review-skill
Skill190 starsChanged 3 months agoApache-2.0View on GitHub
Review a proposed Agent Skill for structural validity and content quality before publishing. Runs the skill-validator CLI to check for structural issues, scores the skill with an LLM judge, and interprets results to advise SMEs on what to address. Use when a user wants to review, validate, or quality-check an Agent Skill.
- Pipes a download into a shell
- Installs packages
We split this skill into the rules it gives an agent
17 rules. 0 are common, 7 are distinctive, and 10 are very specific to this project.
0
Common
Most of the 14 edited versions we read keep these.
7
Distinctive
This author's own choices. Worth a look.
10
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 20
Follow every step in order.
- Distinctive: line 24
Check for saved configuration:
- Very specific: line 59
If not found, search common locations (/usr/local/bin, /opt/homebrew/bin, ~/go/bin).
- Very specific: line 63
If --version is not at least v1.5.1, help the user upgrade with brew upgrade skill-validator or go install …
- Distinctive: line 67
Do NOT proceed until this succeeds.
- Very specific: line 71
If LLM_SCORING=true, verify the Claude CLI is available:
- Distinctive: line 77
If not found, tell the user to install Claude Code:
- Distinctive: line 80
Other platforms: follow the Claude Code quickstart guide
- Distinctive: line 84
Do NOT proceed with LLM scoring until this succeeds.
- Very specific: line 101
Ask the user for the path to the skill they want to review, unless they have already provided it.
- Very specific: line 108
If SKILL.md does not exist at the given path, tell the user this is not a valid skill directory and ask them to provide the correct path.
- Distinctive: line 113
Run the full check suite:
- Very specific: line 134
Read the SKILL.md and any reference files, then evaluate each check below.
- Very specific: line 150
If LLM_SCORING=false, skip to Step 6.
- Very specific: line 152
If LLM_SCORING=true, follow the "Run LLM Scoring" and "Interpret LLM Scores" sections of references/llm-scoring.md.
- Very specific: line 158
If LLM_SCORING=true, follow the "Full Review Summary" section of references/llm-scoring.md.
- Very specific: line 162
If LLM_SCORING=false, present structural result, content review result, areas to address, and a self-assessment checklist using the scoring …
“Common” is measured: kept by at least 6 in 10 of the 14 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
Review Skill Workflow
You are helping an SME review an Agent Skill before publishing. This is a multi-step process: determine environment, verify prerequisites, run structural validation, review content, optionally run LLM scoring, and interpret results. Follow every step in order.
Step 0: Determine Environment
Check for saved configuration:
cat ~/.config/skill-validator/review-state.yaml 2>/dev/nullIf the state file exists with prereqs_passed: true, offer:
Found saved settings — configured for [full/structural-only] reviews.
- Continue with saved settings — skip to Step 2
- Re-run prerequisite checks
- Change environment — switch between full and structural-only
Option 1: read llm_scoring from the file and skip to Step 2.
Options 2-3: continue below.
If no state file exists, or the user chose to re-check/change, ask:
LLM scoring evaluates content quality across multiple dimensions.
- Yes, run LLM scoring — full review with LLM scoring
- No, skip LLM scoring — structural validation only
Option 1: set LLM_SCORING=true.
Option 2: set LLM_SCORING=false. Run Step 1a only, then jump to Step 2.
Step 1: Verify Prerequisites
1a. Check for skill-validator binary
skill-validator --versionIf not found, search common locations (/usr/local/bin, /opt/homebrew/bin,
~/go/bin). If found but not on PATH, tell the user. If not found anywhere,
follow references/install-skill-validator.md.
If --version is not at least v1.5.1, help the user upgrade with
brew upgrade skill-validator or
go install github.com/agent-ecosystem/skill-validator/cmd/skill-validator@latest.
Do NOT proceed until this succeeds.
1b. Check for claude CLI (LLM scoring only)
If LLM_SCORING=true, verify the Claude CLI is available:
claude --versionIf not found, tell the user to install Claude Code:
- macOS:
curl -fsSL https://claude.ai/install.sh | bash - Other platforms: follow the Claude Code quickstart guide
The user must authenticate by running claude interactively before continuing.
Do NOT proceed with LLM scoring until this succeeds.
Save state after prerequisites pass
Persist state so future runs skip this step. Replace <true or false> with
the actual LLM_SCORING value:
mkdir -p ~/.config/skill-validator
cat > ~/.config/skill-validator/review-state.yaml << 'EOF'
prereqs_passed: true
llm_scoring: <true or false>
EOFStep 2: Locate the Skill
Ask the user for the path to the skill they want to review, unless they have
already provided it. Verify the path contains a SKILL.md file:
ls <path>/SKILL.mdIf SKILL.md does not exist at the given path, tell the user this is not a
valid skill directory and ask them to provide the correct path.
Step 3: Run Structural Validation
Run the full check suite:
skill-validator check <path>Capture the exit code:
| Exit code | Meaning |
| 0 | Clean — no errors or warnings |
| 1 | Errors found — must fix before publishing |
| 2 | Warnings only — review but not blocking |
| 3 | CLI/usage error — check the command |
Exit 0: proceed. Exit 2: note warnings, proceed. Exit 1: list errors — these are blocking. The user must fix them before the skill can be published. Do NOT proceed to LLM scoring if exit code is 1.
Step 4: Content Review
Read the SKILL.md and any reference files, then evaluate each check below. Report which checks pass and which do not, with specific details on what is missing.
| Check | Criteria |
| Examples | Does the skill provide examples of expected inputs and outputs? |
| Edge cases | Does the skill document common edge cases or failure modes? |
| Scope-gating | Does the skill define when to stop/continue, prerequisites, and conditions for branching paths? |
| MongoDB data access | If the skill needs MongoDB contextual data, does it instruct agents to use the MCP server for auth and tool calls? Skip if not applicable. |
Flag any failing checks as areas the SME should address. These are not blocking but should be resolved before publishing for best results.
Step 5: LLM Scoring and Interpretation
If LLM_SCORING=false, skip to Step 6.
If LLM_SCORING=true, follow the "Run LLM Scoring" and "Interpret LLM Scores"
sections of
references/llm-scoring.md.
Step 6: Present the Review Summary
If LLM_SCORING=true, follow the "Full Review Summary" section of
references/llm-scoring.md.
Include any failing content review checks from Step 4 in the action items.
If LLM_SCORING=false, present structural result, content review result,
areas to address, and a self-assessment checklist using the scoring dimensions
from assets/report.md. Note that LLM scoring was skipped;
advise re-running with LLM scoring enabled or self-assessing against the report
dimensions.
Example Review Summary Structure
Structure the final summary with these sections in order:
- Structural validation — pass/fail with errors or warnings
- SKILL.md scores — overall and per-dimension table
- Reference scores — per-file table with overall and lowest dimension
- Novelty assessment — mean novelty vs threshold of 3; list
novel_infoper file for SME verification - Action items — prioritized list of what to fix
- Recommendation — ready to publish / minor revisions / significant rework
Trending
Steady: 0 new projects took it in the last 4 weeks, none the 4 weeks before.thin data
Other versions19 projects use a version of this.
Word for word · 1
- mongodb/laravel-mongodb★ 7.1k100% same
Edited · 1
- mongodb/docs★ 77999% same
Wrote their own version · 17
- harlan-zw/skilld★ 327same name
- skilld-dev/skilld★ 324same 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
- alehlopeh/claude-skills★ 2same name
- Gidntsquia/claude-config★ 2same name
- tangjiahui-cn/skills★ 2same name
7 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 repository23 other files it gives its agents.
- mongodb-atlas-stream-processingSkill
- mongodb-connectionSkill
- mongodb-natural-language-queryingSkill
- mongodb-qe-size-estimationSkill
- mongodb-query-optimizerSkill
- mongodb-schema-designSkill
- mongodb-search-and-aiSkill
- mongodb-atlas-stream-processingSkill
- mongodb-connectionSkill
- mongodb-mcp-setupSkill
- mongodb-natural-language-queryingSkill
- mongodb-qe-size-estimationSkill
- mongodb-query-optimizerSkill
- mongodb-schema-designSkill
- mongodb-search-and-aiSkill
- mongodb-atlas-stream-processingSkill
- mongodb-connectionSkill
- mongodb-mcp-setupSkill
- mongodb-natural-language-queryingSkill
- mongodb-qe-size-estimationSkill
- mongodb-query-optimizerSkill
- mongodb-schema-designSkill
- mongodb-search-and-aiSkill
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.
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