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Retro TEXT

Analyzes a coding session's logs to identify inefficiencies, errors, or missing guardrails. It proposes concrete improvements to the agent's environment, such as adding automated checks, refining navigation pointers, or updating coding standards.

2 uses this weeksource mattpococklicence MIT
Quality gate: INCONCLUSIVE · better answers · measured 2026-10-24
Blind-judged against the bare model on 2 requests: average lift +0.0 points (specificity, structure, method, fit).
won 1/2, lift +0.0, tokens ×245.54
Security scan: clean · 2026-10-24 · 2 files · ran in sandbox
no network calls, shell tricks, credential access or instruction tampering found in its files.

Try asking

Say it in your own words; the assistant finds this recipe by itself. Examples:

“Kør en retro på den sidste session, hvor jeg bad dig rette login-fejlen.”
“Jeg bemærkede, at du brugte meget tid på at finde konfigurationsfilen. Kan vi lave en retrospektiv for at se, om vi kan tilføje en navigationsmarkør?”
“Analyser sessionen fra i går. Hvorfor fangede linteren ikke den type-fejl?”
“Run a retro on the last session where I asked you to fix the login bug.”
“I noticed you spent a lot of time searching for the config file. Can we do a retrospective to see if we can add a navigation pointer?”
“Analyze the session from yesterday. Why did the linter fail to catch that type error?”
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Good for

retrospectiveagent-optimizationsession-analysiscoding-standardsautomationdebuggingprocess-improvementcontext-management

Not for

Do not use this skill for general code reviews of specific pull requests or for debugging a single bug in the current codebase. It is not for writing new features or refactoring code directly, but rather for improving the meta-process of how the agent works. For immediate code fixes, use a standard coding or debugging skill instead.

Details

When it is the right choice

Use this skill after a coding session to review what went well and what didn't. It is ideal when the user wants to improve the agent's future performance by fixing environment issues, adding missing tests, or clarifying instructions. It is also appropriate when the user notices the agent struggled with navigation or made repeated errors that could be prevented by better tooling.

The full recipe the assistant reads

The user has asked for a retrospective. You are suggesting improvements to the coding agent's environment to improve future runs.

Steps

  1. Call the Skill tool with writing-for-agents for the writing style guide.

  2. Read the primary sources for the session the user specifies. This may mean searching through session logs on this machine. If the user doesn't specify a session, default to the current one.

  3. Look for candidates for improvement in these categories.

  4. Navigation: how easy was it for the agent to find the right files? Are there hidden dependencies between files? Would a navigation pointer make it easier? Use when the session took a long time to find a piece of information.

  5. Automated checks: are there automated checks that could catch errors the agent made? Linting, typing, tests, filesystem linters? Read the repo's own check command first (its package.json/build-tool lint/check scripts, its CI workflow), so a check that already exists but sits unwired or silently broken is the finding, not a reinvention. A repo with no guardrail (no pre-commit hook and no CI job running its lint/typecheck/test command) is itself a finding: an un-linted repo is a standing missed opportunity, not a neutral default. Use when the agent made a mistake an automated check could have caught, or the repo has no guardrail at all.
  6. Coding standards: should the reviewer agent be given a new rule to enforce? Should an existing rule be removed or clarified? Classify the violation first: a mechanical one (a fixed syntactic pattern, a banned API, an import shape, a file-location rule) gets a deterministic check, full stop: a custom rule in the repo's own linter, a new pre-commit hook, or a new CI job, whichever the repo's language and existing guardrail make cheapest. Default to building the check over writing the rule. Reserve CODING_STANDARDS.md for genuine judgement calls (cross-file consistency, "matches the surrounding style," anything no guardrail could ever substitute for). Use when the reviewer agent failed to catch a mistake.
  7. Global AGENTS.md: are there any steering instructions that should be moved to coding standards (or automated checks) instead? Use when the AGENTS.md file is particularly large - in the repo OR the user's global scope.
  8. Tool economy: did the agent make expensive tool calls that could be streamlined? Is there any custom tooling (CLI's, MCP's) that is particularly token-inefficient? Use when the agent made an expensive tool call.
  9. No-ops: look for instructions in steering files that don't modify the agent's behavior. Use when the steering files are large and unwieldy.
  10. Information access: look for opportunities to increase the agent's access to information. Teeing dev server logs, readonly access to third-party services. Use when a crucial piece of information was not available to the agent.

  11. Present these candidates to the user, in order of severity.

Reference

Implementation vs Review

Remember that all work goes through two stages: implementation and review. The implementation agent has the most context pressure. They are responsible for exploration, writing code, and debugging failures.

The review agent has the least context pressure - it receives a diff, so no exploration needed. It often does not need to write code or debug.

This means that the review agent should be responsible for imposing coding standards, not the implementation agent.

Files

You have access to several files in the repo:

  • CLAUDE.md/AGENTS.md: these files are pushed to the context window of any agent working in this repo. They should be used incredibly sparingly, usually only for navigation pointers to other files.
  • CODING_STANDARDS.md: this file is read during review, not implementation. Add navigation pointers to docs folders if the standards file gets more than 1,000 lines long.
  • Docs: use docs as references files, pointed to by other files. Look for existing docs before writing new ones.
  • Skills: use skills for docs (since their description goes into the agent's context window), or for user-invoked commands. Follow the advice in the writing-for-agents skill.
Files in this skill (3)
  • LICENSE
  • SKILL.md
  • agents/openai.yaml
Where it comes from

Vendored from mattpocock/skills, commit 5beb35b040e3, path skills/engineering/retro, licence MIT. The upstream licence file ships inside the skill.