protocol-authoring

You can document AI agent behavior using a test-driven development methodology to create protocols. This approach applies a RED-GREEN-REFACTOR cycle to documentation, explicitly sealing loopholes to prevent agent rationalization under pressure.

Test-driven protocol creation applies the RED-GREEN-REFACTOR cycle to documentation, ensuring protocols address real agent failures. It requires strict formatting, testing, and refactoring cycles to guarantee protocol quality, utility, and discoverability by AI agents.

To create a protocol for failing AI agents, you author documentation that explicitly forbids the observed failure mode and test its effectiveness. This structured approach ensures protocols are clear, effective, and robust against agent failures.

You optimize protocol discoverability by using precise descriptions and targeted keywords within the documentation. This test-driven authoring approach ensures protocols are easily found and understood by AI agents during execution.

Yes, you can use the test-driven development cycle to refactor existing AI documentation. The refactoring phase allows you to seal loopholes and refine protocol quality while ensuring the documentation remains effective against agent failures.

You need to harden protocols when an AI agent consistently fails to follow specific standards under time pressure. Protocol hardening seals loopholes and prevents rationalization, ensuring documentation remains robust during execution.