agentleFS
kuya-eggkuya-egg/Monozukuri/jidoka/SKILL.md

jidoka

Skill11 starsChanged 2 months agoMITView on GitHub

Debug software by making failures visible, reproducing them, finding contributing causes, and adding durable regression protection. Use for bugs, failing tests, incidents, regressions, flaky behavior, and unexplained production errors.

The file

We split this skill into the rules it gives an agent

10 rules. About 0 are common, 10 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈10

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Create one reliable command, test, fixture, request, or observation that fails for the actual problem.

    line 42
  2. Distinctive:

    Read the error, inputs, state transitions, logs, traces, timing, and related code.

    line 48
  3. Distinctive:

    Ask why the failure occurred and why existing tests, types, constraints, observability, or review did not catch it.

    line 60
  4. Distinctive:

    Do not claim root cause from a plausible code reading alone.

    line 84
  5. Distinctive:

    Do not suppress a failing check to restore green status.

    line 91
  6. Distinctive:

    Do not patch only the symptom when the cause is observable.

    line 92
  7. Distinctive:

    Do not perform unrelated cleanup while the feedback loop is broken.

    line 93
  8. Distinctive:

    Do not declare “cannot reproduce” without recording what was tried and what evidence is missing.

    line 94
  9. Distinctive:

    Do not leave a known high-impact defect invisible because it was inherited.

    line 96
  10. Distinctive:

    If a referenced skill is not installed, apply its named lens inline instead of trying to invoke it.

    line 104

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Jidoka

Jidoka is the stop-the-line discipline: when a meaningful defect appears, make it visible and understand it before allowing more work or releases to build on it. It is a Japanese-inspired engineering metaphor for quality at the source, not a promise that every minor imperfection stops all work forever.

Use this skill when

  • a test, build, type check, migration, or invariant fails;
  • behavior is incorrect, flaky, slow, or unexplained;
  • a regression or production incident needs diagnosis;
  • an existing workaround hides a recurring problem; or
  • a fix is tempting but the cause is not yet understood.

Outcome

Produce a verified root-cause fix with:

  • a tight reproduction or a clear explanation of why reproduction is blocked;
  • observations separated from hypotheses;
  • experiments that distinguish plausible causes;
  • the contributing cause and why the system allowed it;
  • the narrowest safe fix;
  • regression protection or durable diagnostic evidence; and
  • explicit results and residual risk.

Workflow

1. Stop and frame

State the failure, impact, affected boundary, and current known-good or known-bad evidence. Do not start with a broad refactor or a preferred theory.

2. Reproduce

Create one reliable command, test, fixture, request, or observation that fails for the actual problem. If the failure is intermittent, capture the smallest useful signal and improve the feedback loop before guessing.

3. Observe

Read the error, inputs, state transitions, logs, traces, timing, and related code. Instrument only what distinguishes hypotheses. Treat symptoms as clues, not causes.

4. Test hypotheses

List plausible causes and run the cheapest experiment that can eliminate one. Change one relevant variable at a time. Stop using a hypothesis when evidence contradicts it.

5. Find the contributing cause

Ask why the failure occurred and why existing tests, types, constraints, observability, or review did not catch it. Use Five Whys when it exposes a missing guardrail; do not use it to invent blame or a single simplistic cause.

6. Fix and protect

Make the smallest fix at the right boundary. Add a regression test, invariant, diagnostic, or process guardrail that would fail if the problem returns.

7. Verify the stop is over

Rerun the reproduction, targeted checks, and broader checks appropriate to the risk. Confirm that the fix does not mask an adjacent failure.

Autonomous correction boundary

During the edit phase, fix compile errors, test failures, and minor defects introduced by your own change when the intended behavior is clear. Stop for human input only when requirements or architecture are ambiguous, a new authorization is required, a destructive action is involved, or the evidence reveals a conflict that cannot be resolved safely.

Evidence standard

Do not claim root cause from a plausible code reading alone. Show the failing case before the fix, the result after the fix, and the checks that cover the changed boundary. Every verification claim must be traceable to an executed command, observed result, or authoritative evidence.

Boundaries

  • Do not suppress a failing check to restore green status.
  • Do not patch only the symptom when the cause is observable.
  • Do not perform unrelated cleanup while the feedback loop is broken.
  • Do not declare “cannot reproduce” without recording what was tried and what evidence is missing.
  • Do not leave a known high-impact defect invisible because it was inherited.

Handoff

Report the failure, cause, fix, regression protection, verification, and any remaining uncertainty. Use poka-yoke for stronger prevention, andon for diagnostics, or hansei when the failure reveals a process or system gap.

If a referenced skill is not installed, apply its named lens inline instead of trying to invoke it.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.