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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/miles990/claude-software-skills --skill database- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads database automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Database Development
Overview
Database design, query optimization, and data management patterns for relational and NoSQL databases.
PostgreSQL
Schema Design
-- Users table with proper constraints
CREATE TABLE users (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
email VARCHAR(255) NOT NULL UNIQUE,
password_hash VARCHAR(255) NOT NULL,
name VARCHAR(100),
role VARCHAR(20) DEFAULT 'user' CHECK (role IN ('user', 'admin', 'moderator')),
status VARCHAR(20) DEFAULT 'active' CHECK (status IN ('active', 'suspended', 'deleted')),
metadata JSONB DEFAULT '{}',
created_at TIMESTAMPTZ DEFAULT NOW(),
updated_at TIMESTAMPTZ DEFAULT NOW()
);
-- Posts with foreign key
CREATE TABLE posts (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
title VARCHAR(255) NOT NULL,
slug VARCHAR(255) NOT NULL UNIQUE,
content TEXT,
excerpt VARCHAR(500),
status VARCHAR(20) DEFAULT 'draft' CHECK (status IN ('draft', 'published', 'archived')),
author_id UUID NOT NULL REFERENCES users(id) ON DELETE CASCADE,
published_at TIMESTAMPTZ,
created_at TIMESTAMPTZ DEFAULT NOW(),
updated_at TIMESTAMPTZ DEFAULT NOW()
);
-- Many-to-many with junction table
CREATE TABLE tags (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
name VARCHAR(50) NOT NULL UNIQUE,
slug VARCHAR(50) NOT NULL UNIQUE
);
CREATE TABLE post_tags (
post_id UUID REFERENCES posts(id) ON DELETE CASCADE,
tag_id UUID REFERENCES tags(id) ON DELETE CASCADE,
PRIMARY KEY (post_id, tag_id)
);
-- Indexes
CREATE INDEX idx_posts_author ON posts(author_id);
CREATE INDEX idx_posts_status ON posts(status) WHERE status = 'published';
CREATE INDEX idx_posts_published_at ON posts(published_at DESC) WHERE status = 'published';
CREATE INDEX idx_users_email_lower ON users(LOWER(email));
-- Full-text search
ALTER TABLE posts ADD COLUMN search_vector tsvector;
CREATE INDEX idx_posts_search ON posts USING GIN(search_vector);
CREATE OR REPLACE FUNCTION update_search_vector()
RETURNS TRIGGER AS $$
BEGIN
NEW.search_vector :=
setweight(to_tsvector('english', COALESCE(NEW.title, '')), 'A') ||
setweight(to_tsvector('english', COALESCE(NEW.excerpt, '')), 'B') ||
setweight(to_tsvector('english', COALESCE(NEW.content, '')), 'C');
RETURN NEW;
END;
$$ LANGUAGE plpgsql;
CREATE TRIGGER posts_search_update
BEFORE INSERT OR UPDATE ON posts
FOR EACH ROW EXECUTE FUNCTION update_search_vector();
Advanced Queries
-- Common Table Expressions (CTE)
WITH post_stats AS (
SELECT
author_id,
COUNT(*) as post_count,
AVG(LENGTH(content)) as avg_length
FROM posts
WHERE status = 'published'
GROUP BY author_id
)
SELECT
u.name,
u.email,
ps.post_count,
ps.avg_length
FROM users u
JOIN post_stats ps ON u.id = ps.author_id
ORDER BY ps.post_count DESC
LIMIT 10;
-- Window functions
SELECT
p.title,
p.published_at,
u.name as author,
ROW_NUMBER() OVER (PARTITION BY p.author_id ORDER BY p.published_at DESC) as author_rank,
COUNT(*) OVER (PARTITION BY p.author_id) as author_total_posts,
p.published_at - LAG(p.published_at) OVER (PARTITION BY p.author_id ORDER BY p.published_at) as days_since_last
FROM posts p
JOIN users u ON p.author_id = u.id
WHERE p.status = 'published';
-- Recursive CTE (hierarchical data)
WITH RECURSIVE category_tree AS (
-- Base case
SELECT id, name, parent_id, 0 as depth, ARRAY[name] as path
FROM categories
WHERE parent_id IS NULL
UNION ALL
-- Recursive case
SELECT c.id, c.name, c.parent_id, ct.depth + 1, ct.path || c.name
FROM categories c
JOIN category_tree ct ON c.parent_id = ct.id
)
SELECT * FROM category_tree ORDER BY path;
-- JSONB queries
SELECT
id,
metadata->>'theme' as theme,
metadata->'preferences'->>'notifications' as notifications
FROM users
WHERE metadata @> '{"verified": true}'
AND metadata->'preferences' ? 'dark_mode';
-- Update JSONB
UPDATE users
SET metadata = jsonb_set(
metadata,
'{lastLogin}',
to_jsonb(NOW())
)
WHERE id = $1;
Performance Optimization
-- Analyze query plan
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)
SELECT p.*, u.name as author_name
FROM posts p
JOIN users u ON p.author_id = u.id
WHERE p.status = 'published'
ORDER BY p.published_at DESC
LIMIT 20;
-- Partial index for common queries
CREATE INDEX idx_active_users ON users(email) WHERE status = 'active';
-- Covering index (index-only scan)
CREATE INDEX idx_posts_list ON posts(status, published_at DESC)
INCLUDE (title, slug, excerpt, author_id);
-- BRIN index for time-series data
CREATE INDEX idx_events_created ON events USING BRIN(created_at);
-- Table partitioning
CREATE TABLE events (
id UUID DEFAULT gen_random_uuid(),
event_type VARCHAR(50),
payload JSONB,
created_at TIMESTAMPTZ DEFAULT NOW()
) PARTITION BY RANGE (created_at);
CREATE TABLE events_2024_q1 PARTITION OF events
FOR VALUES FROM ('2024-01-01') TO ('2024-04-01');
CREATE TABLE events_2024_q2 PARTITION OF events
FOR VALUES FROM ('2024-04-01') TO ('2024-07-01');
MongoDB
Schema Design
// User document with embedded data
const userSchema = {
_id: ObjectId,
email: String,
passwordHash: String,
profile: {
name: String,
avatar: String,
bio: String,
},
preferences: {
theme: String,
notifications: {
email: Boolean,
push: Boolean,
},
},
roles: [String],
createdAt: Date,
updatedAt: Date,
};
// Post with references
const postSchema = {
_id: ObjectId,
title: String,
slug: String,
content: String,
authorId: ObjectId, // Reference to users
tags: [String], // Denormalized for read performance
stats: {
views: Number,
likes: Number,
comments: Number,
},
status: String,
publishedAt: Date,
createdAt: Date,
};
// Indexes
db.users.createIndex({ email: 1 }, { unique: true });
db.posts.createIndex({ authorId: 1, publishedAt: -1 });
db.posts.createIndex({ tags: 1 });
db.posts.createIndex({ title: "text", content: "text" });
Aggregation Pipeline
// Complex aggregation
db.posts.aggregate([
// Match published posts
{ $match: { status: "published" } },
// Lookup author
{
$lookup: {
from: "users",
localField: "authorId",
foreignField: "_id",
as: "author",
},
},
{ $unwind: "$author" },
// Group by author
{
$group: {
_id: "$author._id",
authorName: { $first: "$author.profile.name" },
postCount: { $sum: 1 },
totalViews: { $sum: "$stats.views" },
avgLikes: { $avg: "$stats.likes" },
posts: {
$push: {
title: "$title",
publishedAt: "$publishedAt",
},
},
},
},
// Sort by post count
{ $sort: { postCount: -1 } },
// Limit to top 10
{ $limit: 10 },
// Project final shape
{
$project: {
_id: 0,
authorId: "$_id",
authorName: 1,
postCount: 1,
totalViews: 1,
avgLikes: { $round: ["$avgLikes", 2] },
recentPosts: { $slice: ["$posts", 5] },
},
},
]);
// Faceted search
db.products.aggregate([
{ $match: { $text: { $search: "laptop" } } },
{
$facet: {
results: [
{ $sort: { score: { $meta: "textScore" } } },
{ $skip: 0 },
{ $limit: 20 },
],
priceRanges: [
{
$bucket: {
groupBy: "$price",
boundaries: [0, 500, 1000, 2000, Infinity],
default: "Other",
output: { count: { $sum: 1 } },
},
},
],
brands: [{ $group: { _id: "$brand", count: { $sum: 1 } } }],
totalCount: [{ $count: "count" }],
},
},
]);
Redis
Data Structures
import Redis from 'ioredis';
const redis = new Redis(process.env.REDIS_URL);
// String operations
await redis.set('user:123:name', 'John');
await redis.setex('session:abc', 3600, JSON.stringify(sessionData)); // with TTL
const name = await redis.get('user:123:name');
// Hash operations
await redis.hset('user:123', {
name: 'John',
email: 'john@example.com',
role: 'admin',
});
const user = await redis.hgetall('user:123');
await redis.hincrby('user:123', 'loginCount', 1);
// List operations (queues)
await redis.lpush('queue:emails', JSON.stringify(emailJob));
const job = await redis.brpop('queue:emails', 0); // Blocking pop
// Set operations
await redis.sadd('user:123:followers', 'user:456', 'user:789');
await redis.sadd('user:456:followers', 'user:123', 'user:789');
const mutualFollowers = await redis.sinter(
'user:123:followers',
'user:456:followers'
);
// Sorted set (leaderboard)
await redis.zadd('leaderboard', 100, 'player1', 95, 'player2', 110, 'player3');
const topPlayers = await redis.zrevrange('leaderboard', 0, 9, 'WITHSCORES');
const rank = await redis.zrevrank('leaderboard', 'player1');
// HyperLogLog (unique counts)
await redis.pfadd('pageviews:2024-01-15', 'user:123', 'user:456');
const uniqueViews = await redis.pfcount('pageviews:2024-01-15');
Caching Patterns
// Cache-aside pattern
async function getCachedUser(userId: string): Promise<User> {
const cacheKey = `user:${userId}`;
// Try cache first
const cached = await redis.get(cacheKey);
if (cached) {
return JSON.parse(cached);
}
// Cache miss - fetch from DB
const user = await db.user.findUnique({ where: { id: userId } });
if (user) {
// Store in cache with TTL
await redis.setex(cacheKey, 3600, JSON.stringify(user));
}
return user;
}
// Cache invalidation
async function updateUser(userId: string, data: UpdateUserInput) {
const user = await db.user.update({
where: { id: userId },
data,
});
// Invalidate cache
await redis.del(`user:${userId}`);
return user;
}
// Rate limiting
async function checkRateLimit(userId: string, limit: number, window: number) {
const key = `ratelimit:${userId}`;
const current = await redis.incr(key);
if (current === 1) {
await redis.expire(key, window);
}
return current <= limit;
}
Prisma ORM
Schema Definition
// prisma/schema.prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model User {
id String @id @default(cuid())
email String @unique
password String
name String?
role Role @default(USER)
posts Post[]
comments Comment[]
profile Profile?
createdAt DateTime @default(now())
updatedAt DateTime @updatedAt
@@index([email])
}
model Profile {
id String @id @default(cuid())
bio String?
avatar String?
user User @relation(fields: [userId], references: [id], onDelete: Cascade)
userId String @unique
}
model Post {
id String @id @default(cuid())
title String
slug String @unique
content String?
published Boolean @default(false)
publishedAt DateTime?
author User @relation(fields: [authorId], references: [id])
authorId String
tags Tag[]
comments Comment[]
createdAt DateTime @default(now())
updatedAt DateTime @updatedAt
@@index([authorId, published])
@@index([publishedAt(sort: Desc)])
}
model Tag {
id String @id @default(cuid())
name String @unique
slug String @unique
posts Post[]
}
model Comment {
id String @id @default(cuid())
content String
author User @relation(fields: [authorId], references: [id])
authorId String
post Post @relation(fields: [postId], references: [id], onDelete: Cascade)
postId String
createdAt DateTime @default(now())
}
enum Role {
USER
ADMIN
MODERATOR
}
Query Patterns
import { PrismaClient, Prisma } from '@prisma/client';
const prisma = new PrismaClient();
// Basic queries
const users = await prisma.user.findMany({
where: {
role: 'USER',
email: { contains: '@example.com' },
},
select: {
id: true,
email: true,
name: true,
_count: { select: { posts: true } },
},
orderBy: { createdAt: 'desc' },
take: 10,
skip: 0,
});
// Complex query with relations
const postsWithAuthor = await prisma.post.findMany({
where: {
published: true,
OR: [
{ title: { contains: searchTerm, mode: 'insensitive' } },
{ content: { contains: searchTerm, mode: 'insensitive' } },
],
},
include: {
author: {
select: { id: true, name: true, profile: true },
},
tags: true,
_count: { select: { comments: true } },
},
orderBy: { publishedAt: 'desc' },
});
// Transactions
const [post, notification] = await prisma.$transaction([
prisma.post.create({
data: {
title: 'New Post',
slug: 'new-post',
authorId: userId,
},
}),
prisma.notification.create({
data: {
type: 'NEW_POST',
userId: userId,
},
}),
]);
// Interactive transaction
const transfer = await prisma.$transaction(async (tx) => {
const from = await tx.account.update({
where: { id: fromAccountId },
data: { balance: { decrement: amount } },
});
if (from.balance < 0) {
throw new Error('Insufficient funds');
}
const to = await tx.account.update({
where: { id: toAccountId },
data: { balance: { increment: amount } },
});
return { from, to };
});
// Raw queries when needed
const result = await prisma.$queryRaw<Post[]>`
SELECT p.*, ts_rank(search_vector, to_tsquery(${searchQuery})) as rank
FROM posts p
WHERE search_vector @@ to_tsquery(${searchQuery})
ORDER BY rank DESC
LIMIT 20
`;
Migrations
# Prisma migrations
npx prisma migrate dev --name add_user_status
npx prisma migrate deploy # Production
npx prisma db push # Prototype (no migration files)
# Generate client after schema changes
npx prisma generate
// Custom migration with data
// prisma/migrations/xxx_add_slug/migration.sql
-- Add slug column
ALTER TABLE posts ADD COLUMN slug VARCHAR(255);
-- Populate existing posts
UPDATE posts SET slug = LOWER(REPLACE(title, ' ', '-'));
-- Make non-nullable and unique
ALTER TABLE posts ALTER COLUMN slug SET NOT NULL;
ALTER TABLE posts ADD CONSTRAINT posts_slug_unique UNIQUE (slug);
Related Skills
- [[data-design]] - Data modeling patterns
- [[performance-optimization]] - Query optimization
- [[backend]] - Database integration
FAQ
What does the database skill do?
Database design, SQL, NoSQL, and data management patterns
How do I install database?
Run npx skills add https://github.com/miles990/claude-software-skills --skill database in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/database/ (personal) or .claude/skills/database/ (project).
Which AI agents can use database?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is database safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains database?
It is published by miles990 in miles990/claude-software-skills. It has 97 recorded installs.
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