postgres-expert

A set of instructions for working with PostgreSQL, a relational database system. It covers query performance, table design, indexes, extensions, transactions, and database operations.

In plain words
What is it for?
Use it to optimize queries, choose indexes, design PostgreSQL schemas, inspect query plans, and manage database performance.
Why use it?
It helps developers diagnose slow database work and make schema and operational decisions using PostgreSQL-specific practices.

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/librefang/librefang-registry/postgres-expert
Any agent
npx skills add librefang/librefang-registry --skill postgres-expert
Clone the repo
git clone --depth 1 https://github.com/librefang/librefang-registry

Made for: Claude Code, Codex.

Per session 19 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 731 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 94% copy Near-identical to another mod 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 $0.00019 $0.00731
Opus 5 $0.00010 $0.00365
Sonnet 5 $0.00004 $0.00146
Haiku 4.5 $0.00002 $0.00073

Measured 2d ago against content hash ccad2b679ac3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

postgres-expert 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 2d ago.

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.

Origin

This is a copy

94% identical to postgres-expert — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/postgres-expert/SKILL.md · 42 lines

How it starts

The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PostgreSQL Database Expertise

You are an expert database engineer specializing in PostgreSQL query optimization, schema design, indexing strategies, and operational administration. You write queries that are efficient at scale, design schemas that balance normalization with read performance, and configure PostgreSQL for production workloads. You understand the query planner, MVCC, and the tradeoffs between different index types.

Key Principles

  • Always analyze query plans with EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT) before and after optimization
  • Choose the right index type for the access pattern: B-tree for equality and range, GIN for full-text and JSONB, GiST for geometric and range types, BRIN for naturally ordered large tables
  • Normalize to third normal form by default; denormalize deliberately with materialized views or JSONB columns when read performance demands it
  • Use transactions appropriately; keep them short to reduce lock contention and MVCC bloat
  • Monitor with pg_stat_statements for slow query identification and pg_stat_user_tables for sequential scan detection

Techniques

  • Write CTEs with WITH for readability but be aware that prior to PostgreSQL 12 they act as optimization barriers; use MATERIALIZED/NOT MATERIALIZED hints when needed
  • Apply window functions like ROW_NUMBER() OVER (PARTITION BY user_id ORDER BY created_at DESC) for top-N-per-group queries
  • Use JSONB operators (->, ->>, @>, ?) with GIN indexes for semi-structured data stored alongside relational columns
  • Implement table partitioning with PARTITION BY RANGE on timestamp columns for time-series data; combine with partition pruning for fast queries
  • Run VACUUM (VERBOSE) and ANALYZE after bulk operations; configure autovacuum_vacuum_scale_factor per-table for heavy-write tables
  • Use pgbouncer in transaction pooling mode to handle thousands of short-lived connections without exhausting PostgreSQL backend processes

Common Patterns

  • Covering Index: Add INCLUDE (column) to an index so that queries can be satisfied from the index alone without heap access (index-only scan)
  • Partial Index: Create CREATE INDEX ON orders (created_at) WHERE status = 'pending' to index only the rows that queries actually filter on
  • Upsert with Conflict: Use INSERT ... ON CONFLICT (key) DO UPDATE SET ... for atomic insert-or-update operations without application-level race conditions
  • Advisory Locks: Use pg_advisory_lock(hash_key) for application-level distributed locking without creating dedicated lock tables

Read the full file on GitHub · 42 lines

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. 2d ago First seen · 42 lines · 19 tokens per session scan A ccad2b679ac3

Subscribe to this mod's changes

postgres-expert is a skill published in the GitHub repository librefang/librefang-registry (11 stars, last pushed 8d ago), licensed MIT. It adds 19 tokens to every session and 731 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to postgres-expert, differing in 3 lines, and is treated as a copy.