Computer Use Agent

Planner execute verify agent Planner model create a list of intermediate goals, then ReAct agent execute actions to achieve this goal, when finish - the planner verify actions with summarized trajectory, after that

Single-pass A2A agent for the CAR-bench track. Uses a reasoning-capable LLM (default: openai/gpt-5-mini with reasoning_effort=medium) plus a compact, domain-agnostic prompt consisting of six general agent rules. No hardcoded policy content, tool names, or task-specific lookup tables — all instructions come from the green agent at runtime.

Test dummy agent pushing

A2A-compatible purple agent for the Computer Use & Web Agent track, designed for CAR-bench style web and computer-use tasks with reproducible containerized deployment.

A2A-compatible purple agent for the Computer Use & Web Agent track, designed for CAR-bench style web and computer-use tasks with reproducible containerized deployment.