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This collection provides structured guidance for backend and infrastructure engineers working with PostgreSQL. It focuses on improving the precision of AI-generated database code through expert patterns for table design and migration strategies.
The repository includes specialized knowledge for implementing location-based applications using PostGIS, as well as identifying hypertable candidates for time-series data optimization.
WHO IT'S FOR
Backend / infrastructure engineers
optimizing PostgreSQL table design and migrations
AI / ML engineers
implementing semantic and hybrid search in Postgres
GIS developers
designing spatial tables with PostGIS
Database architects
migrating time-series data to TimescaleDB hypertables
Compatible AgentsThe repository documents support for these agents. The skills may also work with other agents that can load SKILL.md files, but they may need some setup or small changes.
Follow the documented setup, then try a first task.
I’m using
Claude Code plugin
Installs: Complete pg Claude Code plugin, including the skills in the repository's skills directory and the public pg-aiguide MCP server. · Claude Code
Before you start
Claude Code with plugin support
In a terminal, add the repository as a Claude Code plugin marketplace.
claude plugin marketplace add timescale/pg-aiguide
After adding the marketplace, install the pg plugin in a terminal.
Installs: Public pg-aiguide MCP server for PostgreSQL documentation access; no local skill-path mapping is established by the supplied evidence. · Codex
Before you start
An MCP-compatible Codex client
Run this command in a terminal to add the public pg-aiguide MCP server to Codex.
Installs: Public pg-aiguide MCP server for PostgreSQL documentation access; this is separate from the documented plugin installation and has no supplied local skill-path mapping. · Claude Code
Before you start
An MCP-compatible Claude Code client
Run this command in a terminal to connect Claude Code to the public MCP server.
claude mcp add --transport http pg-aiguide https://mcp.tigerdata.com/docs
Use the design-postgres-tables skill to draft, but not execute, a PostgreSQL schema for [describe the small application]. Start with only [list the two or three core entities] and the access patterns [list common lookups or joins]. Include appropriate data types, primary and foreign keys, semantic NOT NULL constraints, checks, and only the indexes justified by those access patterns. Target PostgreSQL [version]. Briefly explain each design choice.
An available database connection or PostgreSQL schema files
The authorized database and schema scope
Use the schema-exploration skill to answer this focused question about my PostgreSQL database: [question]. Work only within the authorized database and schemas [scope]. Begin with read-only catalog metadata, identify the most relevant schema-qualified objects and relationships, distinguish observations from inferences, and stop once you can answer. Do not inspect rows or data-derived statistics unless you first request my approval. If no database connection is available, work from the schema files I provide.
pgvector 0.8.0 or newer installed in the target environment
Content type to store
Embedding dimension N
Embedding model used for stored and query vectors
Desired result count k
Use the pgvector-semantic-search skill to draft, but not execute, the default SQL setup for semantic search over [content type]. My embedding dimension is [N], and both stored and query embeddings come from [embedding model]. Include the extension, a minimal table, a default HNSW cosine index, and a parameterized top-[k] nearest-neighbor query with an explicit halfvec([N]) cast. Briefly identify the placeholders I must replace.