Skill audit report
Use this to make an LLM app resilient to provider failures, rate limits, timeouts, and outages. Trigger on "handle LLM API errors", "add retries/fallbacks", "the app breaks when OpenAI is down", "rate limit errors", "make my LLM calls reliable", "timeout handling". Add retries, timeouts, and model/provider fallbacks, and observe them so failures are visible.
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
26d since push
License clarity
PASS86
CC0-1.0
README/SKILL.md completeness
INFO76
Public metadata needs stronger README/SKILL.md context
Dependency/runtime risk
INFO64
credential or environment access, network or browser surface
Install availability
PASS92
npx skills add ContextJet-ai/awesome-llm-observability --skill add-llm-fallbacks
Install command safety
PASS92
standard package or runtime install path
Permission surface
WARN60
secrets or environment access, network or browser access
Repository evidence
PASS86
https://github.com/ContextJet-ai/awesome-llm-observability/tree/main/skills/add-llm-fallbacks
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 add-llm-fallbacks
Repository
88
https://github.com/ContextJet-ai/awesome-llm-observability/tree/main/skills/add-llm-fallbacks
License
86
CC0-1.0
Maintenance
100
26d since push
AI review
55
Review approval is missing
README/SKILL.md completeness
84
Usable description available
Dependency risk
64
credential or environment access, network or browser surface
Install command safety
92
standard package or runtime install path
Permission surface
60
secrets or environment access, network or browser 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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