OpenAgentSkill
GitHub200+

Pre-install eval

closed-surface-uv-coverage Eval report.

A machine-readable install decision for agents: task fit, Trust Score, Audit Score, install safety, permission surface, and a concrete validation plan before this skill touches a workspace.

Needs reviewMedium riskREVIEW Policy
63
Eval report
64
Trust
71
Audit
43
Agent safety

manual review

Test manually in an isolated workspace and compare against safer alternatives.

Required gates

Checks an agent must pass before install

Open JSON

Task fit

94

pass

Task wording matches this skill metadata.

  • Evaluate closed-surface-uv-coverage before installing it in an agent workflow
  • research
  • Research agents workflows; Claude Code teams; builders willing to evaluate younger projects

Install path

92

pass

Install handoff is available.

  • npx skills add CheshireJCat/blender --skill closed-surface-uv-coverage

Install command safety

92

pass

standard package or runtime install path

  • npx skills add CheshireJCat/blender --skill closed-surface-uv-coverage

Trust score

64

warn

Potentially useful, but at least one trust signal needs human inspection.

  • Manual review
  • 26 GitHub stars
  • MIT

Audit score

71

warn

Needs review

  • The audit script does not fully implement the acceptance gates described in SKILL.md: it only checks for image texture nodes and warns when a material slot lacks one, but does not verify generated coordinates or procedural material policies for sidewalls/back caps.

Agent safety gate

43

warn

Sparse or mixed signals. Useful for discovery, but not for autonomous installation.

  • Test manually in an isolated workspace and compare against safer alternatives.
  • High-risk permission hints: Shell or command execution

License clarity

86

pass

MIT

  • MIT

Permission surface

62

warn

shell or command execution, filesystem or document access

  • Shell or command execution: high
  • Network access: medium
  • Filesystem access: medium

Validation plan

What the agent should do next

  1. 1Inspect repository, README/SKILL.md, license, and recent commits before production use.
  2. 2Install in an isolated workspace or sandbox with no production secrets available.
  3. 3Run the smallest representative task and record files touched, commands run, network access, and outputs.
  4. 4Compare the selected skill against at least one alternative when the eval status is review or failed.
  5. 5Promote only after the agent reports a successful verification result and unresolved warnings are accepted.

Do not use when

Conditions that require another skill

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • Low GitHub adoption signal
  • The audit script does not fully implement the acceptance gates described in SKILL.md: it only checks for image texture nodes and warns when a material slot lacks one, but does not verify generated coordinates or procedural material policies for sidewalls/back caps.
  • High-risk permission hints: Shell or command execution
  • The script's default object selection is limited to names starting with 'AVATAR_BASE__' or 'SIDE_BACK__', which may not cover all use cases and could miss relevant objects in a general scene.

Supporting checks

Trust signals behind the decision

README/SKILL.md completeness

warn

76

Public metadata needs stronger README/SKILL.md context

Recent maintenance

pass

88

3mo since push

Alternatives available

info

55

No close alternatives were found in the current shortlist.