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retro

Conduct a retrospective on a coding session.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(3)

  • SKILL.md4.3 KB
  • agents/openai.yaml146 B
  • LICENSE1.0 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

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

Steps

  1. Read write-skills 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.

  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  1. 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 write-skills.

리뷰

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같은 저장소의 스킬

Audit or rewrite AGENTS.md so it holds only lasting principles. Run it only when the user asks for it by name; never invoke it on your own.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dzhng/skills1.4천2026년 10월 19일 업데이트

Audit the choices an implementing agent made, not its diff — a pure decision audit that traces the session's history into a choices ledger, changes no code, and never blocks an unsupervised run. Working code still embeds architecture the user never chose; surface it because future work inherits it. Use when the user wants to review the decisions the AI made on their behalf, before merging or committing AI-implemented work, when integrating a delegated subagent's pass, or when a fix "works" but might be a point fix.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dzhng/skills1.4천2026년 10월 19일 업데이트

Audit and prioritize performance work through bounded-work and forward-progress checks. Use when asked to find performance issues, investigate freezes/500s/OOMs, review retries or polling for no-progress loops, rank a performance backlog, or implement the next simple performance fixes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dzhng/skills1.4천2026년 10월 19일 업데이트

Audit whether tests earn their maintenance cost and which suite owns each contract. Use when pruning redundant tests, investigating implementation coupling or test-only production hooks, reviewing the value of proposed coverage, or auditing an entire subsystem. Use write-tests to implement the resulting test changes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dzhng/skills1.4천2026년 10월 19일 업데이트

Run fast, progressive experiments to map tunable parameters and their effects. Use when optimizing code, prompts, configurations, or other artifacts against a goal or benchmark, or when a long research run needs a planned hypothesis queue, focused trials, and durable findings.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dzhng/skills1.4천2026년 10월 19일 업데이트

Shoot software UI like a film. A sequence of hero shots, each a steep, oblique, extreme close-up of the interface floating in black, with a razor-thin focal plane, a slow motivated camera drift, and UI that acts on its own, hard-cut on the action, ending on one line of copy and a still logo. Use when asked for a launch video, product film, feature trailer, teaser, promo clip, hero shot, or any "cinematic" footage of an app or UI. This skill covers camera, framing, light, and edit. It is stack-agnostic.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dzhng/skills1.4천2026년 10월 19일 업데이트

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