Cc Skill Backend Patterns
Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.
mkdir -p ./skills/cc-skill-backend-patterns && curl -sfL https://raw.githubusercontent.com/mayurrathi/awesome-agent-skills/main/skills/cc-skill-backend-patterns/SKILL.md -o ./skills/cc-skill-backend-patterns/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Backend Development Patterns
Backend architecture patterns and best practices for scalable server-side applications.
API Design Patterns
RESTful API Structure
```typescript
// ✅ Resource-based URLs
GET /api/markets # List resources
GET /api/markets/:id # Get single resource
POST /api/markets # Create resource
PUT /api/markets/:id # Replace resource
PATCH /api/markets/:id # Update resource
DELETE /api/markets/:id # Delete resource
// ✅ Query parameters for filtering, sorting, pagination
GET /api/markets?status=active&sort=volume&limit=20&offset=0
```
Repository Pattern
```typescript
// Abstract data access logic
interface MarketRepository {
findAll(filters?: MarketFilters): Promise<Market[]>
findById(id: string): Promise<Market | null>
create(data: CreateMarketDto): Promise<Market>
update(id: string, data: UpdateMarketDto): Promise<Market>
delete(id: string): Promise<void>
}
class SupabaseMarketRepository implements MarketRepository {
async findAll(filters?: MarketFilters): Promise<Market[]> {
let query = supabase.from('markets').select('*')
if (filters?.status) {
query = query.eq('status', filters.status)
}
if (filters?.limit) {
query = query.limit(filters.limit)
}
const { data, error } = await query
if (error) throw new Error(error.message)
return data
}
// Other methods...
}
```
Service Layer Pattern
```typescript
// Business logic separated from data access
class MarketService {
constructor(private marketRepo: MarketRepository) {}
async searchMarkets(query: string, limit: number = 10): Promise<Market[]> {
// Business logic
const embedding = await generateEmbedding(query)
const results = await this.vectorSearch(embedding, limit)
// Fetch full data
const markets = await this.marketRepo.findByIds(results.map(r => r.id))
// Sort by similarity
return markets.sort((a, b) => {
const scoreA = results.find(r => r.id === a.id)?.score || 0
const scoreB = results.find(r => r.id === b.id)?.score || 0
return scoreA - scoreB
})
}
private async vectorSearch(embedding: number[], limit: number) {
// Vector search implementation
}
}
```
Middleware Pattern
```typescript
// Request/response processing pipeline
export function withAuth(handler: NextApiHandler): NextApiHandler {
return async (req, res) => {
const token = req.headers.authorization?.replace('Bearer ', '')
if (!token) {
return res.status(401).json({ error: 'Unauthorized' })
}
try {
const user = await verifyToken(token)
req.user = user
return handler(req, res)
} catch (error) {
return res.status(401).json({ error: 'Invalid token' })
}
}
}
// Usage
export default withAuth(async (req, res) => {
// Handler has access to req.user
})
```
Database Patterns
Query Optimization
```typescript
// ✅ GOOD: Select only needed columns
const { data } = await supabase
.from('markets')
.select('id, name, status, volume')
.eq('status', 'active')
.order('volume', { ascending: false })
.limit(10)
// ❌ BAD: Select everything
const { data } = await supabase
.from('markets')
.select('*')
```
N+1 Query Prevention
```typescript
// ❌ BAD: N+1 query problem
const markets = await getMarkets()
for (const market of markets) {
market.creator = await getUser(market.creator_id) // N queries
}
// ✅ GOOD: Batch fetch
const markets = await getMarkets()
const creatorIds = markets.map(m => m.creator_id)
const creators = await getUsers(creatorIds) // 1 query
const creatorMap = new Map(creators.map(c => [c.id, c]))
markets.forEach(market => {
market.creator = creatorMap.get(market.creator_id)
})
```
Transaction Pattern
```typescript
async function createMarketWithPosition(
marketData: CreateMarketDto,
positionData: CreatePositionDto
) {
// Use Supabase transa
🎯 Best For
- Claude users
- Software engineers
- Development teams
- Tech leads
💡 Use Cases
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Cc Skill Backend Patterns to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Is Cc Skill Backend Patterns compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for Cc Skill Backend Patterns?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install Cc Skill Backend Patterns?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/cc-skill-backend-patterns/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
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