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Senior Backend

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yezannnnn
senior-backend

This skill should be used when the user asks to "design REST APIs", "optimize database queries", "implement authentication", "build microservices", "review backend code", "set up GraphQL", "handle database migrations", or "load test APIs". Use for Node.js/Express/Fastify development, PostgreSQL optimization, API security, and backend architecture patterns.

Overview

Publisheryezannnnn
RepositoryagentGroup
Skill namesenior-backend
Stars
149
Forks
49
Bundled files
6
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by yezannnnn on GitHub. Read the source before you install it.

Installation

Install the Senior Backend AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/yezannnnn/agentGroup.git /tmp/agentGroup
mkdir -p .claude/skills
cp -r /tmp/agentGroup/jarvis/skills/engineering-team/senior-backend .claude/skills/senior-backend
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Senior Backend in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Senior Backend on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Senior Backend is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Senior Backend Engineer

Backend development patterns, API design, database optimization, and security practices.

Table of Contents


Quick Start

bash
# Generate API routes from OpenAPI spec
python scripts/api_scaffolder.py openapi.yaml --framework express --output src/routes/

# Analyze database schema and generate migrations
python scripts/database_migration_tool.py --connection postgres://localhost/mydb --analyze

# Load test an API endpoint
python scripts/api_load_tester.py https://api.example.com/users --concurrency 50 --duration 30

Tools Overview

1. API Scaffolder

Generates API route handlers, middleware, and OpenAPI specifications from schema definitions.

Input: OpenAPI spec (YAML/JSON) or database schema Output: Route handlers, validation middleware, TypeScript types

Usage:

bash
# Generate Express routes from OpenAPI spec
python scripts/api_scaffolder.py openapi.yaml --framework express --output src/routes/

# Output:
# Generated 12 route handlers in src/routes/
# - GET /users (listUsers)
# - POST /users (createUser)
# - GET /users/{id} (getUser)
# - PUT /users/{id} (updateUser)
# - DELETE /users/{id} (deleteUser)
# ...
# Created validation middleware: src/middleware/validators.ts
# Created TypeScript types: src/types/api.ts

# Generate from database schema
python scripts/api_scaffolder.py --from-db postgres://localhost/mydb --output src/routes/

# Generate OpenAPI spec from existing routes
python scripts/api_scaffolder.py src/routes/ --generate-spec --output openapi.yaml

Supported Frameworks:

  • Express.js (--framework express)
  • Fastify (--framework fastify)
  • Koa (--framework koa)

2. Database Migration Tool

Analyzes database schemas, detects changes, and generates migration files with rollback support.

Input: Database connection string or schema files Output: Migration files, schema diff report, optimization suggestions

Usage:

bash
# Analyze current schema and suggest optimizations
python scripts/database_migration_tool.py --connection postgres://localhost/mydb --analyze

# Output:
# === Database Analysis Report ===
# Tables: 24
# Total rows: 1,247,832
#
# MISSING INDEXES (5 found):
#   orders.user_id - 847ms avg query time, ADD INDEX recommended
#   products.category_id - 234ms avg query time, ADD INDEX recommended
#
# N+1 QUERY RISKS (3 found):
#   users -> orders relationship (no eager loading)
#
# SUGGESTED MIGRATIONS:
#   1. Add index on orders(user_id)
#   2. Add index on products(category_id)
#   3. Add composite index on order_items(order_id, product_id)

# Generate migration from schema diff
python scripts/database_migration_tool.py --connection postgres://localhost/mydb \
  --compare schema/v2.sql --output migrations/

# Output:
# Generated migration: migrations/20240115_add_user_indexes.sql
# Generated rollback: migrations/20240115_add_user_indexes_rollback.sql

# Dry-run a migration
python scripts/database_migration_tool.py --connection postgres://localhost/mydb \
  --migrate migrations/20240115_add_user_indexes.sql --dry-run

3. API Load Tester

Performs HTTP load testing with configurable concurrency, measuring latency percentiles and throughput.

Input: API endpoint URL and test configuration Output: Performance report with latency distribution, error rates, throughput metrics

Usage:

bash
# Basic load test
python scripts/api_load_tester.py https://api.example.com/users --concurrency 50 --duration 30

# Output:
# === Load Test Results ===
# Target: https://api.example.com/users
# Duration: 30s | Concurrency: 50
#
# THROUGHPUT:
#   Total requests: 15,247
#   Requests/sec: 508.2
#   Successful: 15,102 (99.0%)
#   Failed: 145 (1.0%)
#
# LATENCY (ms):
#   Min: 12
#   Avg: 89
#   P50: 67
#   P95: 198
#   P99: 423
#   Max: 1,247
#
# ERRORS:
#   Connection timeout: 89
#   HTTP 503: 56
#
# RECOMMENDATION: P99 latency (423ms) exceeds 200ms target.
# Consider: connection pooling, query optimization, or horizontal scaling.

# Test with custom headers and body
python scripts/api_load_tester.py https://api.example.com/orders \
  --method POST \
  --header "Authorization: Bearer token123" \
  --body '{"product_id": 1, "quantity": 2}' \
  --concurrency 100 \
  --duration 60

# Compare two endpoints
python scripts/api_load_tester.py https://api.example.com/v1/users https://api.example.com/v2/users \
  --compare --concurrency 50 --duration 30

Backend Development Workflows

API Design Workflow

Use when designing a new API or refactoring existing endpoints.

Step 1: Define resources and operations

yaml
# openapi.yaml
openapi: 3.0.3
info:
  title: User Service API
  version: 1.0.0
paths:
  /users:
    get:
      summary: List users
      parameters:
        - name: limit
          in: query
          schema:
            type: integer
            default: 20
    post:
      summary: Create user
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateUser'

Step 2: Generate route scaffolding

bash
python scripts/api_scaffolder.py openapi.yaml --framework express --output src/routes/

Step 3: Implement business logic

typescript
// src/routes/users.ts (generated, then customized)
export const createUser = async (req: Request, res: Response) => {
  const { email, name } = req.body;

  // Add business logic
  const user = await userService.create({ email, name });

  res.status(201).json(user);
};

Step 4: Add validation middleware

bash
# Validation is auto-generated from OpenAPI schema
# src/middleware/validators.ts includes:
# - Request body validation
# - Query parameter validation
# - Path parameter validation

Step 5: Generate updated OpenAPI spec

bash
python scripts/api_scaffolder.py src/routes/ --generate-spec --output openapi.yaml

Database Optimization Workflow

Use when queries are slow or database performance needs improvement.

Step 1: Analyze current performance

bash
python scripts/database_migration_tool.py --connection $DATABASE_URL --analyze

Step 2: Identify slow queries

sql
-- Check query execution plans
EXPLAIN ANALYZE SELECT * FROM orders
WHERE user_id = 123
ORDER BY created_at DESC
LIMIT 10;

-- Look for: Seq Scan (bad), Index Scan (good)

Step 3: Generate index migrations

bash
python scripts/database_migration_tool.py --connection $DATABASE_URL \
  --suggest-indexes --output migrations/

Step 4: Test migration (dry-run)

bash
python scripts/database_migration_tool.py --connection $DATABASE_URL \
  --migrate migrations/add_indexes.sql --dry-run

Step 5: Apply and verify

bash
# Apply migration
python scripts/database_migration_tool.py --connection $DATABASE_URL \
  --migrate migrations/add_indexes.sql

# Verify improvement
python scripts/database_migration_tool.py --connection $DATABASE_URL --analyze

Security Hardening Workflow

Use when preparing an API for production or after a security review.

Step 1: Review authentication setup

typescript
// Verify JWT configuration
const jwtConfig = {
  secret: process.env.JWT_SECRET,  // Must be from env, never hardcoded
  expiresIn: '1h',                 // Short-lived tokens
  algorithm: 'RS256'               // Prefer asymmetric
};

Step 2: Add rate limiting

typescript
import rateLimit from 'express-rate-limit';

const apiLimiter = rateLimit({
  windowMs: 15 * 60 * 1000,  // 15 minutes
  max: 100,                   // 100 requests per window
  standardHeaders: true,
  legacyHeaders: false,
});

app.use('/api/', apiLimiter);

Step 3: Validate all inputs

typescript
import { z } from 'zod';

const CreateUserSchema = z.object({
  email: z.string().email().max(255),
  name: z.string().min(1).max(100),
  age: z.number().int().positive().optional()
});

// Use in route handler
const data = CreateUserSchema.parse(req.body);

Step 4: Load test with attack patterns

bash
# Test rate limiting
python scripts/api_load_tester.py https://api.example.com/login \
  --concurrency 200 --duration 10 --expect-rate-limit

# Test input validation
python scripts/api_load_tester.py https://api.example.com/users \
  --method POST \
  --body '{"email": "not-an-email"}' \
  --expect-status 400

Step 5: Review security headers

typescript
import helmet from 'helmet';

app.use(helmet({
  contentSecurityPolicy: true,
  crossOriginEmbedderPolicy: true,
  crossOriginOpenerPolicy: true,
  crossOriginResourcePolicy: true,
  hsts: { maxAge: 31536000, includeSubDomains: true },
}));

Reference Documentation

FileContainsUse When
references/api_design_patterns.mdREST vs GraphQL, versioning, error handling, paginationDesigning new APIs
references/database_optimization_guide.mdIndexing strategies, query optimization, N+1 solutionsFixing slow queries
references/backend_security_practices.mdOWASP Top 10, auth patterns, input validationSecurity hardening

Common Patterns Quick Reference

REST API Response Format

json
{
  "data": { "id": 1, "name": "John" },
  "meta": { "requestId": "abc-123" }
}

Error Response Format

json
{
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid email format",
    "details": [{ "field": "email", "message": "must be valid email" }]
  },
  "meta": { "requestId": "abc-123" }
}

HTTP Status Codes

CodeUse Case
200Success (GET, PUT, PATCH)
201Created (POST)
204No Content (DELETE)
400Validation error
401Authentication required
403Permission denied
404Resource not found
429Rate limit exceeded
500Internal server error

Database Index Strategy

sql
-- Single column (equality lookups)
CREATE INDEX idx_users_email ON users(email);

-- Composite (multi-column queries)
CREATE INDEX idx_orders_user_status ON orders(user_id, status);

-- Partial (filtered queries)
CREATE INDEX idx_orders_active ON orders(created_at) WHERE status = 'active';

-- Covering (avoid table lookup)
CREATE INDEX idx_users_email_name ON users(email) INCLUDE (name);

Common Commands

bash
# API Development
python scripts/api_scaffolder.py openapi.yaml --framework express
python scripts/api_scaffolder.py src/routes/ --generate-spec

# Database Operations
python scripts/database_migration_tool.py --connection $DATABASE_URL --analyze
python scripts/database_migration_tool.py --connection $DATABASE_URL --migrate file.sql

# Performance Testing
python scripts/api_load_tester.py https://api.example.com/endpoint --concurrency 50
python scripts/api_load_tester.py https://api.example.com/endpoint --compare baseline.json

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Senior Backend AI skill do?

This skill should be used when the user asks to "design REST APIs", "optimize database queries", "implement authentication", "build microservices", "review backend code", "set up GraphQL", "handle database migrations", or "load test APIs". Use for Node.js/Express/Fastify development, PostgreSQL optimization, API security, and backend architecture patterns.

Why use Senior Backend on TypingMind?

Because you install it once and use it with any model. Senior Backend is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Senior Backend in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yezannnnn/agentGroup/tree/master/jarvis/skills/engineering-team/senior-backend. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Senior Backend?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Senior Backend?

As many as you like. As long as a model supports skills, you can use Senior Backend with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Senior Backend AI skill free?

Yes. It is published on GitHub by yezannnnn under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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