Skill audit report
Use this when adding tracing/observability to an LLM or AI-agent application - capturing prompts, tool calls, token usage, latency, and cost per step. Trigger whenever someone wants to "add tracing", "instrument", "monitor", "see what my agent is doing", or debug an LLM app in production. Prefer vendor-neutral OpenTelemetry unless a specific platform is already in use.
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
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
INFO72
credential or environment access
Install availability
PASS92
npx skills add ContextJet-ai/awesome-llm-observability --skill instrument-llm-observability
Install command safety
PASS92
standard package or runtime install path
Permission surface
WARN60
secrets or environment access, filesystem or document access
Repository evidence
PASS86
https://github.com/ContextJet-ai/awesome-llm-observability/tree/main/skills/instrument-llm-observability
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 instrument-llm-observability
Repository
88
https://github.com/ContextJet-ai/awesome-llm-observability/tree/main/skills/instrument-llm-observability
License
86
CC0-1.0
Maintenance
100
10d since push
AI review
55
Review approval is missing
README/SKILL.md completeness
86
Usable description available
Dependency risk
72
credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
60
secrets or environment access, filesystem or document 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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