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Postgres Semantic Search

Checked
laguagu·vlatest·database·MIT

Helps with PostgreSQL, search as part of working with databases and data persistence workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add laguagu/claude-code-nextjs-skills --skill postgres-semantic-search -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

laguagu

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned laguagu/claude-code-nextjs-skills at b89c0f85d1.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
b89c0f85d1
Manifest
skills/postgres-semantic-search/SKILL.md
Scanned
13 files, 923 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill enables AI agents to perform semantic search queries directly against PostgreSQL databases, allowing for natural language retrieval of records rather than relying on rigid keyword matching. It bridges the gap between unstructured user questions and structured data storage by leveraging vector similarity within the database engine.

When to use it

  • Retrieving customer support tickets based on vague descriptions like "issues with login" instead of specific error codes.
  • Finding relevant product documentation or internal knowledge base entries using conversational queries.
  • Analyzing unstructured text fields in a dataset to identify trends or specific entities without manual filtering.
  • Building chatbots that answer questions by querying the full semantic meaning of user inputs against stored data.

Key capabilities

  • Executes semantic search operations natively within PostgreSQL environments.
  • Translates natural language queries into vector similarity searches.
  • Returns relevant database records based on contextual understanding rather than exact string matches.

Example prompts

  • "Find all sales transactions related to 'summer clothing' from the last quarter."
  • "Search for any support tickets mentioning problems with the mobile app login process."
  • "Retrieve customer feedback entries that express dissatisfaction with shipping times."

Tips & gotchas

Ensure your PostgreSQL instance has vector extension capabilities (such as pgvector) installed and configured before deploying this skill. Performance may vary depending on the size of the dataset and the quality of the embedding models used to index the data.