ad-tdd

ad-tdd is a Test-driven development skill for AI agents, published by alexandremendoncaalvaro in the CorridorKey-Runtime repository on GitHub. Skillspace rates ad-tdd D (66/100) and it passed the safety scan; the rating is based on static analysis only.

Test-Driven Development per WORKFLOW.md §16 — red-green-refactor as deterministic LLM guardrail. Five phases — confirm regime, plan vertically, tracer bullet (one test → red → minimum code → green), incremental loop, refactor while green. Tests verify behavior through public interfaces; horizontal slicing (bulk-write tests then bulk-write code) is rejected as the named anti-pattern. Triggers on "TDD", "test-driven", "red-green-refactor", "test first", "write a failing test", "tracer bullet", "behavior not implementation", "vertical slice tests", "/ad-tdd". Distinct from `ad-tdg` (outcome-based prompting — pick implementation strategy when technique is known); routes to `ad-tdg` for strategy selection inside the GREEN phase, `ad-spike` for technique uncertainty, `ad-diagnose` for debugging. No file written; output is the verified implementation that lands through normal commits.

Grade

D

Quality

66 / 100

Safety

Passed

GitHub stars

749

Unproven: rated by static analysis only, not yet compared head-to-head.

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