Skill audit report

Mlscraper audit report.

馃 Scrape data from HTML websites automatically by just providing examples

EXPERIMENTALREVIEWNeeds reviewGenerated Jun 16, 2026Heuristic metadata audit
69
Audit
75
Trust
67
Quality
87
Security
20
Maintain
92
Install

OpenAgentSkill Trust Score

75
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

1.4K GitHub stars

Recent maintenance

FAIL

22

2y since push

License clarity

WARN

42

Unknown

README/SKILL.md completeness

PASS

84

Metadata includes enough usage and workflow context

Dependency risk

PASS

82

network or browser surface

Install availability

PASS

92

npx skills add lorey/mlscraper

Repository evidence

PASS

86

https://github.com/lorey/mlscraper

Review status

PASS

88

AI review data available

Checks

Install and adoption review

6 passed 路 8 review

Install path

92

PASS

npx skills add lorey/mlscraper

Repository

88

PASS

https://github.com/lorey/mlscraper

License

45

CHECK

Unknown

Maintenance

20

FIX

2y since push

AI review

88

PASS

Approved with no listed issues

README/SKILL.md completeness

84

PASS

Usable description available

Dependency risk

82

PASS

network or browser surface

Adoption

88

PASS

1.4K GitHub stars

Warnings

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