ralph-validate-prd

PRD validation checks feature completeness, test coverage, feature sizing, dependency ordering, and acceptance criteria quality against predefined criteria. It acts as a pre-flight checklist to catch critical issues before complex feature development begins.

RLM optimization structures a Product Requirements Document for efficient AI processing by verifying clear headings, single requirements per line, and consistent section structure. This ensures the document is parsed efficiently by AI agents during initialization.

Checking acceptance criteria quality involves validating the prd.md file against predefined criteria for completeness and test coverage. This ensures each requirement has actionable, testable acceptance criteria before coding starts.

AI feature development fails with incomplete requirements due to unclear headings, multiple requirements per line, or missing dependency ordering. Validating the PRD beforehand prevents suboptimal output by ensuring consistent section structure and feature completeness.

Yes, a PRD quality checklist verifies feature sizing alongside test coverage and dependency ordering. Checking feature sizing ensures requirements are appropriately scoped for the AI initializer to process without hitting structural pitfalls.