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opendata-api

Query OpenData datasets for rows, metadata, and analytical summaries.

121|7|Updated Mar 15, 2026
Search Tags:#api#aggregation#query#joins#datasets#opendata#graph intelligence
One-click install
npx skills add https://github.com/tryopendata/skills --skill opendata-api-tryopendata
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: opendata-api
Source: https://github.com/tryopendata/skills/tree/main/plugins/opendata/skills/opendata-api
Command: npx skills add https://github.com/tryopendata/skills --skill opendata-api-tryopendata

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

It removes the friction of exploring public datasets by letting you query, filter, sort, aggregate, and compare OpenData records through a single guided workflow.

Core Features & Use Cases

  • Dataset Exploration: Inspect columns, sample rows, and metadata before building a query so you can understand unfamiliar datasets quickly.
  • Analytical Queries: Run server-side aggregations, SQL, pagination, and exports to support research, reporting, and dashboard-ready outputs.
  • Cross-Dataset Workflows: Discover joinable datasets, preview compositions, and use graph intelligence to connect related sources for richer analysis.

Quick Start

Ask the assistant to inspect the dataset, find the right filters or joins, and return a concise analysis from the OpenData API.

Frequently Asked Questions about opendata-api

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I query OpenData datasets for rows and analytical summaries?▼

Querying OpenData datasets lets you retrieve rows, metadata, and analytical summaries through a guided workflow supporting filtering, sorting, aggregation, and SQL operations. The assistant inspects dataset schemas to return concise analysis.

How do I explore and understand unfamiliar public datasets before building a query?▼

Exploring unfamiliar public datasets involves inspecting columns, sample rows, and metadata to understand structure quickly. This schema-aware validation helps identify the right filters and joins before executing analytical queries.

Do I need authenticated API access to run SQL and joins on OpenData records?▼

Yes, authenticated API access is required to run SQL, joins, and aggregations on OpenData records. Authentication alongside schema-aware validation ensures you can securely query, filter, sort, and compare datasets.

Can I discover joinable datasets and use graph intelligence for cross-dataset workflows?▼

Yes, you can discover joinable datasets and use graph intelligence to connect related sources for cross-dataset workflows. This allows you to preview compositions and build richer analysis by linking related data sources.

What's the best way to export dashboard-ready outputs from OpenData aggregations?▼

The best way to export dashboard-ready outputs from OpenData aggregations is running server-side aggregations with pagination and exports. This workflow supports research, reporting, and dashboard-ready outputs directly from the API.

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