cua is an agent orchestration repository at trycua/cua; the stored repo summary is: 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). Its recorded primary language is HTML. License metadata lists MIT. GitHub metadata shows about 17,320 stars. The project homepage is https://cua.ai.
License
MIT
Stars
19,343
Homepage
https://cua.ai/Features
- Source description for 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).
- cua uses HTML as its recorded primary language, which helps with stack-fit review.
- cua helps evaluate coordination, planning, or task-decomposition patterns in agent systems.
- cua acts as a reference point for measuring, tracing, benchmarking, or monitoring behavior.
- cua can inform repeatable automation, scheduled execution, or operations workflow design.
- cua lists MIT license metadata; review obligations before redistribution or hosted use.
Use Cases
- Used for AI quality monitoring and regression evaluation
- Supports AI engineering build-and-iterate workflows for dev teams
- Used for cross-system process automation and operations efficiency
- Build internal AI workflow prototypes with cua
- Validate cua in production-like engineering scenarios
- Building AI development workflows
FAQ
Start from the repository summary (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).), then verify maintenance status, integration boundaries, and whether its agent orchestration, evaluation and observability, workflow automation focus matches the intended workflow. Repository: https://github.com/trycua/cua. Stars: about 17,320. License: MIT. Language: HTML.
cua is best treated as a repository-level component or reference implementation for agent orchestration, evaluation and observability, workflow automation. Good evaluation scenarios include: Compare cua when the need is agent orchestration and the repo summary matches: Open-source infrastructure for Computer-Use Agents. Sandboxes, SDKs, and benchmarks to... Compare the HTML implementation in cua before choosing a similar internal architecture. Use cua to test agent coordination patterns with a concrete open-source codebase.
