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Datacommons Client

Checked
ovachiever·vlatest·other

Connects to Ovacommons data repositories, retrieves structured information, and formats it for analysis within Ovaciever 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 ovachiever/droid-tings --skill datacommons-client -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

ovachiever

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 ovachiever/droid-tings at 7acd12a754.

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

Commit
7acd12a754
Manifest
skills/datacommons-client/SKILL.md
Scanned
5 files, 1,236 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

The ovachiever-datacommons-client skill provides access to the Data Commons API. It allows AI agents to query and retrieve structured data about various topics, including demographics, education, health, and government. This enables tasks like gathering statistical information, building knowledge graphs, or performing comparative analyses across different regions or time periods.

When to use it

  • Researching demographic trends: An agent could be used to find population statistics for specific cities or states over a given period.
  • Comparing educational outcomes: Retrieve data on graduation rates and test scores across different school districts.
  • Analyzing healthcare disparities: Gather information about disease prevalence and access to care in various regions.
  • Building a knowledge base: Populate a database with facts and figures from the Data Commons for use in other applications.

Key capabilities

  • Accesses the Data Commons API
  • Retrieves structured data
  • Supports queries across diverse topics (demographics, education, health, government)
  • Provides statistical information

Example prompts

  • "Find the median household income for California in 2020."
  • "What is the graduation rate for public high schools in Texas?"
  • "Compare the population density of New York City and Los Angeles."

Tips & gotchas

The Data Commons API can be complex, so understanding its schema and query language will improve results. Be mindful of potential data limitations or inconsistencies within the Data Commons dataset itself.