Skill audit report
Dual AI Chat Audit report.
一个先进的聊天应用，演示了一种独特的对话范式：用户的查询首先由两个不同的人工智能角色进行辩论和提炼，然后才提供最终的综合答案。该项目利用 Google Gemini API 驱动一个逻辑型 AI (Cognito) 和一个怀疑型 AI (Muse)，它们协作生成更健壮、准确和经过严格审查的响应。
OpenAgentSkill Trust Score
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
347 GitHub stars
Stars/forks activity
INFO62
347 stars, 65 forks; issue activity unavailable in current metadata
Recent maintenance
INFO76
3mo since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS90
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS82
network or browser surface
Install availability
PASS92
npx skills add yeahhe365/Dual-AI-Chat
Install command safety
PASS92
standard package or runtime install path
Permission surface
INFO72
filesystem or document access, network or browser access
Repository evidence
PASS86
https://github.com/yeahhe365/Dual-AI-Chat
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install and adoption review
Install path
92
npx skills add yeahhe365/Dual-AI-Chat
Repository
88
https://github.com/yeahhe365/Dual-AI-Chat
License
86
MIT
Maintenance
76
3mo since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
90
Usable description available
Dependency risk
82
network or browser surface
Install command safety
92
standard package or runtime install path
Permission surface
72
filesystem or document access, network or browser access
Stars/forks activity
62
347 stars, 65 forks; issue activity unavailable in current metadata
Adoption
68
347 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Warnings
- Financial research output is not financial advice; require human review before any live investment decision
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
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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