
Cc Skill Project Guidelines Example
- 515 installs
- 44k repo stars
- Updated July 27, 2026
- sickn33/antigravity-awesome-skills
cc-skill-project-guidelines-example is a Claude Code skill template that shows how to encode one repository's architecture, file structure, testing rules, and deployment workflow so coding agents follow project-specific
About
cc-skill-project-guidelines-example is a sickn33/antigravity-awesome-skills template skill demonstrating how to author project-specific Claude Code guidance from a real production application. The example—based on the Zenith AI customer discovery platform—documents architecture overview, repository file structure, code patterns, testing requirements, and deployment workflow sections agents should load when touching that codebase. Developers reach for cc-skill-project-guidelines-example when creating a new SKILL.md for their own repository and need a proven section layout rather than inventing agent onboarding from scratch. The skill is explicitly labeled an example to clone, not a drop-in configuration for unrelated projects. It bridges build and ship concerns by encoding test gates and deploy steps alongside frontend patterns such as Next.js conventions referenced in the sample architecture. Use it as the starting scaffold before customizing architecture and CI details for a target repository.
- Example skill shaped after a production Zenith-style customer-discovery SaaS
- Architecture overview: Next.js 15, FastAPI, Supabase, Claude API, Cloud Run
- Explicit sections for file structure, code patterns, testing, and deployment workflow
- When to Use block for referencing the skill only on its target project
- Template intent—swap stack details for your own monorepo or services map
Cc Skill Project Guidelines Example by the numbers
- 515 all-time installs (skills.sh)
- Ranked #96 of 826 Skill Development skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Jul 28, 2026 (Skillselion catalog sync)
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| Installs | 515 |
|---|---|
| repo stars | ★ 44k |
| Security audit | 3 / 3 scanners passed |
| Last updated | July 27, 2026 |
| Repository | sickn33/antigravity-awesome-skills ↗ |
How do you write a project-specific Claude Code skill?
Clone this SKILL.md pattern so your agent always follows one repo’s architecture, tests, and deploy steps instead of generic guesses.
Who is it for?
Developers authoring their first project-specific agent skill who want a production-based SKILL.md template with architecture, testing, and deploy sections.
Skip if: Teams seeking ready-made domain expertise without customization should skip cc-skill-project-guidelines-example because it is an example scaffold, not a finished skill.
When should I use this skill?
Trigger when creating or updating a repository-specific SKILL.md that must encode architecture, tests, and deployment conventions for agents.
What you get
A customized project SKILL.md with architecture, file structure, code patterns, testing rules, and deployment workflow
- Project-specific SKILL.md
- Agent convention documentation
Files
Project Guidelines Skill (Example)
This is an example of a project-specific skill. Use this as a template for your own projects.
Based on a real production application: Zenith - AI-powered customer discovery platform.
---
When to Use
Reference this skill when working on the specific project it's designed for. Project skills contain:
- Architecture overview
- File structure
- Code patterns
- Testing requirements
- Deployment workflow
---
Architecture Overview
Tech Stack:
- Frontend: Next.js 15 (App Router), TypeScript, React
- Backend: FastAPI (Python), Pydantic models
- Database: Supabase (PostgreSQL)
- AI: Claude API with tool calling and structured output
- Deployment: Google Cloud Run
- Testing: Playwright (E2E), pytest (backend), React Testing Library
Services:
┌─────────────────────────────────────────────────────────────┐
│ Frontend │
│ Next.js 15 + TypeScript + TailwindCSS │
│ Deployed: Vercel / Cloud Run │
└─────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ Backend │
│ FastAPI + Python 3.11 + Pydantic │
│ Deployed: Cloud Run │
└─────────────────────────────────────────────────────────────┘
│
┌───────────────┼───────────────┐
▼ ▼ ▼
┌──────────┐ ┌──────────┐ ┌──────────┐
│ Supabase │ │ Claude │ │ Redis │
│ Database │ │ API │ │ Cache │
└──────────┘ └──────────┘ └──────────┘---
File Structure
project/
├── frontend/
│ └── src/
│ ├── app/ # Next.js app router pages
│ │ ├── api/ # API routes
│ │ ├── (auth)/ # Auth-protected routes
│ │ └── workspace/ # Main app workspace
│ ├── components/ # React components
│ │ ├── ui/ # Base UI components
│ │ ├── forms/ # Form components
│ │ └── layouts/ # Layout components
│ ├── hooks/ # Custom React hooks
│ ├── lib/ # Utilities
│ ├── types/ # TypeScript definitions
│ └── config/ # Configuration
│
├── backend/
│ ├── routers/ # FastAPI route handlers
│ ├── models.py # Pydantic models
│ ├── main.py # FastAPI app entry
│ ├── auth_system.py # Authentication
│ ├── database.py # Database operations
│ ├── services/ # Business logic
│ └── tests/ # pytest tests
│
├── deploy/ # Deployment configs
├── docs/ # Documentation
└── scripts/ # Utility scripts---
Code Patterns
API Response Format (FastAPI)
from pydantic import BaseModel
from typing import Generic, TypeVar, Optional
T = TypeVar('T')
class ApiResponse(BaseModel, Generic[T]):
success: bool
data: Optional[T] = None
error: Optional[str] = None
@classmethod
def ok(cls, data: T) -> "ApiResponse[T]":
return cls(success=True, data=data)
@classmethod
def fail(cls, error: str) -> "ApiResponse[T]":
return cls(success=False, error=error)Frontend API Calls (TypeScript)
interface ApiResponse<T> {
success: boolean
data?: T
error?: string
}
async function fetchApi<T>(
endpoint: string,
options?: RequestInit
): Promise<ApiResponse<T>> {
try {
const response = await fetch(`/api${endpoint}`, {
...options,
headers: {
'Content-Type': 'application/json',
...options?.headers,
},
})
if (!response.ok) {
return { success: false, error: `HTTP ${response.status}` }
}
return await response.json()
} catch (error) {
return { success: false, error: String(error) }
}
}Claude AI Integration (Structured Output)
from anthropic import Anthropic
from pydantic import BaseModel
class AnalysisResult(BaseModel):
summary: str
key_points: list[str]
confidence: float
async def analyze_with_claude(content: str) -> AnalysisResult:
client = Anthropic()
response = client.messages.create(
model="claude-sonnet-4-5-20250514",
max_tokens=1024,
messages=[{"role": "user", "content": content}],
tools=[{
"name": "provide_analysis",
"description": "Provide structured analysis",
"input_schema": AnalysisResult.model_json_schema()
}],
tool_choice={"type": "tool", "name": "provide_analysis"}
)
# Extract tool use result
tool_use = next(
block for block in response.content
if block.type == "tool_use"
)
return AnalysisResult(**tool_use.input)Custom Hooks (React)
import { useState, useCallback } from 'react'
interface UseApiState<T> {
data: T | null
loading: boolean
error: string | null
}
export function useApi<T>(
fetchFn: () => Promise<ApiResponse<T>>
) {
const [state, setState] = useState<UseApiState<T>>({
data: null,
loading: false,
error: null,
})
const execute = useCallback(async () => {
setState(prev => ({ ...prev, loading: true, error: null }))
const result = await fetchFn()
if (result.success) {
setState({ data: result.data!, loading: false, error: null })
} else {
setState({ data: null, loading: false, error: result.error! })
}
}, [fetchFn])
return { ...state, execute }
}---
Testing Requirements
Backend (pytest)
# Run all tests
poetry run pytest tests/
# Run with coverage
poetry run pytest tests/ --cov=. --cov-report=html
# Run specific test file
poetry run pytest tests/test_auth.py -vTest structure:
import pytest
from httpx import AsyncClient
from main import app
@pytest.fixture
async def client():
async with AsyncClient(app=app, base_url="http://test") as ac:
yield ac
@pytest.mark.asyncio
async def test_health_check(client: AsyncClient):
response = await client.get("/health")
assert response.status_code == 200
assert response.json()["status"] == "healthy"Frontend (React Testing Library)
# Run tests
npm run test
# Run with coverage
npm run test -- --coverage
# Run E2E tests
npm run test:e2eTest structure:
import { render, screen, fireEvent } from '@testing-library/react'
import { WorkspacePanel } from './WorkspacePanel'
describe('WorkspacePanel', () => {
it('renders workspace correctly', () => {
render(<WorkspacePanel />)
expect(screen.getByRole('main')).toBeInTheDocument()
})
it('handles session creation', async () => {
render(<WorkspacePanel />)
fireEvent.click(screen.getByText('New Session'))
expect(await screen.findByText('Session created')).toBeInTheDocument()
})
})---
Deployment Workflow
Pre-Deployment Checklist
- [ ] All tests passing locally
- [ ]
npm run buildsucceeds (frontend) - [ ]
poetry run pytestpasses (backend) - [ ] No hardcoded secrets
- [ ] Environment variables documented
- [ ] Database migrations ready
Deployment Commands
# Build and deploy frontend
cd frontend && npm run build
gcloud run deploy frontend --source .
# Build and deploy backend
cd backend
gcloud run deploy backend --source .Environment Variables
# Frontend (.env.local)
NEXT_PUBLIC_API_URL=https://api.example.com
NEXT_PUBLIC_SUPABASE_URL=https://xxx.supabase.co
NEXT_PUBLIC_SUPABASE_ANON_KEY=eyJ...
# Backend (.env)
DATABASE_URL=postgresql://...
ANTHROPIC_API_KEY=sk-ant-...
SUPABASE_URL=https://xxx.supabase.co
SUPABASE_KEY=eyJ...---
Critical Rules
1. No emojis in code, comments, or documentation 2. Immutability - never mutate objects or arrays 3. TDD - write tests before implementation 4. 80% coverage minimum 5. Many small files - 200-400 lines typical, 800 max 6. No console.log in production code 7. Proper error handling with try/catch 8. Input validation with Pydantic/Zod
---
Related Skills
coding-standards.md- General coding best practicesbackend-patterns.md- API and database patternsfrontend-patterns.md- React and Next.js patternstdd-workflow/- Test-driven development methodology
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
Related skills
FAQ
Is cc-skill-project-guidelines-example meant to be used directly?
cc-skill-project-guidelines-example is a template to clone and customize for a specific repository. It documents Zenith's architecture, tests, and deploy flow as a reference layout, not a universal skill.
What sections should a project skill include?
cc-skill-project-guidelines-example shows architecture overview, file structure, code patterns, testing requirements, and deployment workflow sections. Agents reference these when working inside the target project.
Is Cc Skill Project Guidelines Example safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.