Agent Skills for EDB Postgres AI

Agent Skills give AI coding agents — for example, Claude Code — built-in, validated knowledge of how AIDB, PGAA, and PGFS actually work. Each skill is maintained by EDB alongside the product it covers: its SQL functions, configuration, and concepts, kept in sync as the product changes, in a form the agent reads directly rather than one it has to piece together on its own.

Why install EDB's Agent Skills

  • Accurate to the product you're running: each skill reflects AIDB, PGAA, or PGFS's actual SQL functions, configuration, and concepts, maintained by EDB alongside the product itself.

  • Specific, not generic: skill content is scoped to EDB Postgres AI products, so the agent works from the product's real surface instead of general Postgres knowledge that may not apply.

  • Stays current: as AIDB, PGAA, or PGFS change, the skill changes with them, so it doesn't go stale the way a scraped blog post or an older training snapshot would.

What Agent Skills cover

Skills are available for:

ProductWhat it does
AIDBBrings native AI capabilities — embeddings, RAG pipelines, and in-database agents — into Postgres.
Postgres Analytics Accelerator (PGAA)Analytics in Postgres over Apache Iceberg, Delta Lake, and Parquet tables.
Postgres File System (PGFS)Companion extension for AIDB and PGAA that provides access to external storage.

Getting the skills

The skills are maintained in the edb-agent-skills GitHub repository.

Installing a skill

  1. Decide which product's skill you want to install, or install all of them by not selecting a specific directory.

  2. Ask your AI agent to install the skill, for example: Install the skills from https://github.com/EnterpriseDB/edb-agent-skills.

  3. Follow any instructions the agent gives you to complete the installation.

Once installed, a skill runs as part of your agent's local session — there's no separate service to deploy or account to configure. The agent loads the skill's content itself when it decides the skill is relevant to your request.

Using the skills

Once a skill is installed, ask your agent to help with tasks like:

  • Discovery and solution design — for example, How can I build a back end for a RAG application with EDB AIDB?

  • SQL generation, or asking the agent to run SQL directly

  • Installing and configuring the product — for example, "Register a new LLM for use with AIDB; I want to use OpenAI GPT-5"

  • Tuning, experimentation, and optimization — for example, "I want to try different chunking strategies for my RAG vector embeddings"

  • Debugging — for example, "My RAG knowledge base 'products' returns poor results; what could the reason be?"

  • Coding — for example, "Integrate the local Python demo app with PG and the AIDB extension so I can add semantic search to the UI"

Example

This partial example, from a Claude Code session with the AIDB skill installed, shows the agent answering a discovery question:

❯ what can I do with the AIDB extension?

⏺ Skill(aidb)
  ⎿ Successfully loaded skill

⏺ Everything AIDB does is a SQL call in the aidb schema — no CLI, no SDK. Here's the capability map, checked against your instance on port 28818.

  The six building blocks

  ┌─────────────────────┬──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
  │        Block        │                                                                                   What you get                                                                                   │
  ├─────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
  │ Standalone          │ One-off AI inside a query: chunk_text, parse_html, parse_pdf, pdf_to_image, perform_ocr, summarize_text, encode_text, generate_text, rerank_text                                 │
  │ functions           │                                                                                                                                                                                  │
  ├─────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
  │ Models              │ Register once by name, reuse everywhere. Local (in-process) or remote (OpenAI, Anthropic, Gemini, NIM, OpenRouter)                                                               │
...

Supported AI platforms

  • Claude Code

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