spec-kitty-plan

name	spec-kitty-plan
description	Execute the implementation planning workflow using the plan template to generate design artifacts.

/spec-kitty.plan - Create Implementation Plan

Version: 0.11.0+

📍 WORKING DIRECTORY: Stay in planning repository

IMPORTANT: Plan works in the planning repository. NO worktrees created.

# Run from project root (same directory as /spec-kitty.specify):
# You should already be here if you just ran /spec-kitty.specify

# Creates:
# - kitty-specs/###-feature/plan.md → In planning repository
# - Commits to target branch
# - NO worktrees created

Do NOT cd anywhere. Stay in the planning repository root.

User Input

$ARGUMENTS

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

Location Check (0.11.0+)

This command runs in the planning repository, not in a worktree.

• Verify you're on the target branch (meta.json → target_branch) before scaffolding plan.md
• Planning artifacts live in kitty-specs/###-feature/
• The plan template is committed to the target branch after generation

Path reference rule: When you mention directories or files, provide either the absolute path or a path relative to the project root (for example, kitty-specs/<feature>/tasks/). Never refer to a folder by name alone.

Planning Interrogation (mandatory)

Before executing any scripts or generating artifacts you must interrogate the specification and stakeholders.

• Scope proportionality (CRITICAL): FIRST, assess the feature's complexity from the spec:

  • Trivial/Test Features (hello world, simple static pages, basic demos): Ask 1-2 questions maximum about tech stack preference, then proceed with sensible defaults
  • Simple Features (small components, minor API additions): Ask 2-3 questions about tech choices and constraints
  • Complex Features (new subsystems, multi-component features): Ask 3-5 questions covering architecture, NFRs, integrations
  • Platform/Critical Features (core infrastructure, security, payments): Full interrogation with 5+ questions

• User signals to reduce questioning: If the user says "use defaults", "just make it simple", "skip to implementation", "vanilla HTML/CSS/JS" - recognize these as signals to minimize planning questions and use standard approaches.

• First response rule:

  • For TRIVIAL features: Ask ONE tech stack question, then if answer is simple (e.g., "vanilla HTML"), proceed directly to plan generation
  • For other features: Ask a single architecture question and end with WAITING_FOR_PLANNING_INPUT

• If the user has not provided plan context, keep interrogating with one question at a time.

• Conversational cadence: After each reply, assess if you have SUFFICIENT context for this feature's scope. For trivial features, knowing the basic stack is enough. Only continue if critical unknowns remain.

Planning requirements (scale to complexity):

1. Maintain a Planning Questions table internally covering questions appropriate to the feature's complexity (1-2 for trivial, up to 5+ for platform-level). Track columns #, Question, Why it matters, and Current insight. Do not render this table to the user.
2. For trivial features, standard practices are acceptable (vanilla HTML, simple file structure, no build tools). Only probe if the user's request suggests otherwise.
3. When you have sufficient context for the scope, summarize into an Engineering Alignment note and confirm.
4. If user explicitly asks to skip questions or use defaults, acknowledge and proceed with best practices for that feature type.

Outline

1. Check planning discovery status:

   • If any planning questions remain unanswered or the user has not confirmed the Engineering Alignment summary, stay in the one-question cadence, capture the user's response, update your internal table, and end with WAITING_FOR_PLANNING_INPUT. Do not surface the table. Do not run the setup command yet.
   • Once every planning question has a concrete answer and the alignment summary is confirmed by the user, continue.

2. Detect feature context (CRITICAL - prevents wrong feature selection):

   Before running any commands, detect which feature you're working on:

   a. Check git branch name:

   • Run: git rev-parse --abbrev-ref HEAD
   • If branch matches pattern ###-feature-name or ###-feature-name-WP##, extract the feature slug (strip -WP## suffix if present)
   • Example: Branch 020-my-feature or 020-my-feature-WP01 → Feature 020-my-feature

   b. Check current directory:

   • Look for ###-feature-name pattern in the current path
   • Examples:
     • Inside kitty-specs/020-my-feature/ → Feature 020-my-feature
     • Not in a worktree during planning (worktrees only used during implement): If detection runs from .worktrees/020-my-feature-WP01/ → Feature 020-my-feature

   c. Prioritize features without plan.md (if multiple exist):

   • If multiple features exist and none detected from branch/path, list all features in kitty-specs/
   • Prefer features that don't have plan.md yet (unplanned features)
   • If ambiguous, ask the user which feature to plan

   d. Extract feature slug:

   • Feature slug format: ###-feature-name (e.g., 020-my-feature)
   • You MUST pass this explicitly to the setup-plan command using --feature flag
   • DO NOT rely on auto-detection by the CLI (prevents wrong feature selection)

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 ``
   • 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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⛔ MANDATORY STOP POINT

This command is COMPLETE after generating planning artifacts.

After reporting:

• plan.md path
• research.md path (if generated)
• data-model.md path (if generated)
• contracts/ contents (if generated)
• Agent context file updated

YOU MUST STOP HERE.

Do NOT:

• ❌ Generate tasks.md
• ❌ Create work package (WP) files
• ❌ Create tasks/ subdirectories
• ❌ Proceed to implementation

The user will run /spec-kitty.tasks when they are ready to generate work packages.

Next suggested command: /spec-kitty.tasks (user must invoke this explicitly)