bigquery-overture-skill

Convert natural language Overture questions into budget-checked BigQuery SQL queries.

3|1|Updated Feb 28, 2026
One-click install
npx skills add https://github.com/dekart-xyz/bigquery-overture-skill --skill bigquery-overture-skill
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: bigquery-overture-skill
Source: https://github.com/dekart-xyz/bigquery-overture-skill/tree/main
Command: npx skills add https://github.com/dekart-xyz/bigquery-overture-skill --skill bigquery-overture-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Converts natural language Overture questions into SQL queries that are checked for budget compliance, preventing over-budget execution and ensuring cost control.

Core Features & Use Cases

  • Transforms plain-language geographic or data queries into BigQuery Overture Maps SQL.
  • Implements dry-run estimates to enforce cost limits before actual query execution.
  • Supports spatial aggregation with H3 indexing and easy visualization handoff.
  • Suitable for data analysts and geospatial professionals working within strict cost constraints or needing safe query iteration.

Quick Start

Ask it to generate a spatial aggregation query with budget checks, then review the SQL and consider executing or refining based on the dry-run estimate.

Frequently Asked Questions about bigquery-overture-skill

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

FAQPage Schema
How do I estimate BigQuery query costs before running Overture Maps SQL?

Estimate BigQuery query costs by using dry-run checks on your Overture Maps SQL. This process validates budget compliance and prevents over-budget execution by calculating expected data scanned before actual query execution.

How do I build spatial aggregation queries in BigQuery for Overture Maps data?

Build spatial aggregation queries by transforming plain-language geographic questions into BigQuery Overture Maps SQL. This process leverages H3 indexing for spatial aggregation and ensures queries are optimized for safe iteration.

Can I enforce project budget limits when querying Overture Maps datasets in BigQuery?

Enforce project budget limits by generating BigQuery Overture Maps SQL with built-in cost safeguards. Dry-run estimates verify that queries respect strict cost constraints before execution, ensuring complete budget compliance.

What are dry-run checks in BigQuery and how do they control Overture Maps query costs?

Dry-run checks in BigQuery estimate the data volume scanned to control Overture Maps query costs. They evaluate query safety and block execution if the estimated cost exceeds your defined project budgets.

How do I convert natural language geographic questions into BigQuery Overture Maps SQL?

Convert natural language geographic questions into BigQuery Overture Maps SQL through automated query generation. This mechanism creates spatial queries that include cost limits and optimize query safety using dedicated spatial functions.

Does this approach support H3 spatial indexing for BigQuery Overture Maps queries?

H3 spatial indexing is fully supported for BigQuery Overture Maps queries. It enables spatial aggregation with H3 indexing and provides easy visualization handoff for data analysts and geospatial professionals.