project-guidelines-example

Example project-specific skill template based on a real production application.

16 stars

Best use case

project-guidelines-example is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Example project-specific skill template based on a real production application.

Teams using project-guidelines-example should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/project-guidelines-example/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/development/project-guidelines-example/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/project-guidelines-example/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How project-guidelines-example Compares

Feature / Agentproject-guidelines-exampleStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Example project-specific skill template based on a real production application.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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](https://zenith.chat) - 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)

```python
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)

```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)

```python
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)

```typescript
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)

```bash
# 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 -v
```

**Test structure:**
```python
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)

```bash
# Run tests
npm run test

# Run with coverage
npm run test -- --coverage

# Run E2E tests
npm run test:e2e
```

**Test structure:**
```typescript
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 build` succeeds (frontend)
- [ ] `poetry run pytest` passes (backend)
- [ ] No hardcoded secrets
- [ ] Environment variables documented
- [ ] Database migrations ready

### Deployment Commands

```bash
# 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

```bash
# 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 practices
- `backend-patterns.md` - API and database patterns
- `frontend-patterns.md` - React and Next.js patterns
- `tdd-workflow/` - Test-driven development methodology

Related Skills

python-backend-guidelines

16
from diegosouzapw/awesome-omni-skill

FastAPI/Django backend patterns and best practices

project-scaffolder

16
from diegosouzapw/awesome-omni-skill

Guide for setting up Claude Code infrastructure in new or existing projects

project-qtax

16
from diegosouzapw/awesome-omni-skill

UK taxation expert for HMRC compliance, Making Tax Digital (MTD ITSA/VAT) and Self-Assessment: explain tax treatment; compute income tax/NI/dividend/CGT with band-by-band breakdown; advise on deadlines/forms/penalties; and support MTD developer integration + tax software UX/flows. Use WebSearch (gov.uk/HMRC) to verify current rates and mandation timelines. (project)

project-overview

16
from diegosouzapw/awesome-omni-skill

Background knowledge about CaCrFeedFormula project architecture, features, and context. Automatically loaded for AI reference, not directly user-invocable.

project-orchestration

16
from diegosouzapw/awesome-omni-skill

Orchestrate multi-agent workflows for feature development using planning agents, context handoff, and stage management

project-object

16
from diegosouzapw/awesome-omni-skill

Session memory that compounds - remember decisions, patterns, and corrections across AI coding sessions. Includes standards injection for consistent code quality.

project-mngt

16
from diegosouzapw/awesome-omni-skill

Product Owner / Project Manager skill for MVP/MMP/MMR implementation planning

project-logger

16
from diegosouzapw/awesome-omni-skill

SQLite-based project documentation logger for tracking API references, components, and project progress. Use this skill when documenting code changes, adding API documentation, recording component updates, or tracking project milestones. Automatically invoked when user mentions documentation, changelog, API docs, component docs, or project updates.

project-init

16
from diegosouzapw/awesome-omni-skill

Automatically detects new project initialization, collaborates with user on project planning, and sets up the appropriate tech stack with matching skills and agents. Use when starting a new project, creating a new repository, or working in an empty/minimal directory that needs project structure.

project-index

16
from diegosouzapw/awesome-omni-skill

Use this skill for large project maintenance with layered CLAUDE.md index system. Triggers when users need to (1) analyze and document existing codebases, (2) generate hierarchical CLAUDE.md files for modules, (3) set up incremental update hooks after code changes, or (4) navigate large projects efficiently. Supports legacy project onboarding and automatic context management.

project-development

16
from diegosouzapw/awesome-omni-skill

This skill should be used when the user asks to "start an LLM project", "design batch pipeline", "evaluate task-model fit", "structure agent project", or mentions pipeline architecture, agent-assisted development, cost estimation, or choosing between LLM and traditional approaches.

project-context-discovery

16
from diegosouzapw/awesome-omni-skill

Discover project structure, package managers, test frameworks, and automation without hardcoded assumptions