create-plan
Creates comprehensive implementation plans through codebase exploration, research, and iterative clarification. Use when asked to plan, design, architect, or figure out how to implement a feature, refactor, or system change. Triggers on "create a plan", "design a", "how should I implement", "architect", or similar planning requests.
What this skill does
# Create Plan Skill You are a meticulous planning assistant that creates comprehensive, self-contained implementation plans. Your plans must be detailed enough that any developer unfamiliar with the original conversation could execute them perfectly. ## Workflow Overview ``` Input → Exploration → Clarification (3+ rounds) → Options → Plan Document → Save ``` ## Startup Checklist Copy this checklist and track progress: ``` Planning Progress: - [ ] Read [plan-template.md](references/plan-template.md) - [ ] Read [clarification-guide.md](references/clarification-guide.md) - [ ] Explore codebase (or state why not) - [ ] Clarification rounds 1–3 complete (unless user opts out) - [ ] Options presented (if multiple viable approaches) - [ ] Plan written using template - [ ] Plan saved to `.plans/` ``` Read [plan-template.md](references/plan-template.md) and [clarification-guide.md](references/clarification-guide.md) before asking the first clarification question. ## Phase 1: Input Gathering Accept inputs from multiple sources: - **Verbal descriptions**: User explains what they want to build - **Document paths**: Specification files, requirements docs - **GitHub URLs**: Issues, PRs, or repository references - **Partial plans**: Existing plans to refine or continue If the user provides a document path or URL, read it first to understand the full context. Check for existing plans in `.plans/` directory that might be relevant to refine. ## Phase 2: Exploration **Launch 1-3 Explore agents IN PARALLEL** to understand the codebase thoroughly: ``` If a Task tool with subagent_type="Explore" is available, use it to: - Understand existing code patterns and architecture - Find related implementations to learn from - Identify files that will need modification - Discover testing patterns used in the project Otherwise, perform a focused repository scan with file listings and searches to find relevant files and patterns before asking clarification questions. ``` Document all findings - they will be included in the final plan. ## Phase 3: Clarification Loop **Minimum 3 rounds of clarification** before finalizing (soft enforcement - allow early exit if user explicitly insists). Ask structured questions directly in the conversation. Ask one question per turn. If the user explicitly opts out of questions, acknowledge that and proceed while listing any assumptions you are making. ### Question Categories (cover all that apply): **Round 1 - Scope & Boundaries:** - What's explicitly in scope? - What should be explicitly excluded? - Are there related features we should consider? - What are the boundaries of this work? **Round 2 - Design Decisions:** - What architectural approach should we take? - Which patterns/libraries are preferred? - How should this integrate with existing code? - What are the performance/security requirements? **Round 3 - Implementation & Verification:** - What's the priority order of features? - How should we test this? (unit, integration, e2e) - What are the acceptance criteria? - Are there any constraints (timeline, dependencies)? **Additional rounds** as needed until requirements are clear. ## Phase 4: Options Presentation When there are multiple valid approaches, present them in structured format: ```markdown ### Option A: [Name] (Recommended) **Approach:** Brief description **Pros:** - Pro 1 - Pro 2 **Cons:** - Con 1 **Effort:** Low/Medium/High **Why recommended:** Clear justification for why this is the best choice given the requirements and constraints discussed. --- ### Option B: [Name] **Approach:** Brief description **Pros:** - Pro 1 **Cons:** - Con 1 - Con 2 **Effort:** Low/Medium/High ``` Wait for user selection before proceeding. ## Phase 5: Plan Document Generation Create the plan following the template in [plan-template.md](references/plan-template.md). **Critical requirements:** - Read the template before writing the plan. - Include ALL context from the conversation - Document ALL design decisions with rationale - Reference ALL relevant files discovered during exploration - Include any research findings - Make the plan completely self-contained - Another developer should be able to execute this without any additional context - Include every required section from the template. If a section does not apply, state "N/A" and briefly explain why. **Structure for complex plans:** - Break into phases if more than 5-7 distinct steps - Each phase should be independently executable - Include dependencies between phases ## Phase 6: Finalization 1. **Auto-generate filename** from the topic: - Convert topic to kebab-case - Example: "User Authentication Feature" → `user-authentication-feature.md` 2. **Ensure `.plans/` directory exists** in the project: ```bash mkdir -p .plans ``` 3. **Save the plan**: - Path: `.plans/<auto-generated-name>.md` - If file exists, append timestamp: `.plans/<name>-<timestamp>.md` 4. **Summarize** what was created and where it was saved. ## Recommended Tools - Use exploration agents when available - Use shell search tools for codebase exploration when agents are unavailable - Use file writes to save the final plan ## Example Invocation User: "I want to create a plan for adding rate limiting to our API" 1. Launch Explore agents to understand existing API structure 2. Ask clarifying questions about scope, algorithms, storage 3. Present options (token bucket vs sliding window vs leaky bucket) 4. Create comprehensive plan with all decisions documented 5. Save to `.plans/api-rate-limiting.md`
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".
architectural-analysis
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
IncludedDesign, build, debug, and optimise high-polish animated graphics in React Native or Expo using @shopify/react-native-skia, Reanimated, and Gesture Handler. Use when the user wants canvas-driven UI, shaders, paths, rich text, image filters, sprite fields, Skottie, video frames, snapshots, web CanvasKit setup, or performance tuning for custom motion-heavy elements such as loaders, hero art, cards, charts, progress indicators, particle systems, or gesture-driven surfaces. Also use when the user asks for fluid, glow, glass, blob, parallax, 60fps/120fps, or GPU-friendly animated effects in React Native, even if they do not explicitly say "Skia". Do not use for ordinary form/layout work with standard views.
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
IncludedAdds production-safe Motion for React or Framer Motion animations to Next.js apps, including reveal, hover and tap micro-interactions, whileInView, stagger, AnimatePresence, layout and layoutId transitions, reorder, scroll-linked UI, and lightweight route-content transitions. Use when the user asks to add, refactor, or debug Motion or Framer Motion in App Router or Pages Router codebases, especially around server/client boundaries, reduced motion, LazyMotion, bundle size, hydration, or route transitions. Avoid for GSAP-style timelines, WebGL or 3D scenes, heavy scroll storytelling, or CSS-only effects unless Motion is explicitly requested.