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Postgresql optimization

Skill kimtth/agent-skill-100-lines-or-less/skills/postgresql-optimization

🧿 Minimal but effective AI agent skill definitions in 100 lines or less.

Install
npx -y skills add kimtth/agent-skill-100-lines-or-less --skill postgresql-optimization

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What its author says it does

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Use when: improve PostgreSQL schema, queries, indexes, JSONB, arrays, full-text search, or performance with Postgres-specific features.

SKILL.md

1.4 KB, 278 tokens by cl100k_base, as published. Nobody here has run it

Goal: use PostgreSQL features deliberately and measure performance with evidence.

Use for:

  • slow queries, missing indexes, schema design, and data modeling
  • JSONB, arrays, custom types, ranges, full-text search, and extensions
  • window functions, CTEs, materialized views, and analytics queries
  • migration review and Postgres-specific refactors

Workflow:

  1. Identify table sizes, query shape, filters, joins, and expected latency.
  2. Run or request EXPLAIN (ANALYZE, BUFFERS) for performance work.
  3. Check existing indexes, constraints, and data distribution.
  4. Pick the smallest Postgres feature that solves the real bottleneck.
  5. Propose migration SQL plus rollback when schema changes are needed.
  6. Verify with query plans, tests, and representative data.

Patterns:

  • JSONB: GIN indexes, containment, path extraction, generated columns
  • arrays: ANY, overlap, containment, unnest only when needed
  • text search: tsvector, GIN, ranking, language config
  • analytics: window functions over app-side loops
  • indexing: composite order, partial indexes, covering indexes

Rules:

  • do not add indexes without a query they serve
  • do not optimize synthetic tiny data as if it were production
  • keep migrations reversible when possible
  • measure before and after

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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