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Datacommons Client

Listed
davila7·vlatest·other·MIT

Access and query public data repositories via Data Commons APIs to retrieve structured information on diverse topics.

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 davila7/claude-code-templates --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

davila7

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.

Nobody has reviewed this code. TrustedSkills indexes and links skills; it does not audit, run or scan them. A skill runs with whatever access you give your agent — read the source before you install it.

Automated safety checks

scanned

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Not scanned. none of the 457 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as davila7/claude-code-templates.
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About this skill

The datacommons-client skill enables AI agents to interact with the Data Commons knowledge graph, allowing them to retrieve structured data about real-world entities like cities, businesses, and environmental metrics. It facilitates complex queries across diverse domains including economics, health, and sustainability by leveraging a unified data infrastructure.

When to use it

  • Analyzing local economic indicators such as unemployment rates or median household income for specific geographic regions.
  • Investigating public health trends or air quality measurements linked to particular locations over time.
  • Gathering aggregated statistics on education outcomes, housing prices, or energy consumption for comparative analysis.
  • Accessing standardized data from multiple sources simultaneously without needing separate API keys for each dataset.

Key capabilities

  • Querying the Data Commons knowledge graph for entity-specific metrics.
  • Retrieving time-series data to track changes in variables over historical periods.
  • Filtering results by geographic boundaries, including countries, states, and cities.
  • Accessing a wide range of pre-processed datasets covering demographics, environment, and finance.

Example prompts

  • "What has been the trend in median home prices for Austin, Texas over the last five years?"
  • "Retrieve current air quality index data and population density for New York City."
  • "Compare the unemployment rates between rural and urban areas in California as of 2023."

Tips & gotchas

Ensure your AI agent specifies clear geographic identifiers (like city names or state codes) to avoid ambiguous results, as Data Commons relies heavily on location-based indexing. Be aware that data availability depends on the specific metrics published by contributing organizations within the Data Commons ecosystem; some niche indicators may have limited historical coverage.