kodawari
Skill11 starsChanged 2 months agoMITView on GitHub
Review software with careful attention to correctness, maintainability, security, operations, and meaningful detail. Use for diffs, branches, pull requests, architecture decisions, or final quality checks.
In this repository13 other files it gives its agents.
- andonSkill
- genchi-genbutsuSkill
- hanseiSkill
- jidokaSkill
- kaizenSkill
- kansoSkill
- kataSkill
- monozukuri-blueprintSkill
- monozukuri-coreSkill
- monozukuri-routerSkill
- nemawashiSkill
- poka-yokeSkill
- shukkaSkill
The file
We split this skill into the rules it gives an agent
9 rules. About 0 are common, 9 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈9
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
- Distinctive: line 42
Look for accidental edits, scope creep, dead code, duplicate logic, hidden behavior changes, confusing names, unsafe defaults, and …
- Distinctive: line 69
Use repository conventions and the task's contract as the authority.
- Distinctive: line 75
Every finding must point to a concrete line, path, behavior, test, or unverified assumption.
- Distinctive: line 82
Do not rewrite the implementation while reviewing it.
- Distinctive: line 83
Do not report style preferences as correctness defects.
- Distinctive: line 84
Do not approve based only on compilation or a happy-path test.
- Distinctive: line 85
Do not demand speculative abstractions, documentation, or scale.
- Distinctive: line 86
Do not hide a blocker to keep the review pleasant.
- Distinctive: line 95
If a referenced skill is not installed, apply its named lens inline instead of trying to invoke it.
≈ “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.
Files
Kodawari
Kodawari is careful attention to meaningful detail. In software, quality is often carried by small choices: a truthful name, a preserved invariant, an actionable error, a useful test, or a log that makes an incident diagnosable. This is a Japanese-inspired engineering metaphor, not perfectionism for its own sake.
Use this skill when
- reviewing a diff, branch, pull request, or release candidate;
- checking an implementation against a specification;
- evaluating maintainability or an architectural decision;
- preparing a greenfield vertical slice for handoff; or
- a change “works” but its long-term quality is uncertain.
Outcome
Produce a prioritized review with:
- actionable findings supported by file-level or behavior-level evidence;
- correctness, security, data, compatibility, performance, and operability risks considered;
- missing tests, error paths, documentation, or observability identified;
- optional style preferences separated from defects; and
- a clear approval boundary and residual risk.
Workflow
1. Re-read the contract
State the requested behavior, non-goals, constraints, and verification evidence. Compare the change with the actual task, not an imagined improvement.
2. Inspect the diff
Look for accidental edits, scope creep, dead code, duplicate logic, hidden behavior changes, confusing names, unsafe defaults, and generated excess. Trace changed code into callers, data, configuration, and deployment paths.
3. Review the quality axes
Check, as relevant:
- behavior and edge cases;
- authentication, authorization, input handling, secrets, and data exposure;
- API, schema, migration, and compatibility contracts;
- error handling, retries, idempotency, and failure containment;
- performance only where evidence or risk justifies it;
- tests that prove behavior and regressions;
- logs, metrics, traces, health, and recovery signals;
- documentation and decisions future maintainers must know; and
- rollback or removal paths.
4. Rank findings
Lead with defects that can cause incorrect behavior, data loss, security impact, outage, incompatibility, or unmaintainable coupling. Explain the condition, impact, evidence, and smallest useful fix. Do not bury a blocking finding beneath a list of preferences.
5. Reconcile standards and intent
Use repository conventions and the task's contract as the authority. Do not reject a clear, safe solution because it differs from personal taste. Do not approve known risk merely because it existed before the change.
Evidence standard
Every finding must point to a concrete line, path, behavior, test, or unverified assumption. Say what was checked and what could not be checked. Verification claims must be traceable to an executed command, observed result, or authoritative evidence.
Boundaries
- Do not rewrite the implementation while reviewing it.
- Do not report style preferences as correctness defects.
- Do not approve based only on compilation or a happy-path test.
- Do not demand speculative abstractions, documentation, or scale.
- Do not hide a blocker to keep the review pleasant.
Handoff
End with findings ordered by impact, checks performed, missing evidence, and
the minimum changes needed for confidence. Use andon for operational gaps,
poka-yoke for missing prevention, kaizen for safe cleanup, or shukka
when the reviewed change is a release candidate.
If a referenced skill is not installed, apply its named lens inline instead of trying to invoke it.
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
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.

