Skill comparison
Compare agent skills before installing.
Comparing 4 skills
Use this as a shortlist, then open the skill detail page before adopting.
Decision summary
Qlib is the strongest overall pick here because it has a 100/100 readiness score and fits Finance and quant.
Strongest overall
Qlib
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
Qlib
Best first install candidate based on install readiness and adoption.
Freshest repo
Machine Learning For Trading
Most recent maintenance signal among this shortlist.
| Signal | Pandapy PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x faster (by @firmai) | Vectorbt The backtesting engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one. | Machine Learning For Trading Code for Machine Learning for Algorithmic Trading, 2nd edition. | 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. |
|---|---|---|---|---|
| Quality | 49/100 Needs review | 99/100 Excellent | 100/100 Excellent | 100/100 Excellent |
| Decision verdict | 51/100 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. |
| Adoption | 547 stars Verified outcomes are shown on each skill page | 7.9K stars Verified outcomes are shown on each skill page | 19K stars Verified outcomes are shown on each skill page | 44K stars Verified outcomes are shown on each skill page |
| Freshness | Oct 20, 2021 | Jun 10, 2026 | Jun 23, 2026 | Apr 22, 2026 |
| Use-case fit | ||||
| Workflow fit | ||||
| Platform hints | Python, Finance, Claude Code | Python, Finance, Claude Code | Jupyter Notebook, Finance, Claude Code | Python, Finance, Claude Code |
| Warnings | Repository looks stale · No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet |
| Best for | GitHub automation workflows · Claude Code teams · teams that value GitHub adoption signals | Finance and quant workflows · Claude Code teams · teams that value GitHub adoption signals | Coding agents workflows · Claude Code teams · teams that value GitHub adoption signals | Finance and quant workflows · Claude Code teams · teams that value GitHub adoption signals |
| Not ideal for | teams that require actively maintained dependencies · production agents without a repository review | teams that need a vendor-supported SLA · high-compliance environments without internal security review | teams that need a vendor-supported SLA · high-compliance environments without internal security review | teams that need a vendor-supported SLA · high-compliance environments without internal security review |
| OpenAgentSkill engagement | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies |
| Install | $ npx skills add firmai/pandapy | $ npx skills add polakowo/vectorbt | $ npx skills add stefan-jansen/machine-learning-for-trading | $ npx skills add microsoft/qlib |