backend-patterns

A reference guide for building server-side applications with Node.js, Express, and Next.js API routes.

In plain words
What is it for?
It helps design REST or GraphQL endpoints, improve database queries, add authentication or rate limits, and organize backend code.
Why use it?
It provides patterns for structuring APIs, database access, caching, background jobs, validation, errors, and middleware.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/tpavanipradeep/everything-claude-code/backend-patterns
Any agent
npx skills add tpavanipradeep/everything-claude-code --skill backend-patterns
Clone the repo
git clone --depth 1 https://github.com/tpavanipradeep/everything-claude-code

Made for: Claude Code, Codex.

Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,331 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin 94% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00031 $0.03331
Opus 5 $0.00015 $0.01665
Sonnet 5 $0.00006 $0.00666
Haiku 4.5 $0.00003 $0.00333

Measured 2d ago against content hash 681c33b4e125, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

backend-patterns scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

const requests = this.requests.get(identifier) || []
Origin

This is a copy

94% identical to backend-patterns — 15 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/backend-patterns/SKILL.md · 599 lines

How it starts

The opening of the file, as written. The whole thing — 599 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Backend Development Patterns

Backend architecture patterns and best practices for scalable server-side applications.

When to Activate

  • Designing REST or GraphQL API endpoints
  • Implementing repository, service, or controller layers
  • Optimizing database queries (N+1, indexing, connection pooling)
  • Adding caching (Redis, in-memory, HTTP cache headers)
  • Setting up background jobs or async processing
  • Structuring error handling and validation for APIs
  • Building middleware (auth, logging, rate limiting)

API Design Patterns

RESTful API Structure

// ✅ 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

// 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

// 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
  }
}

Read the full file on GitHub · 599 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 599 lines · 31 tokens per session scan A 681c33b4e125

Subscribe to this mod's changes

backend-patterns is a skill published in the GitHub repository tpavanipradeep/everything-claude-code (104 stars, last pushed 5mo ago), licensed MIT. It adds 31 tokens to every session and 3,331 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 94% identical to backend-patterns, differing in 15 lines, and is treated as a copy.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens