Skill audit report
Turn on-site competitor observations into source-tagged intelligence notes and evidence-based actions.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
WARN48
48 GitHub stars
Stars/forks activity
WARN43
48 stars, 6 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
Pushed today
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add LensmorOfficial/trade-show-skills --skill trade-show-competitor-radar
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS100
no high-risk permission surface in public metadata
Repository evidence
PASS86
https://github.com/LensmorOfficial/trade-show-skills/tree/main/trade-show-competitor-radar
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add LensmorOfficial/trade-show-skills --skill trade-show-competitor-radar
Repository
88
https://github.com/LensmorOfficial/trade-show-skills/tree/main/trade-show-competitor-radar
License
86
MIT
Maintenance
100
Pushed today
AI review
55
Review approval is missing
README/SKILL.md completeness
86
Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Install command safety
92
standard package or runtime install path
Permission surface
100
no high-risk permission surface in public metadata
Stars/forks activity
43
48 stars, 6 forks; issue activity unavailable in current metadata
Adoption
42
48 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
Compare nearby options
Eliminates predictable AI writing patterns from prose while preserving specific meaning and reader trust.
16K Stars · Audit report
Applies Cursor's prose-discipline rules to remove filler and AI writing tells from agent-facing and user-facing text.
4.8K Stars · Audit report
Rewrites AI-sounding text so it reads naturally while preserving every factual claim and matching the writer's voice.
37K Stars · Audit report