Agent skill · data analytics · aiskillstore
datacommons-client
Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.
Why this skill is useful
Provides specific API commands and patterns for querying demographic and statistical data that the AI wouldn't reliably generate on its own.
What it needs
Requires datacommons-client installed locally. About 3k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Data Commons Client Overview Provides comprehensive access to the Data Commons Python API v2 for querying statistical observations, exploring the knowledge graph, and resolving entity identifiers. Data Commons aggregates data from census bureaus, health organizations, environmental agencies, and other authoritative sources into a unified knowledge graph. Installation Install the Data Commons Python client with Pandas support: For basic usage without Pandas: Core Capabilities The Data Commons API consists of three main endpoints, each detailed in dedicated reference files: 1. Observation Endpoint - Statistical Data Queries Query time-series statistical data for entities. See references/observation.md for comprehensive documentation. Primary use cases: Retrieve population, economic, health, or environmental statistics Access historical time-series data for trend analysis Query data for hierarchies (all counties in a state, all countries in a region) Compare statistics across multiple entities Filter by data source for consistency Common patterns: 2. Node Endpoint - Knowledge Graph Exploration Explore entity relationships and properties within the knowledge graph. See references/node.md for comprehensive documentation. Primary use cases: Discover available properties for entities Navigate geographic hierarchies (parent/child relationships) Retrieve entity names and metadata Explore connections between entities List all entity types in the graph Common patterns: 3. Resolve Endpoint - Entity Identification Translate entity names, coordinates, or external IDs into Data Commons IDs (DCIDs). See references/resolve.md for comprehensive documentation. Primary use cases: Convert place names to DCIDs for queries Resolve coordinates to places Map Wikidata IDs to Data Commons entities Handle ambiguous entity names Common patterns: Typical Workflow Most Data Commons queries follow this pattern: 1. Resolve entities (if starting with names): 2. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/datacommons-client