Full-stack-skills speckit-plan
Generate a technical implementation plan from a feature spec by filling the plan template, resolving unknowns via research, producing data-model.md, API contracts, and quickstart.md artifacts. Use when the feature spec is ready and the user needs architecture decisions, data models, API schemas, or a structured plan before task generation.
git clone https://github.com/partme-ai/full-stack-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/partme-ai/full-stack-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/speckit-skills/speckit-plan" ~/.claude/skills/partme-ai-full-stack-skills-speckit-plan && rm -rf "$T"
skills/speckit-skills/speckit-plan/SKILL.mdSpec Kit Plan Skill
When to Use
- The feature spec is ready and you need a technical implementation plan.
Inputs
specs/<feature>/spec.md- Repo context and
templates.specify/ - User-provided constraints or tech preferences (if any)
If the spec is missing, ask the user to run speckit-specify first.
Workflow
-
Setup: Run
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")..specify/scripts/bash/setup-plan.sh --json -
Load context: Read FEATURE_SPEC and
. Load IMPL_PLAN template (already copied)..specify/memory/constitution.md -
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
-
Stop and report: Command ends after Phase 2 planning. Report branch, IMPL_PLAN path, and generated artifacts.
Phases
Phase 0: Outline & Research
-
Extract unknowns from Technical Context above:
- For each NEEDS CLARIFICATION → research task
- For each dependency → best practices task
- For each integration → patterns task
-
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}" -
Consolidate findings in
using format:research.md- 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
-
Extract entities from feature spec →
:data-model.md- Entity name, fields, relationships
- Validation rules from requirements
- State transitions if applicable
-
Generate API contracts from functional requirements:
- For each user action → endpoint
- Use standard REST/GraphQL patterns
- Output OpenAPI/GraphQL schema to
/contracts/
-
Agent context update:
- Run
.specify/scripts/bash/update-agent-context.sh <agent_type> - Use the current runtime agent type (e.g., claude, codex, copilot, gemini). Leave empty to update all existing agent files.
- Update the appropriate agent-specific context file
- Add only new technology from current plan
- Preserve manual additions between markers
- Run
Output: data-model.md, /contracts/*, quickstart.md, agent-specific file
Key rules
- Use absolute paths
- ERROR on gate failures or unresolved clarifications
Outputs
(filled implementation plan)specs/<feature>/plan.mdspecs/<feature>/research.mdspecs/<feature>/data-model.md
(API schemas)specs/<feature>/contracts/specs/<feature>/quickstart.md- Updated agent context file (runtime-specific)
Next Steps
After planning:
- Generate tasks with speckit-tasks.
- Create a checklist with speckit-checklist when a quality gate is needed.