Skill audit report
Use this to pick or switch the LLM behind a feature, based on evidence instead of hype or the newest release. Trigger on "which model should I use", "is GPT/Claude/Gemini/Llama better for this", "should I switch models", "can a cheaper model do this", "compare models for my use case". Evaluate on YOUR task, not on leaderboards alone.
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
WARN48
33 GitHub stars
Stars/forks activity
WARN48
33 stars, 18 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
10d since push
License clarity
PASS86
CC0-1.0
README/SKILL.md completeness
INFO76
Public metadata needs stronger README/SKILL.md context
Dependency/runtime risk
INFO72
credential or environment access
Install availability
PASS92
npx skills add ContextJet-ai/awesome-llm-observability --skill compare-llm-models
Install command safety
PASS92
standard package or runtime install path
Permission surface
INFO74
secrets or environment access
Repository evidence
PASS86
https://github.com/ContextJet-ai/awesome-llm-observability/tree/main/skills/compare-llm-models
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add ContextJet-ai/awesome-llm-observability --skill compare-llm-models
Repository
88
https://github.com/ContextJet-ai/awesome-llm-observability/tree/main/skills/compare-llm-models
License
86
CC0-1.0
Maintenance
100
10d since push
AI review
55
Review approval is missing
README/SKILL.md completeness
84
Usable description available
Dependency risk
72
credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
74
secrets or environment access
Stars/forks activity
48
33 stars, 18 forks; issue activity unavailable in current metadata
Adoption
42
33 GitHub stars
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.
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