What problem does it solve? After a coding session with an AI agent, it is hard to know why the agent struggled, made mistakes, or wasted tokens. This Skill reviews session logs and turns those observations into concrete improvements for the agent's environment, such as navigation pointers, automated checks, and coding standards. ## Core Features & Use Cases - Session log analysis: Reads primary sources from a specified coding session (defaulting to the current one) to find friction points. - Categorized improvement candidates: Evaluates navigation, automated checks, coding standards, AGENTS.md bloat, tool economy, no-op instructions, and information access, then presents findings ordered by severity. - Environment file guidance: Applies clear rules for what belongs in CLAUDE.md/AGENTS.md versus CODING_STANDARDS.md versus docs, respecting the context pressure difference between implementation and review agents. - Use Case: After a long session where the agent repeatedly failed to find a config file and made a lint-catchable error, run a retrospective to get a navigation pointer added to AGENTS.md and a new lint rule proposed. ## Quick Start Ask the agent to run a retrospective on the current coding session and suggest improvements to the agent environment.