postgres-patterns

PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.

16 stars

Best use case

postgres-patterns is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.

Teams using postgres-patterns should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/postgres-patterns/SKILL.md --create-dirs "https://raw.githubusercontent.com/Jamkris/everything-gemini-code/main/skills/postgres-patterns/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/postgres-patterns/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How postgres-patterns Compares

Feature / Agentpostgres-patternsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# PostgreSQL Patterns

Quick reference for PostgreSQL best practices. For detailed guidance, use the `database-reviewer` agent.

## When to Use

- Writing SQL queries or migrations
- Designing database schemas
- Troubleshooting slow queries
- Implementing Row Level Security
- Setting up connection pooling

## Quick Reference

### Index Cheat Sheet

| Query Pattern | Index Type | Example |
|--------------|------------|---------|
| `WHERE col = value` | B-tree (default) | `CREATE INDEX idx ON t (col)` |
| `WHERE col > value` | B-tree | `CREATE INDEX idx ON t (col)` |
| `WHERE a = x AND b > y` | Composite | `CREATE INDEX idx ON t (a, b)` |
| `WHERE jsonb @> '{}'` | GIN | `CREATE INDEX idx ON t USING gin (col)` |
| `WHERE tsv @@ query` | GIN | `CREATE INDEX idx ON t USING gin (col)` |
| Time-series ranges | BRIN | `CREATE INDEX idx ON t USING brin (col)` |

### Data Type Quick Reference

| Use Case | Correct Type | Avoid |
|----------|-------------|-------|
| IDs | `bigint` | `int`, random UUID |
| Strings | `text` | `varchar(255)` |
| Timestamps | `timestamptz` | `timestamp` |
| Money | `numeric(10,2)` | `float` |
| Flags | `boolean` | `varchar`, `int` |

### Common Patterns

**Composite Index Order:**
```sql
-- Equality columns first, then range columns
CREATE INDEX idx ON orders (status, created_at);
-- Works for: WHERE status = 'pending' AND created_at > '2024-01-01'
```

**Covering Index:**
```sql
CREATE INDEX idx ON users (email) INCLUDE (name, created_at);
-- Avoids table lookup for SELECT email, name, created_at
```

**Partial Index:**
```sql
CREATE INDEX idx ON users (email) WHERE deleted_at IS NULL;
-- Smaller index, only includes active users
```

**RLS Policy (Optimized):**
```sql
CREATE POLICY policy ON orders
  USING ((SELECT auth.uid()) = user_id);  -- Wrap in SELECT!
```

**UPSERT:**
```sql
INSERT INTO settings (user_id, key, value)
VALUES (123, 'theme', 'dark')
ON CONFLICT (user_id, key)
DO UPDATE SET value = EXCLUDED.value;
```

**Cursor Pagination:**
```sql
SELECT * FROM products WHERE id > $last_id ORDER BY id LIMIT 20;
-- O(1) vs OFFSET which is O(n)
```

**Queue Processing:**
```sql
UPDATE jobs SET status = 'processing'
WHERE id = (
  SELECT id FROM jobs WHERE status = 'pending'
  ORDER BY created_at LIMIT 1
  FOR UPDATE SKIP LOCKED
) RETURNING *;
```

### Anti-Pattern Detection

```sql
-- Find unindexed foreign keys
SELECT conrelid::regclass, a.attname
FROM pg_constraint c
JOIN pg_attribute a ON a.attrelid = c.conrelid AND a.attnum = ANY(c.conkey)
WHERE c.contype = 'f'
  AND NOT EXISTS (
    SELECT 1 FROM pg_index i
    WHERE i.indrelid = c.conrelid AND a.attnum = ANY(i.indkey)
  );

-- Find slow queries
SELECT query, mean_exec_time, calls
FROM pg_stat_statements
WHERE mean_exec_time > 100
ORDER BY mean_exec_time DESC;

-- Check table bloat
SELECT relname, n_dead_tup, last_vacuum
FROM pg_stat_user_tables
WHERE n_dead_tup > 1000
ORDER BY n_dead_tup DESC;
```

### Configuration Template

```sql
-- Connection limits (adjust for RAM)
ALTER SYSTEM SET max_connections = 100;
ALTER SYSTEM SET work_mem = '8MB';

-- Timeouts
ALTER SYSTEM SET idle_in_transaction_session_timeout = '30s';
ALTER SYSTEM SET statement_timeout = '30s';

-- Monitoring
CREATE EXTENSION IF NOT EXISTS pg_stat_statements;

-- Security defaults
REVOKE ALL ON SCHEMA public FROM public;

SELECT pg_reload_conf();
```

## Related

- Agent: `database-reviewer` - Full database review workflow
- Skill: `clickhouse-io` - ClickHouse analytics patterns
- Skill: `backend-patterns` - API and backend patterns

---

*Based on [Supabase Agent Skills](https://github.com/supabase/agent-skills) (MIT License)*

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