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

Cua is the strongest overall pick here because it has a 100/100 readiness score and fits Local desktop.

Strongest overall

Cua

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

Fastest prototype

Cua

Best first install candidate based on install readiness and adoption.

Freshest repo

Cua

Most recent maintenance signal among this shortlist.

Signal	Photo Agents Autonomous self-evolving agents. Vision-grounded layered memory and self-written skills for LLM agents that operate your computer.	Edict 🏛️ 三省六部制 · OpenClaw Multi-Agent Orchestration System — 9 specialized AI agents with real-time dashboard, model config, and full audit trails	Cua Open-source infrastructure for Computer-Use Agents. Sandboxes, SDKs, and benchmarks to train and evaluate AI agents that can control full desktops (macOS, Linux, Windows).	RD Agent Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI. 🔗https://aka.ms/RD-Agent-Tech-Report
Quality	77/100 Strong	100/100 Excellent	100/100 Excellent	100/100 Excellent
Decision verdict	88/100 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.	100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack.
Adoption	861 stars Verified outcomes are shown on each skill page	16K stars Verified outcomes are shown on each skill page	21K stars Verified outcomes are shown on each skill page