What problem does it solve? It turns vague feature requests, behavior changes, and bug fixes into concrete, ordered test case plans following Kent Beck's Canon TDD, so implementation can proceed without ambiguity or missed edge cases. ## Core Features & Use Cases - Requirement Clarification: Applies an ambiguity threshold grounded in codebase conventions, asking targeted questions only when observable behavior decisions remain unsettled. - Test Case Design: Decomposes features into smallest testable increments ordered simple-to-complex, separating behavioral tests from structural Refactor items and marking integration tests. - Portable Plan Files: Writes self-contained Markdown plans to .plans/ with Goal, Context, and checkbox Test Cases that a fresh implementer or the implement skill can execute with zero session context. - Use Case: When asked to add a sequence diagram parser, the skill analyzes the codebase, clarifies API decisions, and produces .plans/sequence-parser.md with ordered test cases ready for execution via the implement skill or /tdd. ## Quick Start Ask the AI to create a TDD plan for the feature or bug fix you want, describing the desired behavior and letting it analyze the codebase first.