Skill audit report
Refuses "flaky" as a diagnosis. Turns an intermittent failure into a reproduction by isolating it from the environment, naming the variable that controls it, forcing that variable, and measuring before and after with enough runs to count. Separates real defects from environment contention with evidence, and never retries to green or widens a threshold. Use when a test, performance check, or deploy step fails intermittently or passes on rerun.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
WARN48
85 GitHub stars
Stars/forks activity
WARN48
85 stars, 20 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
Pushed today
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS82
database surface
Install availability
PASS92
npx skills add ash1794/vibe-engineering --skill vibe-flake-root-cause
Install command safety
PASS92
standard package or runtime install path
Permission surface
INFO74
network or browser access, database access
Repository evidence
PASS86
https://github.com/ash1794/vibe-engineering/tree/master/plugins/vibe-engineering/skills/vibe-flake-root-cause
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add ash1794/vibe-engineering --skill vibe-flake-root-cause
Repository
88
https://github.com/ash1794/vibe-engineering/tree/master/plugins/vibe-engineering/skills/vibe-flake-root-cause
License
86
MIT
Maintenance
100
Pushed today
AI review
55
Review approval is missing
README/SKILL.md completeness
86
Usable description available
Dependency risk
82
database surface
Install command safety
92
standard package or runtime install path
Permission surface
74
network or browser access, database access
Stars/forks activity
48
85 stars, 20 forks; issue activity unavailable in current metadata
Adoption
68
85 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.