speckit-plan

To turn a spec into an actionable implementation plan, you generate a plan.md and workflow-state.json file that maps required artifacts, validation evidence, and the next stage. This preserves upstream design artifacts while moving from intent to execution.

Creating stage-aware plans for bugs and blocked investigations requires bounded investigation and precise context loading to select the right gate packs. The process produces artifact mapping and rollout decisions that track risks and the next required workflow state.

Evidence-driven validation in implementation planning is the process of selecting required context and gate packs based on concrete evidence rather than vague assumptions. It ensures feature rollout decisions track workflow state, risks, and required artifacts.

You need to generate workflow-state.json for a spec-kit project when a feature is blocked, a bug needs bounded investigation, or a spec requires a slice-by-slice implementation map. It tracks the next required stage and coordinates research, data model, and contract artifacts.

Yes, you can coordinate research and data model artifacts during plan generation. The process decides when to create or update research, data model, contracts, quickstart, and review artifacts to ensure stage continuity and evidence-driven validation.