Spec Driven Development (SDD)

Concept of the skill

Use when starting a non-trivial feature, refactor, or agent implementation that needs a written spec, plan, task breakdown, and verification path before code changes.

Coverage

• When to require SDD: non-trivial work, core-module refactors, ambiguous agent loops, cross-boundary changes, or any task where hidden requirements could be expensive after code exists.
• Artifact chain: spec.md for what and why, plan.md for how, tasks.md for ordered work, implementation commits for execution, and a final verification report for spec compliance.
• Phase discipline: specification before plan, plan before tasks, tasks before implementation, and verification before completion.
• Traceability: each task and verification check maps back to a requirement, constraint, or success criterion.
• Review gates: human approval when available, or an explicit documented rationale when autonomous work must proceed.
• Scope control: if implementation discovers the spec or plan is wrong, update the upstream artifact before continuing.
• Post-implementation learning: measure whether the change solved the problem when the task has a product, operational, or user-facing success metric.

Philosophy of the skill

AI agents default to implementation-first thinking: receive a prompt, start coding. That produces features that compile, pass narrow tests, and still miss the actual requirement. SDD makes the specification the source of truth and turns the plan, task list, implementation, and verification report into derived artifacts.