Skill audit report

Embeddedml audit report.

Notes on Machine Learning on edge for embedded/sensor/IoT uses

REVIEWED · REVIEWNeeds reviewGenerated Jul 3, 2026Heuristic metadata audit

Audit

Trust

Quality

Security

100

Maintain

Install

OpenAgentSkill Trust Score

Strong shortlist

Stars, maintenance, license, docs, install safety, permission surface, and installability.

The Trust Score is OpenAgentSkill's adoption layer. It is designed to help an agent decide whether a skill is safe enough to shortlist before installation.

GitHub adoption

INFO

310 GitHub stars

Stars/forks activity

WARN

310 stars, 37 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

100

11d since push

License clarity

WARN

Unknown

README/SKILL.md completeness

INFO

Public metadata needs stronger README/SKILL.md context

Dependency/runtime risk

PASS

no major dependency risk hints in public metadata

Install availability

PASS

npx skills add jonnor/embeddedml

Install command safety

PASS

standard package or runtime install path

Permission surface

INFO

filesystem or document access, network or browser access

Repository evidence

PASS

https://github.com/jonnor/embeddedml

Review status

PASS

AI review data available

Agent Proven outcomes

INFO

No agent outcome data yet

Checks

Install and adoption review

7 passed · 7 review

Install path

PASS

npx skills add jonnor/embeddedml

Repository

PASS

https://github.com/jonnor/embeddedml

License

CHECK

Unknown

Maintenance

100

PASS

11d since push

AI review

PASS

Approved with no listed issues

README/SKILL.md completeness

PASS

Usable description available

Dependency risk

PASS

no major dependency risk hints in public metadata

Install command safety

PASS

standard package or runtime install path

Permission surface

CHECK

filesystem or document access, network or browser access

Stars/forks activity

FIX

310 stars, 37 forks; issue activity unavailable in current metadata

Adoption

INFO

310 GitHub stars

Warnings

License is unclear
Quality score needs review
Stars/forks activity: 310 stars, 37 forks; issue activity unavailable in current metadata
License clarity: Unknown

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.

Install path

Review the report before installing into production agents.

$ npx skills add jonnor/embeddedml

Agent-readable metadata

Machine decision packet

Embedded JSON exposes suited tasks, suited agents, install command, trust score, safety gate, alternatives, and do-not-use conditions for agent review.

Install policy: review
Best agents: Jupyter Notebook + Machine Learning
Alternatives: 3

Open agent JSON

Signals

Audit score: 82/100
Quality: 77/100
Trust: 76/100
Install safety: 92/100
Permission surface: 72/100
Maintenance: 11d since push
Events: 1 events
GitHub stars: 310
Last push: Jun 22, 2026

Agent safety v2

66/100 · Review before install

Reviewed with permission notesreview

Usable candidate, but the agent should surface permission and audit notes before installation.

Require human approval before installing into a real workspace.

License is unclear
66/100 agent safety score

Network access

medium

Skill likely fetches remote pages, APIs, repositories, or external services.

Filesystem access

medium

Skill may read or write project files, documents, generated artifacts, or local workspace state.

License is unclear

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Embeddedml audit report.

Stars, maintenance, license, docs, install safety, permission surface, and installability.

Install and adoption review

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