Skill audit report
Use this to set up human review and annotation of LLM traces, so people (often domain experts) can label outputs, do error analysis, and build a trustworthy golden dataset. Trigger on "review my LLM outputs", "have an expert label these", "error analysis", "annotate traces", "build a golden dataset", or when automated evals are not enough for a high-stakes or specialized domain. Looking at your data is the highest-ROI thing you can do.
OpenAgentSkill Trust Score
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
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add ContextJet-ai/awesome-llm-observability --skill annotate-traces-for-review
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS88
database access
Repository evidence
PASS86
https://github.com/ContextJet-ai/awesome-llm-observability/tree/main/skills/annotate-traces-for-review
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 annotate-traces-for-review
Repository
88
https://github.com/ContextJet-ai/awesome-llm-observability/tree/main/skills/annotate-traces-for-review
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
90
no major dependency risk hints in public metadata
Install command safety
92
standard package or runtime install path
Permission surface
88
database access
Stars/forks activity
48
33 stars, 18 forks; issue activity unavailable in current metadata
Adoption
42
33 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.
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