Skill audit report
Design and review agent runtime observability and model/provider fault tolerance. Use when adding metrics, traces, cost tracking, audit alignment, structured runtime events, model fallback, structured output repair, refusal handling, provider timeouts, or local execution tree diagnostics.
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
WARN48
28 GitHub stars
Stars/forks activity
WARN43
28 stars, 0 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
16d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
INFO76
Public metadata needs stronger README/SKILL.md context
Dependency/runtime risk
WARN54
command execution surface, credential or environment access
Install availability
PASS92
npx skills add HsienW/ai-agent-engineering-playbook --skill agent-observability-fault-tolerance
Install command safety
PASS92
standard package or runtime install path
Permission surface
WARN50
secrets or environment access, shell or command execution
Repository evidence
PASS86
https://github.com/HsienW/ai-agent-engineering-playbook/tree/master/skills-runtime-governance/agent-observability-fault-tolerance
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add HsienW/ai-agent-engineering-playbook --skill agent-observability-fault-tolerance
Repository
88
https://github.com/HsienW/ai-agent-engineering-playbook/tree/master/skills-runtime-governance/agent-observability-fault-tolerance
License
86
MIT
Maintenance
100
16d since push
AI review
55
Review approval is missing
README/SKILL.md completeness
84
Usable description available
Dependency risk
54
command execution surface, credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
50
secrets or environment access, shell or command execution
Stars/forks activity
43
28 stars, 0 forks; issue activity unavailable in current metadata
Adoption
42
28 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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