What problem does it solve? After finishing a task, it is hard to reconstruct what actually happened: which skills were used, where time and tokens went, what dead ends occurred, and how the prompt could have been better. This Skill produces a structured, evidence-based retrospective from the visible conversation and tool-call history. ## Core Features & Use Cases - Trace Reconstruction: Rebuilds the phases of work, skills loaded, files read, commands run, and validation performed from visible context. - Cost Analysis: Ranks longest tasks and token-heavy hotspots using exact telemetry when available or qualitative evidence when not, without fabricating numbers. - Actionable Improvements: Answers focus questions about missing or misleading information and outputs a copyable improved prompt plus a next-time checklist. - Use Case: After a long debugging session, ask for a retrospective to learn which searches were wasted, what context should have been provided up front, and how to prompt better next time. ## Quick Start Ask the agent to run context-reflect on the task we just finished and summarize the dead ends, token hotspots, and a better prompt for next time.