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postgres-pro

Use when optimizing PostgreSQL queries, configuring replication, or implementing advanced database features.

Skill by https://github.com/Jeffallan

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About

Use when optimizing PostgreSQL queries, configuring replication, or implementing advanced database features. Invoke for EXPLAIN analysis, JSONB operations, extension usage, VACUUM tuning, performance monitoring.

Use cases: backend

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/postgres-pro

What's inside

Skill name
postgres-pro
Description
Use when optimizing PostgreSQL queries, configuring replication, or implementing advanced database features. Invoke for EXPLAIN analysis, JSONB operations, extension usage, VACUUM tuning, performance monitoring.
License
MIT
Metadata
role: specialist · scope: implementation · author: https://github.com/Jeffallan · domain: infrastructure · company: https://synergetic.solutions · version: 1.1.0 · triggers: PostgreSQL, Postgres, EXPLAIN ANALYZE, pg_stat, JSONB, streaming replication, logical replication, VACUUM, PostGIS, pgvector · output-format: code · related-skills: database-optimizer, devops-engineer, sre-engineer
Instructions
143 lines in SKILL.md · view on GitHub

Files (6)

  • SKILL.md
  • extensions.md · references/
  • jsonb.md · references/
  • maintenance.md · references/
  • performance.md · references/
  • replication.md · references/

SKILL.md (first lines)

# PostgreSQL Pro

Senior PostgreSQL expert with deep expertise in database administration, performance optimization, and advanced PostgreSQL features.

## When to Use This Skill

- Analyzing and optimizing slow queries with EXPLAIN
- Implementing JSONB storage and indexing strategies
- Setting up streaming or logical replication
- Configuring and using PostgreSQL extensions
- Tuning VACUUM, ANALYZE, and autovacuum
- Monitoring database health with pg_stat views
- Designing indexes for optimal performance

## Core Workflow

1. **Analyze performance** — Run `EXPLAIN (ANALYZE, BUFFERS)` to identify bottlenecks
2. **Design indexes** — Choose B-tree, GIN, GiST, or BRIN based on workload; verify with `EXPLAIN` before deploying
3. **Optimize queries** — Rewrite inefficient queries, run `ANALYZE` to refresh statistics
4. **Setup replication** — Streaming or logical based on requirements; monitor lag continuously
5. **Monitor and maintain** — Track VACUUM, bloat, and autovacuum via `pg_stat` views; verify improvements after each change

### End-to-End Example: Slow Query → Fix → Verification

```sql
-- Step 1: Identify slow queries
SELECT query, mean_exec_time, calls
FROM pg_stat_statements
ORDER BY mean_exec_time DESC
LIMIT 10;

-- Step 2: Analyze a specific slow query
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)
SELECT * FROM orders WHERE customer_id = 42 AND status = 'pending';
-- Look for: Seq Scan (bad on large tables), high Buffers hit, nested loops on large sets

-- Step 3: Create a targeted index
CREATE INDEX CONCURRENTLY idx_orders_customer_status
  ON orders (customer_id, status)
  WHERE status = 'pending';  -- partial index reduces size

-- Step 4: Verify the index is used
EXPLAIN (ANALYZE, BUFFERS)
SELECT * FROM orders WHERE customer_id = 42 AND status = 'pending';
-- Confirm: Index Scan on idx_orders_customer_status, lower actual time

-- Step 5: Update statistics if needed after bulk changes
ANALYZE orders;
```

## Reference Guide

Load detailed guidance based on context:

| Topic | Reference | Load When |
|-------|-----------|-----------|
| Performance | `references/performance.md` | EXPLAIN ANALYZE, indexes, statistics, query tuning |
| JSONB | `references/jsonb.md` | JSONB operators, indexing, GIN indexes, containment |
| Extensions | `references/extensions.md` | PostGIS, pg_trgm, pgvector, uuid-ossp, pg_stat_statements |
| Replication | `references/replication.md` | Streaming replication, logical replication, failover |
| Maintenance | `references/maintenance.md` | VACUUM, ANALYZE, pg_stat views, monitoring, bloat |

## Common Patterns

### JSONB — GIN Index and Query

```sql
-- Create GIN index for containment queries
CREATE INDEX idx_events_payload ON events USING GIN (payload);

-- Efficient JSONB containment query (uses GIN index)
SELECT * FROM events WHERE payload @> '{"type": "login", "success": true}';

-- Extract nested value
SELECT payload->>'user_id', payload->'meta'->>'ip'
FROM events
WHERE payload @> '{"type": "login"}';
```

### VACUUM and Bloat Monitoring

```sql
-- Check tables with high dead tuple counts
SELECT relname, n_dead_tup, n_live_tup,
       round(n_dead_tup::numeric / NULLIF(n_live_tup + n_dead_tup, 0) * 100, 2) AS dead_pct,
       last_autovacuum
FROM pg_stat_user_tables
ORDER BY n_dead_tup DESC
LIMIT 20;

-- Manually vacuum a high-churn table and verify
VACUUM (ANALYZE, VERBOSE) orders;
```

### Replication Lag Monitoring

```sql
-- On primary: check standby lag
SELECT client_addr, state, sent_lsn, write_lsn, flush_lsn, replay_lsn,
       (sent_lsn - replay_lsn) AS replication_lag_bytes
FROM pg_stat_replication;
```

## Constraints

### MUST DO
- Use `EXPLAIN (ANALYZE, BUFFERS)` for query optimization
- Verify indexes are actually used with `EXPLAIN` before and after creation
- Use `CREATE INDEX CONCURRENTLY` to avoid table locks in production
- Run `ANALYZE` after bulk data changes to refresh statistics
- Monitor autovacuum; tune `autovacuum_vacuum_scale_factor` for high-churn tables
- Use connection pooling (pgBouncer, pgPool)
- Monitor replication lag via `pg_stat_replication`
- Use prepared statements to prevent SQL injection
- Use `uuid` type for UUIDs, not `text`

### MUST NOT DO
- Disable autovacuum globally
- Create indexes without first analyzing query patterns

From Jeffallan/claude-skills, MIT.

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Stars
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Forks
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Open issues
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Last commit (this folder)
Oct 15, 2026 (13 days ago)
Last release
Oct 16, 2026 (12 days ago)

From GitHub (fetched Oct 24, 2026).

Details

Version
1.1.0
License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

postgres-pro skill. Agent Mart. https://agentmart.dev/skills/jeffallan-postgres-pro (last updated 2026-10-24)