plan-feature
Plan a new feature with analysis, design, and implementation steps. Use when the user asks to plan a feature or run /plan-feature.
What this skill does
# Feature Planning Plan and structure new features with thorough analysis, design considerations, and actionable implementation steps. ## Instructions When this skill is invoked: 1. **Gather Requirements** - Identify the feature name and high-level goal - Ask clarifying questions if requirements are ambiguous - Determine acceptance criteria for the feature 2. **Analyze Existing Codebase** - Search for related existing functionality - Identify patterns and conventions in the codebase - Find integration points where the feature will connect 3. **Design the Solution** - Determine affected modules (lobby, session, api, ui) - Identify required changes per architectural layer - Consider edge cases and error handling - Note any external dependencies or constraints 4. **Create Implementation Plan** - Break down into atomic, testable tasks - Order tasks by dependencies - Write the plan to the todo list using TodoWrite 5. **Save Plan to File** - Create `.claude/plans/` directory if it doesn't exist - Generate a slug from the feature name (e.g., "Custom Voting Decks" → `custom-voting-decks.md`) - Write the plan to `.claude/plans/<feature-slug>.md` using the Output Format below - This creates a persistent record of the plan for reference 6. **Present for Approval** - Summarize the approach - Highlight key design decisions - Present the task breakdown - Reference the saved plan file location - Wait for user approval before implementing ## Task Breakdown Structure ### Backend Tasks (if applicable) ``` [ ] Define API contract (Commands/Events/Queries in api module) [ ] Implement domain logic (aggregates, entities, value objects) [ ] Create command/query handlers [ ] Update read model projections [ ] Add usecase tests for handlers [ ] Add integration tests ``` ### Frontend Tasks (if applicable) ``` [ ] Design component structure [ ] Implement state management (stores/hooks) [ ] Create UI components [ ] Wire up API integration [ ] Add component tests ``` ### Cross-Cutting Tasks ``` [ ] Update shared types/contracts [ ] Add documentation if needed [ ] Verify build passes [ ] Run full test suite ``` ## Analysis Guidelines ### Questions to Answer 1. **What problem does this solve?** - Clear user value 2. **Who is affected?** - Which users/roles 3. **What are the boundaries?** - What's in/out of scope 4. **What could go wrong?** - Failure modes and mitigations 5. **How will we know it works?** - Testability criteria ### Architecture Considerations **Domain Layer**: - New aggregates or entities needed? - Changes to existing aggregate behavior? - New domain events? **Application Layer**: - New commands or queries? - Handler orchestration complexity? - Transaction boundaries? **Adapter Layer**: - API endpoint changes? - Persistence schema updates? - External service integrations? **UI Layer**: - New pages or components? - State management approach? - User interaction flows? ## File Naming Convention Plans are saved to `.claude/plans/<feature-slug>.md` where: - Feature slug is derived from the feature name - Convert to lowercase - Replace spaces and special characters with hyphens - Remove consecutive hyphens Examples: - "Custom Voting Decks" → `custom-voting-decks.md` - "Add User Authentication" → `add-user-authentication.md` - "Fix Timer Bug" → `fix-timer-bug.md` ## Output Format Write the plan to the file using this structure: ```markdown # Feature: [Name] > **Created**: [YYYY-MM-DD] > **Status**: Draft | Approved | In Progress | Completed ## Summary [1-2 sentence description of what this feature does] ## Affected Modules - [ ] api (contracts) - [ ] guessimate-lobby - [ ] guessimate-session - [ ] guessimate-ui ## Key Design Decisions 1. [Decision 1 with rationale] 2. [Decision 2 with rationale] ## Implementation Tasks [Numbered list of specific, actionable tasks] ## Risks & Considerations - [Risk 1] - [Risk 2] ## Open Questions - [Question needing user input] ``` ## Example For a feature request like "Add ability to customize voting deck", the plan would be saved to `.claude/plans/custom-voting-decks.md`: ```markdown # Feature: Custom Voting Decks > **Created**: 2026-01-02 > **Status**: Draft ## Summary Allow lobby owners to create and select custom card decks for estimation sessions instead of using only the default Fibonacci sequence. ## Affected Modules - [x] api (new commands/events for deck management) - [x] guessimate-lobby (deck storage in lobby aggregate) - [ ] guessimate-session (use selected deck) - [x] guessimate-ui (deck configuration UI) ## Key Design Decisions 1. Store custom decks at lobby level (not user level) - simpler model, decks tied to where they're used 2. Provide preset templates (Fibonacci, T-shirt, Powers of 2) - quick setup for common cases 3. Validate deck has 2-15 cards - reasonable constraints ## Implementation Tasks 1. Add Deck value object with validation to api module 2. Add CreateCustomDeckCommand and DeckCreatedEvent to api 3. Implement deck storage in LobbyAggregate 4. Create DeckSelectionComponent in UI 5. Add deck preview functionality 6. Update session creation to use selected deck 7. Add usecase tests for deck commands 8. Add integration test for full flow ## Risks & Considerations - Migration: existing lobbies need default deck assigned - UI complexity: deck editor could become complex ## Open Questions - Should decks be shareable between lobbies? ```
Related in Design
contribute
IncludedLocal-only OSS contribution command center. Auto-refreshes the user's in-flight PR and issue state on invoke so conversations start with full context — no need to brief Claude on what's in flight. Helps the user find issues to contribute to on GitHub, builds per-repo dossiers of what each upstream expects (CLA, DCO, branch convention, AI policy, draft-first, review bots, issue templates), runs deterministic gates before any external action so AI-assisted contributions don't reach maintainers as slop. State is markdown-only: candidate files at ~/.contribute-system/candidates/, repo dossiers at ~/.contribute-system/research/, append-only event log at ~/.contribute-system/log.jsonl. No database, no cloud calls. Use when the user asks about their PRs / issues / contributions, wants to find new work to take on, claim an issue, build/refresh a repo's dossier, or draft a Design Issue or PR. Trigger with "/contribute", "what's my PR status", "find a contribution", "claim issue X", "draft a Design Issue for Y", "refresh dossier for Z".
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IncludedUser-triggered deep architectural analysis of a codebase or scoped subtree across eight modes — information architecture, data flow, integration points, UI surfaces, interaction patterns, data model, control flow, and failure modes. This skill should be used when the user asks to "diagram this codebase," "map the architecture," "show the data flow," "give me an ERD," "trace control flow," "find the integration points," "verify the layout pattern," "audit the UX architecture," or any similar request whose primary deliverable is mermaid diagrams plus cited reports under docs/architecture/. Dispatches haiku/sonnet sub-agents in parallel for per-mode exploration, then verifies every citation mechanically before any node lands in a diagram. Not for one-off prose explanations of code (use code-explanation) or for high-level system design from scratch (use system-design).
mcp
IncludedModel Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
react-native-skia
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plaid
IncludedProduct Led AI Development — guides founders from idea to launched product. Six capabilities: Idea (discover a product idea), Validate (pressure-test the idea against fatal flaws, problem reality, competition, and 2-week MVP feasibility), Plan (vision intake + document generation), Design (translate image references into a design.md spec), Launch (go-to-market strategy), and Build (roadmap execution). Use when someone says "PLAID", "plaid idea", "help me find an idea", "product idea", "idea from my business", "idea from my expertise", "plaid validate", "validate my idea", "pressure-test", "is this idea good", "find fatal flaws", "validate the problem", "plan a product", "define my vision", "generate a PRD", "product strategy", "plaid design", "design from image", "translate image to design", "create design.md", "extract design tokens", "plaid launch", "go-to-market", "launch plan", "GTM strategy", "launch playbook", "plaid build", "build the app", "start building", or "execute the roadmap".
nextjs-framer-motion-animations
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