Skill comparison

Compare agent skills before installing.

Put high-signal skills side by side and inspect quality, adoption, freshness, install readiness, use-case fit, and warnings in one place.

Comparing 4 skills

Use this as a shortlist, then open the skill detail page before adopting.

Add more skills

Decision summary

TradingAgents is the strongest overall pick here because it has a 100/100 readiness score and fits RAG and knowledge.

Strongest overall

TradingAgents

Use this as a leading candidate, then validate the README and install path in your own agent stack.

Fastest prototype

TradingAgents

Best first install candidate based on install readiness and adoption.

Freshest repo

TradingAgents

Most recent maintenance signal among this shortlist.

SignalFinWorld

FinWorld: An All-in-One Open-Source Platform for End-to-End Financial AI Research and Deployment

TradingAgents

TradingAgents: Multi-Agents LLM Financial Trading Framework

Qlib

Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.

Vnpy

基于Python的开源量化交易平台开发框架

Quality
60/100
Promising
100/100
Excellent
100/100
Excellent
100/100
Excellent
Decision verdict
50/100
Needs manual review

Do a manual repository review before adding this to an agent workflow.

100/100
Production-ready

Use this as a leading candidate, then validate the README and install path in your own agent stack.

100/100
Production-ready

Use this as a leading candidate, then validate the README and install path in your own agent stack.

100/100
Production-ready

Use this as a leading candidate, then validate the README and install path in your own agent stack.

Adoption125 stars
0 installs
88K stars
0 installs
44K stars
0 installs
42K stars
0 installs
FreshnessOct 7, 2025Jun 22, 2026Apr 22, 2026May 17, 2026
Use-case fit
Stack fit
Platform hintsJavaScript, Fintech, Claude CodePython, Finance, Claude CodePython, Finance, Claude CodePython, Quant, Claude Code
WarningsNo OpenAgentSkill engagement data yetNo OpenAgentSkill engagement data yetNo major risk signals from current metadataNo OpenAgentSkill engagement data yet
Best forRAG and knowledge workflows · Claude Code teams · builders willing to evaluate younger projectsRAG and knowledge workflows · Claude Code teams · teams that value GitHub adoption signalsFinance and quant workflows · Claude Code teams · teams that value GitHub adoption signalsFinance and quant workflows · Claude Code teams · teams that value GitHub adoption signals
Not ideal forteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security review
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Install
$ npx skills add DVampire/FinWorld
$ npx skills add TauricResearch/TradingAgents
$ npx skills add microsoft/qlib
$ npx skills add vnpy/vnpy