AWorld

Why we included this project

AWorld's pitch is that the model is only part of the agent: the harness that wires up tools, memory, and context is what lets you package your own domain knowledge into reusable, autonomous agents. You drive it through the aworld-cli, where an orchestrator plans a task and delegates pieces to specialized sub-agents (a developer, an evaluator, and video, audio, and image generators) that build, score, and refine their own output in a build-evaluate-evolve loop. The evaluation step is the practical part worth noticing: instead of hoping the model gets it right, you set a quality bar and the system keeps iterating until it clears it. If you want to encode your expertise as Skills, or just see how far an agent can take a single prompt into a working app or video, the repo ships ready-made Skills for app evaluation and deep-search workflows, so you are not starting from an empty framework.