Skill audit report
atmquant由公众号“堂主的ATMQuant"开发，是基于vnpy框架的AI量化交易平台，专注于AI量化投资、指标信号可视化与策略研发和回测，有完整教学和实战案例，适合量化交易初学者、金融从业者、程序员、投资爱好者
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
WARN48
96 GitHub stars
Stars/forks activity
WARN48
96 stars, 44 forks; issue activity unavailable in current metadata
Recent maintenance
INFO76
5mo since push
License clarity
WARN42
Unknown
README/SKILL.md completeness
PASS90
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add seasonstar/atmquant
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/seasonstar/atmquant
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add seasonstar/atmquant
Repository
88
https://github.com/seasonstar/atmquant
License
45
Unknown
Maintenance
76
5mo since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
90
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
86
filesystem or document access
Stars/forks activity
48
96 stars, 44 forks; issue activity unavailable in current metadata
Adoption
68
96 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
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.