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Tooluniverse Expression Data Retrieval

Checked
mims-harvard·vlatest·backend·Apache-2.0

Retrieves structured data from diverse online sources using a unified expression query language for complex analysis.

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 mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval -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

mims-harvard

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 mims-harvard/tooluniverse at f5c37eebeb.

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

Commit
f5c37eebeb
Manifest
skills/tooluniverse-expression-data-retrieval/SKILL.md
Scanned
9 files, 990 lines
Copies in repo
3 — all of them scanned
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 retrieve and process data using expression-based logic within the ToolUniverse ecosystem. It allows dynamic querying of datasets by translating natural language or structured expressions into executable retrieval operations.

When to use it

  • Fetching specific records from a database when you know the filtering criteria but not the exact query syntax.
  • Aggregating user metrics across multiple dimensions without writing custom backend code.
  • Validating data integrity by checking conditions against stored information in real-time.
  • Generating reports based on complex logical expressions defined at runtime.

Key capabilities

  • Dynamic expression parsing for flexible data queries.
  • Integration with ToolUniverse-compatible data sources.
  • Support for conditional logic within retrieval statements.
  • Real-time execution of computed results based on input variables.

Example prompts

  • "Retrieve all orders from the last 30 days where the total exceeds $500."
  • "Find users who have completed at least two courses in the Data Science track."
  • "Calculate the average response time for API calls made between 9 AM and 5 PM yesterday."

Tips & gotchas

Ensure your expression syntax aligns with the underlying data schema to avoid retrieval errors. Complex nested expressions may require pre-processing or simplification for optimal performance.