Skill audit report

Ml Workspace audit report.

馃洜 All-in-one web-based IDE specialized for machine learning and data science.

REVIEWEDREVIEWNeeds reviewGenerated Jun 16, 2026Heuristic metadata audit
77
Audit
81
Trust
76
Quality
95
Security
38
Maintain
92
Install

OpenAgentSkill Trust Score

81
Strong shortlist

Stars, maintenance, license, docs, dependency risk, 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

PASS

86

3.5K GitHub stars

Recent maintenance

FAIL

38

2y since push

License clarity

PASS

86

Apache-2.0

README/SKILL.md completeness

INFO

74

Public metadata needs stronger README/SKILL.md context

Dependency risk

INFO

80

external package install surface

Install availability

PASS

92

npx skills add ml-tooling/ml-workspace

Repository evidence

PASS

86

https://github.com/ml-tooling/ml-workspace

Review status

PASS

88

AI review data available

Checks

Install and adoption review

7 passed 路 5 review

Install path

92

PASS

npx skills add ml-tooling/ml-workspace

Repository

88

PASS

https://github.com/ml-tooling/ml-workspace

License

86

PASS

Apache-2.0

Maintenance

38

FIX

2y since push

AI review

88

PASS

Approved with no listed issues

README/SKILL.md completeness

84

PASS

Usable description available

Dependency risk

80

PASS

external package install surface

Adoption

88

PASS

3.5K GitHub stars

Warnings

  • Repository appears stale
  • Repository looks stale
  • Quality score needs review
  • Recent maintenance: 2y since push

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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