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Postgresql

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BagelHole
postgresql

Administer PostgreSQL databases. Configure replication, backups, and performance tuning. Use when managing PostgreSQL deployments.

Overview

PublisherBagelHole
RepositoryDevOps-Security-Agent-Skills
Skill namepostgresql
Stars
1.1K
Forks
161
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Postgresql 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.
    https://github.com/BagelHole/DevOps-Security-Agent-Skills/tree/main/infrastructure/databases/postgresql
  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/BagelHole/DevOps-Security-Agent-Skills.git /tmp/DevOps-Security-Agent-Skills
mkdir -p .claude/skills
cp -r /tmp/DevOps-Security-Agent-Skills/infrastructure/databases/postgresql .claude/skills/postgresql
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Postgresql 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 Postgresql 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 Postgresql 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.

PostgreSQL

Administer, optimize, and secure PostgreSQL databases in development and production environments.

When to Use

  • You need a reliable, ACID-compliant relational database.
  • Your application requires advanced features such as JSONB, full-text search, or CTEs.
  • You are setting up streaming replication or point-in-time recovery.
  • You need to tune an existing PostgreSQL deployment for better throughput.

Prerequisites

  • Linux server (Debian/Ubuntu or RHEL-based) or Docker.
  • Root or sudo access for package installation.
  • Familiarity with SQL fundamentals.

Installation and Setup

bash
# Debian / Ubuntu
sudo apt update
sudo apt install -y postgresql postgresql-contrib

# RHEL / Amazon Linux
sudo dnf install -y postgresql15-server postgresql15-contrib
sudo postgresql-setup --initdb
sudo systemctl enable --now postgresql

# Verify
psql --version
sudo systemctl status postgresql

Initial User and Database Setup

bash
# Switch to the postgres system user
sudo -u postgres psql
sql
-- Create an application user
CREATE USER myapp WITH PASSWORD 'strong_password_here';

-- Create the database owned by that user
CREATE DATABASE mydb OWNER myapp;

-- Grant connection privileges
GRANT ALL PRIVILEGES ON DATABASE mydb TO myapp;

-- Connect to the database and set default privileges
\c mydb
ALTER DEFAULT PRIVILEGES IN SCHEMA public
  GRANT SELECT, INSERT, UPDATE, DELETE ON TABLES TO myapp;

psql Commands Reference

\l              -- list databases
\dt             -- list tables in current database
\d+ tablename   -- describe table with storage info
\du             -- list roles
\x              -- toggle expanded output
\timing on      -- show query execution time
\i file.sql     -- execute SQL from file
\copy           -- fast client-side COPY

Configuration Tuning

Edit /etc/postgresql/15/main/postgresql.conf (path varies by OS and version).

ini
# Connection settings
listen_addresses = '*'
max_connections = 200

# Memory — adjust to ~25% of total RAM for shared_buffers
shared_buffers = 4GB
effective_cache_size = 12GB
work_mem = 16MB
maintenance_work_mem = 512MB

# WAL / write performance
wal_buffers = 64MB
checkpoint_completion_target = 0.9
min_wal_size = 1GB
max_wal_size = 4GB

# Planner
random_page_cost = 1.1          # lower for SSD
effective_io_concurrency = 200  # for SSD

# Logging
log_min_duration_statement = 250   # log queries slower than 250 ms
log_checkpoints = on
log_connections = on
log_disconnections = on
log_lock_waits = on
bash
# Reload configuration without restart
sudo -u postgres psql -c "SELECT pg_reload_conf();"

# Some settings (shared_buffers, max_connections) require a full restart
sudo systemctl restart postgresql

pg_hba.conf — Client Authentication

# /etc/postgresql/15/main/pg_hba.conf
# TYPE  DATABASE  USER      ADDRESS         METHOD
local   all       postgres                  peer
host    mydb      myapp     10.0.0.0/8      scram-sha-256
host    all       all       0.0.0.0/0       reject
bash
sudo systemctl reload postgresql

Backup and Restore

Logical Backups with pg_dump

bash
# Plain SQL backup
pg_dump -U myapp -h localhost mydb > /backups/mydb_$(date +%F).sql

# Custom compressed format (recommended)
pg_dump -U myapp -h localhost -Fc mydb > /backups/mydb_$(date +%F).dump

# Backup a single table
pg_dump -U myapp -h localhost -t orders -Fc mydb > /backups/orders.dump

# Restore from custom format
pg_restore -U myapp -h localhost -d mydb --clean --if-exists /backups/mydb_2025-01-15.dump

# Restore plain SQL
psql -U myapp -h localhost -d mydb < /backups/mydb_2025-01-15.sql

Physical Backups with pg_basebackup

bash
# Full base backup (used for PITR and replica seeding)
pg_basebackup -h localhost -U replicator -D /backups/base_$(date +%F) \
  --wal-method=stream --checkpoint=fast --progress --verbose

# Verify the backup
pg_verifybackup /backups/base_2025-01-15

Streaming Replication

Primary Server

sql
-- Create replication user
CREATE USER replicator WITH REPLICATION LOGIN PASSWORD 'repl_secret';
ini
# postgresql.conf on primary
wal_level = replica
max_wal_senders = 5
wal_keep_size = 1GB
# pg_hba.conf on primary
host replication replicator 10.0.0.0/8 scram-sha-256

Replica Server

bash
# Stop PostgreSQL on the replica
sudo systemctl stop postgresql

# Remove existing data directory
sudo rm -rf /var/lib/postgresql/15/main/*

# Base backup from primary
sudo -u postgres pg_basebackup \
  -h 10.0.0.1 -U replicator \
  -D /var/lib/postgresql/15/main \
  --wal-method=stream --checkpoint=fast --progress

# Create standby signal file
sudo -u postgres touch /var/lib/postgresql/15/main/standby.signal
ini
# postgresql.conf on replica
primary_conninfo = 'host=10.0.0.1 port=5432 user=replicator password=repl_secret'
hot_standby = on
bash
sudo systemctl start postgresql

Verify Replication

sql
-- On primary
SELECT client_addr, state, sent_lsn, replay_lsn
FROM pg_stat_replication;

-- On replica
SELECT pg_is_in_recovery();           -- should return true
SELECT pg_last_wal_receive_lsn();
SELECT pg_last_wal_replay_lsn();

Monitoring Queries

sql
-- Active connections by state
SELECT state, COUNT(*)
FROM pg_stat_activity
GROUP BY state;

-- Long-running queries (> 30 seconds)
SELECT pid, now() - query_start AS duration, query
FROM pg_stat_activity
WHERE state = 'active'
  AND now() - query_start > interval '30 seconds'
ORDER BY duration DESC;

-- Table bloat and dead tuples
SELECT relname,
       n_live_tup,
       n_dead_tup,
       ROUND(n_dead_tup::numeric / GREATEST(n_live_tup, 1) * 100, 2) AS dead_pct
FROM pg_stat_user_tables
ORDER BY n_dead_tup DESC
LIMIT 10;

-- Index usage statistics
SELECT relname, indexrelname, idx_scan, idx_tup_read, idx_tup_fetch
FROM pg_stat_user_indexes
ORDER BY idx_scan ASC
LIMIT 10;

-- Cache hit ratio (should be > 99%)
SELECT ROUND(
  100.0 * sum(blks_hit) / NULLIF(sum(blks_hit) + sum(blks_read), 0), 2
) AS cache_hit_pct
FROM pg_stat_database;

-- Database size
SELECT pg_database.datname,
       pg_size_pretty(pg_database_size(pg_database.datname)) AS size
FROM pg_database
ORDER BY pg_database_size(pg_database.datname) DESC;

Docker Compose Setup

yaml
# docker-compose.yml
version: "3.9"

services:
  postgres:
    image: postgres:16-alpine
    restart: unless-stopped
    ports:
      - "5432:5432"
    environment:
      POSTGRES_USER: myapp
      POSTGRES_PASSWORD: secret
      POSTGRES_DB: mydb
    volumes:
      - pg_data:/var/lib/postgresql/data
      - ./init.sql:/docker-entrypoint-initdb.d/init.sql
    command: >
      postgres
        -c shared_buffers=256MB
        -c work_mem=8MB
        -c maintenance_work_mem=128MB
        -c effective_cache_size=768MB
        -c log_min_duration_statement=250
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U myapp -d mydb"]
      interval: 10s
      timeout: 5s
      retries: 5

  pgbouncer:
    image: edoburu/pgbouncer:latest
    restart: unless-stopped
    ports:
      - "6432:6432"
    environment:
      DATABASE_URL: postgres://myapp:secret@postgres:5432/mydb
      POOL_MODE: transaction
      MAX_CLIENT_CONN: 500
      DEFAULT_POOL_SIZE: 40
    depends_on:
      postgres:
        condition: service_healthy

volumes:
  pg_data:
bash
docker compose up -d
psql -h 127.0.0.1 -p 6432 -U myapp mydb

Maintenance Tasks

bash
# Manual VACUUM and ANALYZE
sudo -u postgres psql -d mydb -c "VACUUM ANALYZE;"

# Reindex a bloated index
sudo -u postgres psql -d mydb -c "REINDEX INDEX CONCURRENTLY idx_orders_user_id;"

# Check for unused indexes
sudo -u postgres psql -d mydb -c "
  SELECT indexrelname, idx_scan
  FROM pg_stat_user_indexes
  WHERE idx_scan = 0
  ORDER BY pg_relation_size(indexrelid) DESC;"

Troubleshooting

SymptomLikely CauseFix
FATAL: too many connectionsConnection limit reachedIncrease max_connections or add PgBouncer
Slow SELECT on large tableMissing index or stale statisticsRun EXPLAIN ANALYZE; add index; run ANALYZE
High CPU from autovacuumLarge number of dead tuplesTune autovacuum_vacuum_cost_delay; run manual VACUUM
Replication lag increasingReplica under-provisioned or network bottleneckCheck pg_stat_replication; increase wal_keep_size
could not access file "base/..."Disk full or corrupt data directoryFree disk space; restore from pg_basebackup
FATAL: password authentication failedWrong credentials or pg_hba.conf mismatchVerify pg_hba.conf entries and reload

Related Skills

  • mysql - Alternative relational database
  • database-backups - Automated backup strategies
  • redis - Caching layer to reduce database load
  • planetscale - Managed MySQL-compatible alternative

Frequently asked questions

What does the Postgresql AI skill do?

Administer PostgreSQL databases. Configure replication, backups, and performance tuning. Use when managing PostgreSQL deployments.

Why use Postgresql on TypingMind?

Because you install it once and use it with any model. Postgresql 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 Postgresql in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/BagelHole/DevOps-Security-Agent-Skills/tree/main/infrastructure/databases/postgresql. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Postgresql?

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 Postgresql?

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

Is the Postgresql AI skill free?

Yes. It is published on GitHub by BagelHole 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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