Postgres
Design PostgreSQL schemas, indexes, extensions, and migrations without guessing data types or search patterns.
Install
npx skills add https://github.com/timescale/pg-aiguide --skill postgresWhat is this skill?
- Routes tasks to focused references: general tables, PostGIS, Timescale hypertables, pgvector, and hybrid search
- Covers data types, constraints, indexes, JSONB patterns, and partitioning strategies
- Supports pgvector embeddings, semantic search, RAG, full-text, hybrid, and BM25 ranking
- Guidance for PostGIS geometry vs geography, SRIDs, and spatial indexes
- TimescaleDB hypertable setup and migration evaluation for time-series workloads
Adoption & trust: 1 installs on skills.sh; 1.8k GitHub stars; 3/3 security scanners passed (skills.sh audits); trending (+100% hot-view momentum).
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Journey fit
Primary fit
Table design and indexing are canonical backend build work before the app can ship on a solid data layer. Schema, constraints, pgvector, PostGIS, and TimescaleDB choices live in backend data modeling—not frontend or launch tooling.
Common Questions / FAQ
Is Postgres safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.
SKILL.md
READMESKILL.md - Postgres
# PostgreSQL Expert Skills This skill provides comprehensive PostgreSQL expertise through specialized references. Load the appropriate reference based on the task. ## Available References ### Table Design - **[design-postgres-tables](references/design-postgres-tables.md)** — Data types, constraints, indexes, JSONB patterns, partitioning, and PostgreSQL best practices. **Use for any general table/schema design task.** - **[design-postgis-tables](references/design-postgis-tables.md)** — PostGIS spatial table design: geometry vs geography types, SRIDs, spatial indexing, and location-based query patterns. **Use when the task involves geographic or spatial data.** ### Search - **[pgvector-semantic-search](references/pgvector-semantic-search.md)** — Vector similarity search with pgvector: HNSW/IVFFlat indexes, halfvec storage, quantization, filtered search, and tuning. **Use for embeddings, RAG, or semantic search.** - **[postgres-hybrid-text-search](references/postgres-hybrid-text-search.md)** — Hybrid search combining BM25 keyword search with pgvector semantic search using RRF. **Use when combining keyword and meaning-based search.** ### TimescaleDB - **[setup-timescaledb-hypertables](references/setup-timescaledb-hypertables.md)** — Hypertable creation, compression, retention policies, continuous aggregates, and indexes. **Use when setting up TimescaleDB from scratch.** - **[find-hypertable-candidates](references/find-hypertable-candidates.md)** — SQL queries to analyze existing tables and score them for hypertable conversion. **Use when evaluating which tables to migrate.** - **[migrate-postgres-tables-to-hypertables](references/migrate-postgres-tables-to-hypertables.md)** — Step-by-step migration: partition column selection, in-place vs blue-green, validation. **Use when executing a migration.** ## How to Use 1. Identify which reference matches the user's task from the descriptions above. 2. Load the reference file to get detailed instructions and SQL patterns. 3. For tasks spanning multiple areas (e.g., "design a table with vector search"), load multiple references as needed.