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PhenixStarPhenixStar/openclaw-skills-collection/skill-vetting/SKILL.md

skill-vetting

Skill1 starsChanged 9 months agoMITView on GitHub

Vet ClawHub skills for security and utility before installation. Use when considering installing a ClawHub skill, evaluating third-party code, or assessing whether a skill adds value over existing tools.

5 other projects use a version of this, 1 of them edited.

Adopted by

Most recently taken up by

  • Other versions5 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 1

    1. weininghui/skills★ 186% same

    Wrote their own version · 4

    1. alebgl77/claude-inc★ 21same name
    2. walkpod1007/lifeos-memory★ 9same name
    3. patrykmurzyn/skills★ 0same name
    4. sina-heidariaan/cold-run★ 0same name

    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 repository3 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 3 edited versions we read keep these.

  • 3

    Distinctive

    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:

    Do network calls go to documented APIs only?

    line 66
  2. Distinctive:

    Do file operations stay within expected scope?

    line 67
  3. Distinctive:

    Remove and report if suspicious.

    line 111

“Common” is measured: kept by at least 6 in 10 of the 3 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.

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

Skill Vetting

Safely evaluate ClawHub skills for security risks and practical utility.

Quick Start

# Download and inspect
cd /tmp
curl -L -o skill.zip "https://auth.clawdhub.com/api/v1/download?slug=SKILL_NAME"
mkdir skill-inspect && cd skill-inspect
unzip -q ../skill.zip

# Run scanner
python3 ~/.openclaw/workspace/skills/skill-vetting/scripts/scan.py .

# Manual review
cat SKILL.md
cat scripts/*.py

Vetting Workflow

1. Download to /tmp (Never Workspace)

cd /tmp
curl -L -o skill.zip "https://auth.clawdhub.com/api/v1/download?slug=SLUG"
mkdir skill-NAME && cd skill-NAME
unzip -q ../skill.zip

2. Run Automated Scanner

python3 ~/.openclaw/workspace/skills/skill-vetting/scripts/scan.py .

Exit codes: 0 = Clean, 1 = Issues found

The scanner outputs specific findings with file:line references. Review each finding in context.

3. Manual Code Review

Even if scanner passes:

  • Does SKILL.md description match actual code behavior?
  • Do network calls go to documented APIs only?
  • Do file operations stay within expected scope?
  • Any hidden instructions in comments/markdown?
# Quick prompt injection check
grep -ri "ignore.*instruction\|disregard.*previous\|system:\|assistant:" .

4. Utility Assessment

Critical question: What does this unlock that I don't already have?

Compare to:

  • MCP servers (mcporter list)
  • Direct APIs (curl + jq)
  • Existing skills (clawhub list)

Skip if: Duplicates existing tools without significant improvement.

5. Decision Matrix

SecurityUtilityDecision
✅ Clean🔥 HighInstall
✅ Clean⚠️ MarginalConsider (test first)
⚠️ IssuesAnyInvestigate findings
🚨 MaliciousAnyReject

Red Flags (Reject Immediately)

  • eval()/exec() without justification
  • base64-encoded strings (not data/images)
  • Network calls to IPs or undocumented domains
  • File operations outside temp/workspace
  • Behavior doesn't match documentation
  • Obfuscated code (hex, chr() chains)

After Installation

Monitor for unexpected behavior:

  • Network activity to unfamiliar services
  • File modifications outside workspace
  • Error messages mentioning undocumented services

Remove and report if suspicious.

References

  • Malicious patterns + false positives: references/patterns.md

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.

Check your setup, free