Line Segmentation Algorithm To Gcp Vision Audit Report | OpenAgentSkill | OpenAgentSkill

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Skills/Line Segmentation Algorithm To Gcp Vision/Audit

Skill audit report

Line Segmentation Algorithm To Gcp Vision audit report.

Line segmentation algorithm for Google Vision API.

REVIEWED · REVIEWNeeds reviewGenerated Jul 21, 2026Heuristic metadata audit

79

Audit

74

Trust

71

Quality

85

Security

88

Maintain

92

Install

OpenAgentSkill Trust Score

74

Strong shortlist

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

The skill layer for AI agents: discover, compare, audit, and install reusable capabilities across Codex, Claude Code, Cursor, and agent runtimes.

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Trust

Compare Safety Gate Skills Registry Rankings Outcomes Audits Official Weekly Reports Monthly Index State of Agent Skills vs skills.sh AgentSkills.io Alternative

Build

Docs About OpenAgentSkill API llms.txt OpenAPI CLI Creator Kit X Growth Kit Submit Blog Guides Activity

OpenAgentSkill Registry

PrivacyBuilt for agent-native discovery

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

WARN

48

96 GitHub stars

Stars/forks activity

WARN

48

96 stars, 36 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

88

2mo since push

License clarity

PASS

86

Apache-2.0

README/SKILL.md completeness

INFO

74

Public metadata needs stronger README/SKILL.md context

Dependency/runtime risk

PASS

82

network or browser surface

Install availability

PASS

92

npx skills add sshniro/line-segmentation-algorithm-to-gcp-vision

Install command safety

PASS

92

standard package or runtime install path

Permission surface

INFO

72

filesystem or document access, network or browser access

Repository evidence

PASS

86

https://github.com/sshniro/line-segmentation-algorithm-to-gcp-vision

Review status

PASS

88

AI review data available

Agent Proven outcomes

INFO

54

No agent outcome data yet

Checks

Install and adoption review

8 passed · 5 review

Install path

92

PASS

npx skills add sshniro/line-segmentation-algorithm-to-gcp-vision

Repository

88

PASS

https://github.com/sshniro/line-segmentation-algorithm-to-gcp-vision

License

86

PASS

Apache-2.0

Maintenance

88

PASS

2mo 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

Install command safety

92

PASS

standard package or runtime install path

Permission surface

72

CHECK

filesystem or document access, network or browser access

Stars/forks activity

48

FIX

96 stars, 36 forks; issue activity unavailable in current metadata

Adoption

68

INFO

96 GitHub stars

Warnings

Quality score needs review
GitHub adoption: 96 GitHub stars
Stars/forks activity: 96 stars, 36 forks; issue activity unavailable in current metadata

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 sshniro/line-segmentation-algorithm-to-gcp-vision

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: Kotlin + Invoice
Alternatives: 3

Open agent JSON

Signals

Audit score: 79/100
Quality: 71/100
Trust: 74/100
Install safety: 92/100
Permission surface: 72/100
Maintenance: 2mo since push
Events: 2 events
GitHub stars: 96
Last push: Jun 6, 2026

Agent safety v2

63/100 · 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.

Quality score needs review
63/100 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.

Quality score needs review

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