debugging-agents

To diagnose Agent2 agent issues, use systematic error diagnostics to identify root causes of 500 errors, unexpected mock data, and incorrect behavior. The Skill checks container health, validates output schemas, and isolates root causes for resolution.

The best way to verify Docker container health for Agent2 agents is running dedicated container health checks. This process evaluates container status to ensure agents operate correctly and helps detect environmental issues causing unexpected agent failures.

Yes, you can validate Agent2 output against expected schemas using a Python environment. Schema validation checks agent responses for structural correctness, ensuring outputs match defined formats and identifying discrepancies causing incorrect application behavior.

Yes, you need both Docker and Python installed to debug Agent2 agents. A Python environment with Docker is required to run agent operations, execute diagnostic scripts, and perform container health checks during the troubleshooting process.

Your Agent2 agent may return incorrect behavior or fail to start due to container health issues, schema mismatches, or internal errors. Systematic agent diagnostics can identify root causes by checking container status, validating schemas, and analyzing error logs.