bee:testing-agents-with-subagents

AI agent TDD validation uses a Red-Green-Refactor cycle to test baseline inputs, verify outputs against accuracy metrics, and ensure robustness before deployment to prevent production failures.

The Red-Green-Refactor cycle for LLM agents defines test cases with known inputs, validates outputs against accuracy metrics, and refines agent logic to guarantee consistent, well-structured responses.

Edge case testing for AI agents involves running the agent against unusual or boundary inputs to verify robustness, validate output formatting, and confirm accuracy metrics before production release.

TDD verifies code review agents by running them against known vulnerabilities and clean code files to validate findings, check output formats, and ensure accurate edge-case handling before deployment.

Establishing accuracy metrics for LLM agent testing requires defining expected output formats and validation thresholds, then running baseline tests with known inputs to measure consistency and prevent failures.