Skill audit report

T81 558 Deep Learning audit report.

T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis

REVIEWEDREVIEWSafe to tryGenerated Jun 16, 2026Heuristic metadata audit
92
Audit
90
Trust
98
Quality
89
Security
88
Maintain
92
Install

OpenAgentSkill Trust Score

90
Production candidate

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

94

5.7K GitHub stars

Recent maintenance

PASS

88

2mo since push

License clarity

WARN

42

Unknown

README/SKILL.md completeness

PASS

90

Metadata includes enough usage and workflow context

Dependency risk

PASS

90

no major dependency risk hints in public metadata

Install availability

PASS

92

npx skills add jeffheaton/t81_558_deep_learning

Repository evidence

PASS

86

https://github.com/jeffheaton/t81_558_deep_learning

Review status

PASS

88

AI review data available

Checks

Install and adoption review

7 passed 路 3 review

Install path

92

PASS

npx skills add jeffheaton/t81_558_deep_learning

Repository

88

PASS

https://github.com/jeffheaton/t81_558_deep_learning

License

45

CHECK

Unknown

Maintenance

88

PASS

2mo since push

AI review

88

PASS

Approved with no listed issues

README/SKILL.md completeness

90

PASS

Usable description available

Dependency risk

90

PASS

no major dependency risk hints in public metadata

Adoption

88

PASS

5.7K GitHub stars

Warnings

  • License is unclear
  • 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.

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