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Typeql

Checked
caliluke·vlatest·database·MIT

Typeql generates SQL queries from natural language descriptions, streamlining database interaction and boosting developer efficiency.

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 caliluke/skills --skill typeql -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

caliluke

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 caliluke/skills at 243c6fb1df.

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

Commit
243c6fb1df
Manifest
skills/typedb/SKILL.md
Scanned
1 file, 1,137 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, typeql, allows AI agents to interact with and query data using the TypeQL language. It enables structured data retrieval and manipulation based on defined schemas and relationships. The agent can execute complex queries against datasets described by TypeQL models, returning results in a predictable format.

When to use it

  • Data Extraction: Extract specific information from documents or databases where a TypeQL schema is already defined.
  • Knowledge Graph Queries: Retrieve connections and entities within a knowledge graph represented using TypeQL.
  • Structured Data Reporting: Generate reports based on data conforming to a TypeQL model, allowing for consistent formatting and analysis.
  • Data Validation: Verify that new or existing data adheres to the constraints defined in a TypeQL schema.

Key capabilities

  • TypeQL query execution
  • Schema definition and management (implied)
  • Structured result retrieval

Example prompts

  • "Execute this TypeQL query: ...query string..."
  • "Find all entities of type 'Product' with a price greater than 100."
  • "Run the following TypeQL statement and return the results in JSON format: ...TypeQL statement..."

Tips & gotchas

Requires familiarity with the TypeQL language and access to a dataset defined by a corresponding TypeQL schema. The agent's performance depends on the complexity of the query and the size of the underlying data source.