Skill audit report
当用户需要把游戏体验浓度、留存、首局节奏、Demo 完成率、单机总旅程、D1/D7、反馈、具身感、氛围、认知负荷、最佳刺激窗口、FEP/free-energy、预测误差、Markov blanket、习惯化或 liveops 参与问题，编译成可上线、可埋点、可复盘、可回滚的一周 ED 实验包时使用。Use when converting game experience-density and engagement problems into rollback-ready ED experiments.
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
378 GitHub stars
Stars/forks activity
WARN57
378 stars, 44 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
22d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
INFO76
Public metadata needs stronger README/SKILL.md context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add DY-2026/GameDesignOS --skill game-experience-density-optimizer
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS88
database access
Repository evidence
PASS86
https://github.com/DY-2026/GameDesignOS/tree/main/game-experience-density-optimizer
Review status
INFO66
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add DY-2026/GameDesignOS --skill game-experience-density-optimizer
Repository
88
https://github.com/DY-2026/GameDesignOS/tree/main/game-experience-density-optimizer
License
86
MIT
Maintenance
100
22d since push
AI review
55
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.
README/SKILL.md completeness
84
Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Install command safety
92
standard package or runtime install path
Permission surface
88
database access
Stars/forks activity
57
378 stars, 44 forks; issue activity unavailable in current metadata
Adoption
68
378 GitHub stars
Warnings
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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