessons. ## Core Features & Use Cases - Step-by-step review: Decomposes a completed activity's logs into chronological steps and reviews each one interactively with the user. - Reflection summary: Compiles what went well and what to improve, saved as a material attached to a dedicated postmortem activity. - Lesson persistence: Helps decide where to store actionable lessons, such as tag notes, decisions, auto memory feedback, or CLAUDE.md rules. - Use Case: After completing a multi-session refactoring task, run a postmortem to walk through each step, identify why a wrong design choice was made, and persist a rule so the same mistake is not repeated. ## Quick Start Ask the AI to run a postmortem on the activity you just finished, for example by saying "let's do a retrospective on this work".