review-skill
Skill0 starsChanged 8 months agoUnlicenseView on GitHub
Reviews a SKILL.md file or skill directory for quality, correctness, and alignment with Claude Code skill conventions. Use when you've written a new skill and want to check it before committing, or when evaluating an existing skill for improvements.
21 other projects use a version of this.
Adopted by
Most recently taken up by
- rafapeixer/go-skillstheir own version, first seen Nov 15, 2026
- rafapeixer/db-skillstheir own version, first seen Nov 8, 2026
- mongodb/docstheir own version, first seen Nov 2, 2026
- rafapeixer/java-skillstheir own version, first seen Oct 20, 2026
- runxhq/runxtheir own version, first seen Oct 13, 2026
- mongodb/agent-skillstheir own version, first seen Oct 13, 2026
Other versions21 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 21
- mongodb/laravel-mongodb★ 7.1ksame name
- mongodb/docs★ 780same name
- harlan-zw/skilld★ 327same name
- skilld-dev/skilld★ 324same name
- mongodb/agent-skills★ 198same name
- runxhq/runx★ 97same name
- aviz85/claude-skills-library★ 49same name
- mixpanel/ai-plugins★ 18same name
- geemus/hax-yax★ 4same name
- XAzer-R/azer-feilian-director★ 4same name
11 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository12 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- agent-optimizeSkill
- dev-recordSkill
- flesh-outSkill
- generator-codingSkill
- light-v-structureSkill
- no-pre-existing-failuresSkill
- review-stepsSkill
- sandboxSkill
- sdlc-cross-reviewSkill
- strong-editSkill
- my-skillSkill
The file
We split this skill into the rules it gives an agent
10 rules. 0 are common, 8 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 17 edited versions we read keep these.
8
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 23
Read the target SKILL.md at $ARGUMENTS (and any supporting files in the directory).
- Distinctive: line 29
Check that frontmatter is well-formed and follows conventions:
- Distinctive: line 46
Check the prompt body for structural quality:
- Distinctive: line 61
Check that the skill will work well in practice:
- Very specific: line 67
If the skill uses $ARGUMENTS, does it handle missing or invalid arguments gracefully?
- Distinctive: line 69
Do reference files over 100 lines include a table of contents so Claude can see their full scope?
- Distinctive: line 73
No review pauses in a multi-stage workflow
- Distinctive: line 83
If the skill is intended for this repo's skill library, check alignment with existing skills:
- Distinctive: line 93
If the skill is standalone (not for this repo), skip repo-specific alignment checks and note this.
- Distinctive: line 105
If the skill will be used across model tiers (Haiku, Sonnet, Opus), flag whether instructions are explicit enough for smaller models — what …
“Common” is measured: kept by at least 6 in 10 of the 17 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
This skill reviews and fixes other skills — identifying issues and applying corrections with developer approval at each stage.
Stop after each stage and have changes reviewed with the user.
Note: The agent checks skills against conventions and best practices, then proposes fixes. The developer approves before changes are applied. When uncertain about intent, ask — don't assume.
See
responsibilities.mdfor the full agent vs developer ownership matrix.
Each stage produces a checklist of findings (pass / issue / suggestion) and proposes fixes for any issues found. Stage 5 delivers an overall quality assessment and publish/revise/rethink recommendation.
- Read and understand the skill (agent proposes, developer confirms)
- Read the target
SKILL.mdat$ARGUMENTS(and any supporting files in the directory). If no argument was provided, ask the user which skill to review. - Summarize: what does this skill do, when is it invoked, and what workflow does it follow?
- Confirm understanding before proceeding to review
- Read the target
Frontmatter review (agent reviews, then fixes with developer approval)
Check that frontmatter is well-formed and follows conventions:
- Is
namekebab-case and does it match the directory name? - Is
descriptionpresent, specific enough to trigger correctly, and does it include when-to-use context? - Are invocation control fields appropriate for the skill's purpose?
- Side-effect workflows should use
disable-model-invocation: true - Background knowledge should use
user-invocable: false
- Side-effect workflows should use
- Is
allowed-toolsset if the skill should restrict tool access? - Is
argument-hintpresent if the skill uses$ARGUMENTS? - Is the
descriptionwritten in third person? (descriptions are injected into the system prompt — third person reads naturally there) - Are
context/agentset appropriately if the skill runs in isolation? - Are there unknown or misspelled frontmatter fields?
Report findings as a checklist: pass / issue / suggestion. Then apply fixes for any issues, with developer approval.
- Is
Prompt structure review (agent reviews, then fixes with developer approval)
Check the prompt body for structural quality:
- Does it have a stop-after-each-stage instruction if it's a multi-stage workflow?
- Is there a Stage 0 for understanding/confirmation before doing work?
- Are agent vs developer responsibilities clear at each stage?
- Does it use questions to guide analysis, not just imperatives?
- Is the skill under 500 lines? Does it reference supporting files for detail rather than inlining everything?
- Does the skill specify what artifacts or outputs it produces and in what format? (reports, checklists, files, modified documents)
- Are file references at most one level deep from SKILL.md? (no file→file→file chains — Claude may partially read nested references)
- Is the stage numbering consistent and logical?
Report findings as a checklist: pass / issue / suggestion. Then apply fixes for any issues, with developer approval.
Effectiveness review (agent reviews, then fixes with developer approval)
Check that the skill will work well in practice:
- Are instructions unambiguous — will Claude interpret them correctly?
- Is the scope right-sized? (Not trying to do too much in one skill)
- Are
$ARGUMENTS,$0,$1used correctly if present? - Is dynamic context (exclamation-mark backtick syntax) used correctly if present?
- If the skill uses
$ARGUMENTS, does it handle missing or invalid arguments gracefully? (prompt the user, show usage, or fail with a clear message) - Does the skill address what happens when it encounters an error or unexpected state? (validation, recovery, or clear reporting — not every skill needs elaborate handling, but it shouldn't leave the developer guessing)
- Do reference files over 100 lines include a table of contents so Claude can see their full scope?
- Are supporting files referenced from
SKILL.md? - Check for anti-patterns:
- Overly broad or narrow description
- No review pauses in a multi-stage workflow
- Unreferenced supporting files in the directory
- Task instructions in a skill with no
context: forkand no clear action - Deeply nested file references (file→file→file chains that Claude may not follow)
- Agent escape hatches: Soft language ("where appropriate", "if you have a clear fix", "as needed") that lets the agent skip required work. Completion gates must use hard prerequisites, not discretionary phrasing. Look for: conditional qualifiers on mandatory steps, missing definitions of done, and loops without explicit exit criteria.
Report findings as a checklist: pass / issue / suggestion. Then apply fixes for any issues, with developer approval.
Alignment review (agent reviews, then fixes with developer approval)
If the skill is intended for this repo's skill library, check alignment with existing skills:
- Consistent formatting with other skills in the repo?
- Blockquotes for philosophy notes
- Bold for stage titles
- Tables for comparisons
- Includes "When to use this vs other skills" if it overlaps with existing skills?
- Follows the composition model (flesh-out -> review-steps -> strong-edit -> agent-optimize)?
- Has a
responsibilities.mdif it's a multi-stage workflow with mixed agent/developer ownership?
If the skill is standalone (not for this repo), skip repo-specific alignment checks and note this.
Report findings as a checklist: pass / issue / suggestion. Then apply fixes for any issues, with developer approval.
- Consistent formatting with other skills in the repo?
Summary and recommendations (agent leads)
Provide a final summary:
- Overall quality assessment (ready to use / needs minor fixes / needs rework)
- Top 3 issues to address (if any)
- Top 3 strengths (what the skill does well)
- Recommendation: publish / revise / rethink
- If the skill will be used across model tiers (Haiku, Sonnet, Opus), flag whether instructions are explicit enough for smaller models — what works for Opus may need more detail for Haiku
When to Use This vs Other Skills
| Goal | Use |
| Review a document for polish | review-steps |
| Review a document for substantive critique | strong-edit |
| Review a SKILL.md for quality and conventions | review-skill |
| Create a new skill from scratch | Start with _template, then review-skill the result |
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.

