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.
Decision summary
Camel is the strongest overall pick here because it has a 100/100 readiness score and fits GitHub automation.
Strongest overall
Camel
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
SuperAGI
Best first install candidate based on install readiness and adoption.
Freshest repo
Camel
Most recent maintenance signal among this shortlist.
| Signal | Pywinassistant The first open-source Artificial Narrow Intelligence generalist agentic framework Computer-Using-Agent that fully operates graphical-user-interfaces (GUIs) by using only natural language. Uses Visualization-of-Thought and Chain-of-Thought reasoning to elicit spatial reasoning and perception, emulates, plans and simulates synthetic HID interactions. | SuperAGI <⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably. | Camel 🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org | PentestGPT Automated Penetration Testing Agentic Framework Powered by Large Language Models |
|---|---|---|---|---|
| Quality | 72/100 Strong | 84/100 Strong | 100/100 Excellent | 100/100 Excellent |
| Decision verdict | 74/100 Strong shortlist Shortlist this skill and compare it with close alternatives before production adoption. | 87/100 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 | 1.3K stars 0 installs | 18K stars 0 installs | 17K stars 0 installs | 14K stars 0 installs |
| Freshness | Feb 13, 2025 | Jan 22, 2025 | Jun 14, 2026 | Jun 7, 2026 |
| Use-case fit | ||||
| Stack fit | ||||
| Platform hints | Python, LLM, Claude Code | Python, LLM, Claude Code, OpenAI Agents | Python, LLM, Claude Code | Python, LLM, Claude Code |
| Warnings | Repository looks stale · No OpenAgentSkill engagement data yet | Repository looks stale | No major risk signals from current metadata | No OpenAgentSkill engagement data yet |
| Best for | GitHub automation workflows · Claude Code teams · teams that value GitHub adoption signals | Browser automation workflows · Claude Code teams · teams that value GitHub adoption signals | GitHub automation workflows · Claude Code teams · teams that value GitHub adoption signals | Coding agents 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 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 |
| OpenAgentSkill engagement | 0 views 0 install copies | 1 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies |
| Install | $ npx skills add a-real-ai/pywinassistant | $ npx skills add TransformerOptimus/SuperAGI | $ npx skills add camel-ai/camel | $ npx skills add GreyDGL/PentestGPT |