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speckit-plan

Generate technical implementation plans from feature specifications.

Install

mkdir -p .claude/skills/speckit-plan-kenhia && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/15089" && unzip -o skill.zip -d .claude/skills/speckit-plan-kenhia && rm skill.zip

Installs to .claude/skills/speckit-plan-kenhia

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Generate technical implementation plans from feature specifications.
68 charsno explicit “when” trigger

About this skill

Speckit Plan Skill

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 specdata-model.md:

    • Entity name, fields, relationships
    • Validation rules from requirements
    • State transitions if applicable
  2. Define interface contracts (if project has external interfaces) → /contracts/:

    • Identify what interfaces the project exposes to users or other systems
    • Document the contract format appropriate for the project type
    • Examples: public APIs for libraries, command schemas for CLI tools, endpoints for web services, grammars for parsers, UI contracts for applications
    • Skip if project is purely internal (build scripts, one-off tools, etc.)
  3. Agent context update:

    • Run .specify/scripts/bash/update-agent-context.sh copilot
    • 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

Key rules

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

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