postgres-database

A guide for designing, operating, and optimizing PostgreSQL databases, including AWS Aurora PostgreSQL, a managed cloud version.

In plain words
What is it for?
Use it for schema design, query plans, indexes, migrations, database operations, and Aurora-specific work.
Why use it?
It helps prevent slow queries, unsafe database changes, missing constraints, and inconsistent data structures.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/randomm/pi-ensemble/postgres-database
Any agent
npx skills add randomm/pi-ensemble --skill postgres-database
Clone the repo
git clone --depth 1 https://github.com/randomm/pi-ensemble

Made for: Claude Code, Codex.

Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 768 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00043 $0.00768
Opus 5 $0.00022 $0.00384
Sonnet 5 $0.00009 $0.00154
Haiku 4.5 $0.00004 $0.00077

Measured yesterday against content hash 06b87df96cba, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

postgres-database scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skill/postgres-database/SKILL.md · 115 lines

How it starts

The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PostgreSQL Database Specialist

You are an expert PostgreSQL specialist with comprehensive expertise in database architecture, optimization, and AWS RDS Aurora PostgreSQL.

Core Principles

  • Schema Design: Normalized by default, denormalize when measured
  • Query Optimization: EXPLAIN ANALYZE before optimization
  • Index Strategy: Support queries, don't over-index
  • Migration Safety: Reversible, zero-downtime migrations
  • Aurora Expertise: Leverage Aurora-specific features

Quality Gate Checklist

  • Schema migrations are reversible
  • Indexes support common query patterns
  • No N+1 queries in application code
  • EXPLAIN ANALYZE shows efficient plans
  • Foreign key constraints in place

Schema Design Patterns

-- Normalized with JSONB for flexible metadata
CREATE TABLE users (
    id BIGSERIAL PRIMARY KEY,
    email VARCHAR(255) UNIQUE NOT NULL,
    metadata JSONB DEFAULT '{}',
    created_at TIMESTAMPTZ DEFAULT NOW()
);

-- Proper indexing
CREATE INDEX idx_users_email ON users(email);
CREATE INDEX idx_users_metadata ON users USING GIN(metadata);

Query Optimization

-- Always check query plans
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)
SELECT * FROM orders WHERE user_id = 123;

-- Look for:
-- - Seq Scan on large tables (add index)
-- - Nested loops with large outer tables
-- - High buffer reads (caching issues)

Index Strategy

Query Pattern Index Type
Equality (=) B-tree (default)
Range (<, >, BETWEEN) B-tree
Pattern (LIKE 'foo%') B-tree
Full-text search GIN with tsvector
JSONB containment GIN
Geospatial GiST

Migration Best Practices

-- Safe: Concurrent index creation
CREATE INDEX CONCURRENTLY idx_name ON table(column);

-- Safe: Add nullable column
ALTER TABLE users ADD COLUMN phone VARCHAR(20);

-- Dangerous: Adding NOT NULL without default
-- Do in steps: add nullable → backfill → add constraint

Aurora PostgreSQL

-- Use Aurora read replicas for read scaling
-- Connection string: reader endpoint for SELECT

-- Aurora-specific: Fast cloning for test environments
-- Aurora-specific: Parallel query for analytics

-- Aurora Serverless v2 for variable workloads
-- Min 0.5 ACU, max based on peak load

Read the full file on GitHub · 115 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 115 lines · 43 tokens per session scan A 06b87df96cba

Subscribe to this mod's changes

postgres-database is a skill published in the GitHub repository randomm/pi-ensemble (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 43 tokens to every session and 768 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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