OpenAgentSkill
GitHub200+

Pre-install eval

game-experience-density-optimizer 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
71
Eval report
72
Trust
77
Audit
61
Agent safety

manual review

Require human approval before installing into a real workspace.

Required gates

Checks an agent must pass before install

Open JSON

Task fit

84

pass

Task wording matches this skill metadata.

  • Evaluate game-experience-density-optimizer before installing it in an agent workflow
  • automation
  • Browser automation workflows; Claude Code teams; builders willing to evaluate younger projects

Install path

92

pass

Install handoff is available.

  • npx skills add DY-2026/GameDesignOS --skill game-experience-density-optimizer

Install command safety

92

pass

standard package or runtime install path

  • npx skills add DY-2026/GameDesignOS --skill game-experience-density-optimizer

Trust score

72

warn

Good trust signals with a few areas worth checking before rollout.

  • Strong shortlist
  • 378 GitHub stars
  • MIT

Audit score

77

warn

Needs review

  • SKILL.md references `references/evidence-gate.zh-CN.md` and `templates/experiment-plan.schema.json`, but these files are not present in the submitted skill directory.

Agent safety gate

61

warn

Usable candidate, but the agent should surface permission and audit notes before installation.

  • Require human approval before installing into a real workspace.
  • SKILL.md references `references/evidence-gate.zh-CN.md` and `templates/experiment-plan.schema.json`, but these files are not present in the submitted skill directory.

License clarity

86

pass

MIT

  • MIT

Permission surface

88

pass

database access

  • Network access: medium
  • Database 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
  • SKILL.md references `references/evidence-gate.zh-CN.md` and `templates/experiment-plan.schema.json`, but these files are not present in the submitted skill directory.
  • The SKILL.md excerpt appears truncated at the `weekly_ab_plan` output contract (`handoff_checkli`); the full file should be verified so all output contracts are complete.
  • Quality score needs review
  • Stars/forks activity: 378 stars, 44 forks; issue activity unavailable in current metadata

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

pass

82

Alternative skills are available for comparison.