writing-plans
Use when design is complete and you need detailed implementation tasks - creates comprehensive implementation plans with exact file paths, complete code examples, and verification steps assuming minimal codebase familiarity
What this skill does
# Writing Plans
## Overview
Write comprehensive implementation plans assuming limited codebase context. Document everything needed: which files to touch for each task, code examples, testing approach, verification steps. Break work into bite-sized tasks following DRY, YAGNI, and TDD principles with frequent commits.
Assume the implementer is skilled but unfamiliar with the specific codebase and tooling.
## When to Use
- Design is complete and ready for implementation
- Need to break down work into concrete tasks
- Preparing work for delegation or future execution
- Want clear verification steps for each task
## Plan Location
Save plans to: `docs/plans/YYYY-MM-DD-<feature-name>.md`
## Bite-Sized Task Granularity
**Each step is one action (2-5 minutes):**
- "Write the failing test" - step
- "Run it to make sure it fails" - step
- "Implement the minimal code to make the test pass" - step
- "Run the tests and make sure they pass" - step
- "Commit" - step
Break larger tasks into these atomic steps. Each step should be independently verifiable.
## Plan Document Header
**Every plan MUST start with this header:**
```markdown
# [Feature Name] Implementation Plan
**Goal:** [One sentence describing what this builds]
**Architecture:** [2-3 sentences about approach]
**Tech Stack:** [Key technologies/libraries]
---
```
## Task Structure
```markdown
### Task N: [Component Name]
**Files:**
- Create: `exact/path/to/file.py`
- Modify: `exact/path/to/existing.py:123-145`
- Test: `tests/exact/path/to/test.py`
**Step 1: Write the failing test**
```python
def test_specific_behavior():
result = function(input)
assert result == expected
```
**Step 2: Run test to verify it fails**
Run: `pytest tests/path/test.py::test_name -v`
Expected: FAIL with "function not defined"
**Step 3: Write minimal implementation**
```python
def function(input):
return expected
```
**Step 4: Run test to verify it passes**
Run: `pytest tests/path/test.py::test_name -v`
Expected: PASS
**Step 5: Commit**
```bash
git add tests/path/test.py src/path/file.py
git commit -m "feat: add specific feature"
```
## Essential Elements
### Exact File Paths
Always specify complete paths:
- **Good**: `src/auth/validators.py`
- **Bad**: "the validators file"
For modifications, include line ranges if known: `config.json:45-52`
### Complete Code Examples
Include full, working code in the plan:
- **Good**: Show the complete function/test
- **Bad**: "Add validation for email field"
The implementer should be able to copy-paste code from the plan.
### Exact Commands
Specify complete commands with expected output:
```bash
# Run specific test
pytest tests/auth/test_login.py::test_invalid_email -v
# Expected output
FAIL: AssertionError: Expected validation error
```
### Verification Steps
Each task should explain how to verify it worked:
- What command to run
- What output to expect
- What to check manually if needed
## Commit Guidelines
Encourage frequent, atomic commits:
- One logical change per commit
- Meaningful commit messages
- Follow conventional commits format:
- `feat:` for new features
- `fix:` for bug fixes
- `refactor:` for code changes without behavior change
- `test:` for test-only changes
- `docs:` for documentation
## Example Task
```markdown
### Task 1: Email Validation
**Files:**
- Create: `src/validators/email.py`
- Test: `tests/validators/test_email.py`
**Step 1: Write the failing test**
```python
# tests/validators/test_email.py
from src.validators.email import validate_email
def test_rejects_invalid_email():
result = validate_email("notanemail")
assert result == {"valid": False, "error": "Invalid format"}
def test_accepts_valid_email():
result = validate_email("[email protected]")
assert result == {"valid": True}
```
**Step 2: Run test to verify it fails**
Run: `pytest tests/validators/test_email.py -v`
Expected: FAIL with "ModuleNotFoundError: No module named 'src.validators.email'"
**Step 3: Write minimal implementation**
```python
# src/validators/email.py
import re
def validate_email(email):
pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
if re.match(pattern, email):
return {"valid": True}
return {"valid": False, "error": "Invalid format"}
```
**Step 4: Run test to verify it passes**
Run: `pytest tests/validators/test_email.py -v`
Expected: PASS (2 tests)
**Step 5: Commit**
```bash
git add tests/validators/test_email.py src/validators/email.py
git commit -m "feat: add email validation"
```
## Best Practices
**Be specific:**
- Use exact file paths and line numbers
- Show complete code, not pseudocode
- Specify exact commands to run
**Be minimal:**
- Follow YAGNI - don't add features not in requirements
- Keep implementations simple
- Add complexity only when tests demand it
**Be testable:**
- Every feature has tests
- Tests written before implementation (TDD)
- Clear verification steps
**Be incremental:**
- Small commits after each working change
- Each task independently deliverable
- Build progressively
## Common Mistakes to Avoid
- Don't write "add validation" - show the exact validation code
- Don't write "update config" - show exact config changes
- Don't skip test commands - always show how to verify
- Don't make tasks too large - break down into 2-5 minute steps
- Don't assume knowledge of project structure - specify full paths
## Quick Reference
| Element | Required | Example |
|---------|----------|---------|
| File paths | Always exact | `src/auth/login.py` |
| Code examples | Complete & working | Full function/test |
| Commands | With expected output | `pytest path/test.py -v` → PASS |
| Commits | After each task | `git commit -m "feat: add feature"` |
| Granularity | 2-5 min per step | One action per step |
## Final Rule
```text
Plans should be executable by someone skilled but unfamiliar.
Every step: exact paths, complete code, clear verification.
```
Clear plans enable confident execution.
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.