Skill audit report
Notes on Machine Learning on edge for embedded/sensor/IoT uses
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
310 GitHub stars
Stars/forks activity
WARN57
310 stars, 37 forks; issue activity unavailable in current metadata
Recent maintenance
PASS88
3mo since push
License clarity
WARN42
Unknown
README/SKILL.md completeness
INFO74
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 jonnor/embeddedml
Install command safety
PASS92
standard package or runtime install path
Permission surface
INFO72
filesystem or document access, network or browser access
Repository evidence
PASS86
https://github.com/jonnor/embeddedml
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add jonnor/embeddedml
Repository
88
https://github.com/jonnor/embeddedml
License
45
Unknown
Maintenance
88
3mo since push
AI review
88
Approved with no listed issues
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
72
filesystem or document access, network or browser access
Stars/forks activity
57
310 stars, 37 forks; issue activity unavailable in current metadata
Adoption
68
310 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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