marsai:testing-skills-with-subagents

Testing AI agent skills with subagents involves running a RED-GREEN-REFACTOR cycle. You first capture baseline failures without the skill, implement it to address those failures, and then re-test under pressure to ensure compliant behavior.

The RED-GREEN-REFACTOR cycle is a validation process for agent skills. RED documents baseline failures, GREEN implements the skill to fix them, and REFACTOR closes loopholes by re-testing scenarios under multi-pressure conditions to confirm bulletproof behavior.

To close loopholes when an agent bypasses skill rules, execute a REFACTOR cycle. Capture new rationalizations, update negations and rules, and repeatedly re-test the agent under multi-pressure scenarios until it remains fully compliant.

Yes, you can verify a skill stays bulletproof through meta-testing guidance. Challenge the implemented skill with new rationalizations and repeated testing scenarios to confirm the agent maintains compliant behavior under evolving multi-pressure conditions.

A baseline test is needed to capture exact failures and verbatim rationalizations when the skill is absent. This RED phase reveals how agents bypass behavior naturally, providing the necessary documentation to implement targeted GREEN fixes.

TDD validation works for ensuring agent compliance by applying RED-GREEN-REFACTOR methodology. It documents initial failures, implements the skill, and re-tests under multi-pressure scenarios to close loopholes and confirm resilient behavior.