What problem does it solve?
It solves the problem of turning an implementation plan into correct, maintainable code without relying on a single long-running agent session that can drift or accumulate errors.
Core Features & Use Cases
- Two-stage review per task: runs a spec compliance check first, then a code quality review second to prevent scope creep and catch defects early.
- Fresh implementer per task: dispatches a clean subagent for each task so context pollution is minimized and each change is tightly scoped.
- Task-level verification and commit discipline: encourages failing-test-first (TDD), running tests, and committing at task completion boundaries.
Use case example: You have an implementation plan for a small auth feature (e.g., user model, password hashing, login endpoint). Use this skill to execute each task with an implementer subagent, then ensure the output matches the plan spec and passes quality checks before moving on.
Quick Start
Ask the AI to run subagent-driven-development on your feature implementation plan and implement each task with TDD plus spec compliance and code quality review gates.