Agent skill

Refit Environment Retrospective

by Yeachan-Heo in Yeachan-Heo/oh-my-claudecode

Reads an agent environment's own traces, friction reports and logs across sessions, then proposes fixes on the surface that owns each one, only with your approval.

MITAuto-check passedAgent Workflows

Install Refit Environment Retrospective

skills CLI
$ npx skills add Yeachan-Heo/oh-my-claudecode --skill refit -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Yeachan-Heo/oh-my-claudecode refit --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Yeachan-Heo/oh-my-claudecode.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/refit .claude/skills/refit && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
refit
GitHub stars
40k
Token cost
~1.4k tokens
SKILL.md length
794 words
Files
1
Skills in repo
47
Repo updated
First seen
Licence
MIT

At a glance

Reads an agent environment's own traces, friction reports and logs across sessions, then proposes fixes on the surface that owns each one, only with your approval.

  • Works in 4 steps: Deterministic check — the failure was… → Steering surface — the failure was a… → Tool surface — the drag was tooling… → …
  • After several sessions where the agent kept tripping on the same check
  • SKILL.md covers Evidence first, Four fix-owner surfaces, Proposal and landing and Headless refit (unattended…, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Refit studies the environment the agent worked in rather than the code it produced. It starts from instruments, not a checklist: trace timelines and summaries, a session friction report, the .omc/logs folder, plan notepads such as issues.md and problems.md, and the repo's own checks in package.json scripts and CI workflows. An empty survey is a valid result, and an invented finding counts as a violation.

Every finding must name the surface that owns its fix. A deterministic check covers mechanical failures with a lint rule, hook or CI job. The steering surface covers judgment calls through docs/standards or CLAUDE.md and AGENTS.md. The tool surface covers slow or costly tooling in .mcp.json, scripts or hooks, and the fourth surface is information access. A finding that fits none is declined with a reason, and nothing is written without your approval.

When your agent uses it

  • After several sessions where the agent kept tripping on the same check
  • Turning recorded friction into lint rules, hooks or doc changes
  • Auditing which of a repo's checks are unwired or silently broken

Example prompts

  • “Review what slowed down the last few ralph runs and propose environment fixes.”
  • “Read the friction report and tell me which repeated failures deserve a lint rule.”
  • “Check whether our CI workflows actually run the checks listed in package.json.”

Requirements

  • OMC instrumentation such as trace timelines and session friction reports

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Deterministic check — the failure was mechanical: a fixed syntactic pattern, a banned API, an import shape, a file-location rule. The fix…
  2. Steering surface — the failure was a judgement call no guardrail substitutes for: cross-file consistency, matches-surrounding-style. The…
  3. Tool surface — the drag was tooling itself: expensive or token-inefficient MCP calls, missing automation, checks too slow to be run when…
  4. Information surface — the agent needed a signal it could not reach: dev-server logs, service state, third-party readonly access. The fix…

What it can do on your machine

Read from SKILL.md and the folder at commit 454bae0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Refit Environment Retrospective loads about 1.4k tokens when it runs. Until then it costs about 78 tokens; SKILL.md has 794 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~78
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Yeachan-Heo/oh-my-claudecode at commit 454bae0, republished under its MIT licence (© Yeachan-Heo). 794 words, ~1,427 tokens.

Download SKILL.mdSave it as .claude/skills/refit/SKILL.md (or your agent's skills folder).
name
refit
description
Cross-session environment retrospective driven by OMC's own instrumentation — trace timelines, friction reports, logs, and plan notepads. Every finding lands on the surface that owns the fix (deterministic check, steering volume, tooling, or information access); nothing is written without user approval.
argument-hint
[--scope <area>] [--last <N sessions>]
disable-model-invocation
true

Refit

Refit surveys the environment the agent worked in — not the code it produced (review and verify own that) and not one launch run's lessons (the sediment pass owns that). Every kind of work leaves friction behind: a ralph loop that kept tripping on the same check, an autopilot run that stalled waiting for a signal, a debugging session where the decisive output was never captured anywhere. OMC instruments all of it. Refit reads the instruments and converts recorded friction into environment changes, so the next run starts in a better yard.

Evidence first

The survey starts from OMC's instruments, not from a checklist. Read before asking the user anything:

  • trace_timeline / trace_summary — where turns stalled, repeated, or fanned out wastefully
  • omc session friction report — friction the session recorded about itself
  • .omc/logs/ and session state — errors, retries, swallowed failures
  • plan notepads .omc/notepads/*/issues.md and problems.md — problems that accumulated across a plan
  • the repo's own check surface (package.json scripts, CI workflows) — read before proposing any new check, because a check that exists but sits unwired or silently broken is the finding, not a reinvention

Findings emerge from what the data shows. An empty survey is a valid result and is stated plainly; an invented finding is the same violation as skipping the survey. A repo with no wired automated checks is itself a finding, not a neutral default.

Four fix-owner surfaces

Every finding names the surface that owns its fix. A finding that fits no surface is declined, explicitly and with the reason.

  1. Deterministic check — the failure was mechanical: a fixed syntactic pattern, a banned API, an import shape, a file-location rule. The fix is a lint rule, hook, or CI job — whichever the repo's existing guardrails make cheapest. Default to building the check over writing the rule.
  2. Steering surface — the failure was a judgement call no guardrail substitutes for: cross-file consistency, matches-surrounding-style. The fix lands in the matching docs/standards/ volume, or in CLAUDE.md/AGENTS.md within the thin-entry budget the launch sediment pass defines. Navigation pointers over prose.
  3. Tool surface — the drag was tooling itself: expensive or token-inefficient MCP calls, missing automation, checks too slow to be run when they matter. The fix lands in .mcp.json, scripts/, hooks, or OMC config.
  4. Information surface — the agent needed a signal it could not reach: dev-server logs, service state, third-party readonly access. The fix tees the log, exposes the state, or documents the access path.

The split rests on where enforcement pressure lives: implementation contexts carry the most of it (exploration, writing, and debugging all at once); review contexts receive a diff with none of it. Standards therefore belong to reviewers and checks — never to more instructions loaded onto the implementer.

Show full SKILL.md (346 more words)Show less

Proposal and landing

  1. Present findings ranked by severity, each as finding → surface → intended change, with one line of instrument evidence (which instrument, what it showed).
  2. Stop for user approval. Each line is individually approvable or vetoable.
  3. Write approved findings to their surfaces. Before writing any steering prose, call the Skill tool with agent-doc-discipline and pass its verification checklist. A newly installed deterministic check must be proven to bite before it counts as landed: run it clean once, then demonstrate it failing on a deliberately introduced violation, then revert the violation. A check that cannot be shown failing goes back to the proposal — a guardrail nobody has seen fire is decoration, not protection.
  4. Record where each finding landed — one file location per line — so the next refit starts from the record, not from memory. A refit on a launch-run session starts from that run's sediment list; a launch run may defer a lesson to a later refit by naming it.

Headless refit (unattended invocation)

Refit is user-invoked, but its survey does not need the user at the keyboard to run — only to dispose. A host scheduler (cron, CI timer, an automation tool) may start a headless agent session that invokes this skill; the survey runs to its natural boundary under the same contract:

  • The survey reads the same instruments and lands nothing anywhere: headless refit produces the proposal list only — finding → surface → intended change, each with one line of instrument evidence — written to .omc/refit/pending-proposals.md and, when a notification channel is configured (configure-notifications), summarized there so the user learns a survey is waiting.
  • Nothing reaches a surface without the user's approval, exactly as in an interactive refit: proposals wait ranked, each independently vetoable, and the next interactive refit starts from the pending list instead of re-running the survey.
  • An empty survey is stated plainly ("no findings"), never padded — inventing findings is the same violation as skipping the survey.

Output

  • Findings ranked by severity, each with evidence, surface, and intended change — every line independently decidable
  • After approval: what landed and where
  • Declined findings, with reasons

© Yeachan-Heo, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/refit of Yeachan-Heo/oh-my-claudecode.

Open the folder on GitHubat commit 454bae0

Compare with similar skills

Refit Environment Retrospective next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Refit Environment Retrospective compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Refit Environment Retrospective this skillYeachan-Heo/oh-my-claudecode40k—~1.4kAutomated safety check: PassMIT
Agent Setup Health Audittw93/Waza7.2k—~5.2kAutomated safety check: NotesMIT
Working With Claude Code Docsobra/superpowers-developing-for-claude-code142—~1.5kAutomated safety check: PassNone
Directional Promptingkingbootoshi/directional-prompting143—~2.3kAutomated safety check: PassMIT
Agenticashibing624/agentica352—~1.8kAutomated safety check: NotesApache-2.0
Claude Code Mastery Squadohmyjahh/xquads-squads277—~1.1kAutomated safety check: PassMIT

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Categories

Questions about Refit Environment Retrospective

What does Refit Environment Retrospective do?

Reads an agent environment's own traces, friction reports and logs across sessions, then proposes fixes on the surface that owns each one, only with your approval. Refit studies the environment the agent worked in rather than the code it produced.json scripts and CI workflows.

When should I use Refit Environment Retrospective?

Refit Environment Retrospective fits situations like: after several sessions where the agent kept tripping on the same check; turning recorded friction into lint rules, hooks or doc changes; auditing which of a repo's checks are unwired or silently broken.

How do I install Refit Environment Retrospective in Claude Code?

Run `npx skills add Yeachan-Heo/oh-my-claudecode --skill refit -a claude-code`. Or copy the skill folder (skills/refit in Yeachan-Heo/oh-my-claudecode) into .claude/skills/refit in your project. Claude Code loads it when a task matches its description.

How do I install Refit Environment Retrospective in Codex?

Run `npx skills add Yeachan-Heo/oh-my-claudecode --skill refit -a codex`. Or copy the skill folder (skills/refit in Yeachan-Heo/oh-my-claudecode) into .agents/skills/refit in your project. Codex loads it when a task matches its description.

Can I use Refit Environment Retrospective in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Yeachan-Heo/oh-my-claudecode --skill refit -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/refit, .gemini/skills/refit, .github/skills/refit and .opencode/skills/refit in your project.

What does Refit Environment Retrospective need to run?

SKILL.md names no scripts, command-line tools or credentials: Refit Environment Retrospective is instructions for the agent only. Our summary lists: OMC instrumentation such as trace timelines and session friction reports.

Does Refit Environment Retrospective access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Refit Environment Retrospective safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Refit Environment Retrospective use?

Refit Environment Retrospective is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Refit Environment Retrospective use?

About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Refit Environment Retrospective?

Skills that share tags, products or a category with Refit Environment Retrospective: Agent Setup Health Audit (tw93/Waza, 7.2k stars), Working With Claude Code Docs (obra/superpowers-developing-for-claude-code, 142 stars), Directional Prompting (kingbootoshi/directional-prompting, 143 stars) and Agentica (shibing624/agentica, 352 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Refit Environment Retrospective?

Yeachan-Heo (a GitHub user) maintains it in Yeachan-Heo/oh-my-claudecode, which has 39,720 GitHub stars. The repository holds 47 skills in this directory. The repository was last updated on October 8, 2026.

Source: Yeachan-Heo/oh-my-claudecode on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.