/speckit-plan

description: Execute implementation planning from spec to generate design artifacts.
argument-hint: "Path to spec.md or feature name"

Before proceeding, load the `speckit-orchestrator` skill for workflow coordination. Consider loading complementary skills like `superpowers:writing-plans` for enhanced planning capabilities.

User Input

$ARGUMENTS

You **MUST** consider the user input before proceeding (if not empty).

Outline

1. **Setup**: Run `.specify/scripts/bash/setup-plan.sh --json` from repo root and parse JSON for FEATURE_SPEC, IMPL_PLAN, SPECS_DIR, BRANCH. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").

2. **Load context**: Read FEATURE_SPEC and `.specify/memory/constitution.md`. Load IMPL_PLAN template (already copied).

3. **Execute plan workflow**: Follow the structure in IMPL_PLAN template to:

• Fill Technical Context (mark unknowns as "NEEDS CLARIFICATION")
• Fill Constitution Check section from constitution
• Evaluate gates (ERROR if violations unjustified)
• Phase 0: Generate research.md (resolve all NEEDS CLARIFICATION)
• Phase 1: Generate data-model.md, contracts/, quickstart.md
• Phase 1: Update agent context by running the agent script
• Re-evaluate Constitution Check post-design

4. **Stop and report**: Command ends after Phase 2 planning. Report branch, IMPL_PLAN path, and generated artifacts.

Phases

Phase 0: Outline & Research

1. **Extract unknowns from Technical Context** above:

• For each NEEDS CLARIFICATION → research task
• For each dependency → best practices task
• For each integration → patterns task

2. **Generate and dispatch research agents**:

   For each unknown in Technical Context:
     Task: "Research {unknown} for {feature context}"
   For each technology choice:
     Task: "Find best practices for {tech} in {domain}"

3. **Consolidate findings** in `research.md` using format:

• Decision: [what was chosen]
• Rationale: [why chosen]
• Alternatives considered: [what else evaluated]

**Output**: research.md with all NEEDS CLARIFICATION resolved

Phase 1: Design & Contracts

**Prerequisites:** `research.md` complete

1. **Extract entities from feature spec** → `data-model.md`:

• Entity name, fields, relationships
• Validation rules from requirements
• State transitions if applicable

2. **Generate API contracts** from functional requirements:

• For each user action → endpoint
• Use standard REST/GraphQL patterns
• Output OpenAPI/GraphQL schema to `/contracts/`

3. **Agent context update**:

• Run `.specify/scripts/bash/update-agent-context.sh claude`
• These scripts detect which AI agent is in use
• Update the appropriate agent-specific context file
• Add only new technology from current plan
• Preserve manual additions between markers

**Output**: data-model.md, /contracts/*, quickstart.md, agent-specific file

Record the Tradeoff (decision journal)

When this step settles a decision with real alternatives, record it to `docs/tradeoffs.md` while the reasoning is live (draft and confirm):

• If leyline is installed, invoke `Skill(leyline:decision-journal)` and append

a tradeoff entry (the decision, the options weighed, and what was sacrificed; set `phase` to `plan`). Show the draft; append on confirmation.

• Fallback (leyline absent): append to `docs/tradeoffs.md` using the in-file

ENTRY TEMPLATE; assign the next `TR-NNN` id.

Key rules

• Use absolute paths
• ERROR on gate failures or unresolved clarifications