Agent Skills: Database Management Skill

Master relational and NoSQL databases. Learn PostgreSQL, MySQL, MongoDB, Redis, and other technologies for data persistence, optimization, and scaling.

nosqlpostgresqlmysqlmongoDBredis
databaseID: pluginagentmarketplace/custom-plugin-backend/databases

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skills/databases/SKILL.md

Skill Metadata

Name
databases
Description
Master relational and NoSQL databases. Learn PostgreSQL, MySQL, MongoDB, Redis, and other technologies for data persistence, optimization, and scaling.

Database Management Skill

Bonded to: database-management-agent


Quick Start

# Invoke databases skill
"Design a database schema for my e-commerce application"
"Optimize slow queries in PostgreSQL"
"Set up Redis caching for session storage"

Instructions

  1. Analyze Requirements: Understand data patterns, volume, access needs
  2. Select Database: Choose SQL vs NoSQL based on requirements
  3. Design Schema: Create data models, relationships, constraints
  4. Optimize Queries: Implement indexes, analyze execution plans
  5. Set Up Operations: Configure backup, replication, monitoring

Database Selection Guide

| Type | Best For | ACID | Scale | Examples | |------|----------|------|-------|----------| | Relational | Complex queries, transactions | Full | Vertical | PostgreSQL, MySQL | | Document | Flexible schema, JSON | Partial | Horizontal | MongoDB | | Key-Value | Caching, sessions | No | Horizontal | Redis | | Wide-Column | Time series, analytics | Partial | Horizontal | Cassandra | | Graph | Relationships | Varies | Varies | Neo4j | | Search | Full-text search | No | Horizontal | Elasticsearch |


Decision Tree

Need ACID transactions?
    │
    ├─→ Yes → Complex queries?
    │           ├─→ Yes → PostgreSQL
    │           └─→ No  → MySQL
    │
    └─→ No  → Data type?
              ├─→ Documents/JSON → MongoDB
              ├─→ Key-Value pairs → Redis
              ├─→ Time series → Cassandra/TimescaleDB
              └─→ Full-text search → Elasticsearch

Examples

Example 1: Schema Design

-- E-commerce schema
CREATE TABLE users (
    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    email VARCHAR(255) UNIQUE NOT NULL,
    password_hash VARCHAR(255) NOT NULL,
    created_at TIMESTAMPTZ DEFAULT NOW()
);

CREATE TABLE products (
    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    name VARCHAR(255) NOT NULL,
    price DECIMAL(10,2) NOT NULL CHECK (price > 0),
    stock INTEGER NOT NULL DEFAULT 0
);

CREATE TABLE orders (
    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    user_id UUID REFERENCES users(id),
    total DECIMAL(10,2) NOT NULL,
    status VARCHAR(50) DEFAULT 'pending',
    created_at TIMESTAMPTZ DEFAULT NOW()
);

-- Indexes for common queries
CREATE INDEX idx_orders_user_id ON orders(user_id);
CREATE INDEX idx_orders_created_at ON orders(created_at DESC);

Example 2: Query Optimization

-- Before: Full table scan
EXPLAIN ANALYZE SELECT * FROM orders WHERE user_id = 'abc123';

-- After: Add index
CREATE INDEX idx_orders_user_id ON orders(user_id);

-- Optimized query with selected columns
SELECT id, total, status, created_at
FROM orders
WHERE user_id = 'abc123'
ORDER BY created_at DESC
LIMIT 10;

Example 3: Redis Caching

import redis
import json

r = redis.Redis(host='localhost', port=6379, decode_responses=True)

def get_user(user_id: str) -> dict:
    # Try cache first
    cached = r.get(f"user:{user_id}")
    if cached:
        return json.loads(cached)

    # Cache miss - fetch from DB
    user = db.query(User).get(user_id)
    if user:
        r.setex(f"user:{user_id}", 3600, json.dumps(user.dict()))
    return user.dict()

Troubleshooting

Common Issues

| Issue | Cause | Solution | |-------|-------|----------| | Query timeout | Missing index | Run EXPLAIN ANALYZE, add index | | Connection refused | Wrong config | Check host, port, credentials | | Deadlock | Concurrent updates | Use proper isolation, retry logic | | OOM on query | Large result set | Add LIMIT, use cursors |

Debug Commands

-- PostgreSQL: Check slow queries
SELECT query, calls, mean_time
FROM pg_stat_statements
ORDER BY mean_time DESC LIMIT 10;

-- Check active connections
SELECT * FROM pg_stat_activity WHERE state = 'active';

-- Check table sizes
SELECT relname, pg_size_pretty(pg_total_relation_size(relid))
FROM pg_stat_user_tables
ORDER BY pg_total_relation_size(relid) DESC;

Test Template

# tests/test_database.py
import pytest
from sqlalchemy import create_engine

class TestDatabaseSchema:
    @pytest.fixture
    def engine(self):
        return create_engine("postgresql://test:test@localhost/testdb")

    def test_users_table_exists(self, engine):
        result = engine.execute("SELECT 1 FROM users LIMIT 1")
        assert result is not None

    def test_foreign_key_constraint(self, engine):
        with pytest.raises(IntegrityError):
            engine.execute(
                "INSERT INTO orders (user_id, total) VALUES ('invalid-uuid', 100)"
            )

References

See references/ directory for:

  • DATABASE_GUIDE.md - Detailed database patterns
  • Schema templates and examples

Resources