bigquery

Manage Google BigQuery operations via a Rust-based CLI.

40|12|Updated Oct 17, 2011

Search Tags:#SQL #etl #bigquery #data-warehouse #cost

Ready to run

npx skills add https://github.com/lanej/dotfiles --skill bigquery-lanej

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: bigquery
Source: https://github.com/lanej/dotfiles/tree/main/claude/skills/bigquery
Command: npx skills add https://github.com/lanej/dotfiles --skill bigquery-lanej

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill guides using a Rust-based BigQuery CLI to perform data warehouse operations with authentication, query execution, cost awareness, dataset/table management, and data loading capabilities.

Core Features & Use Cases

Authentication: check status and login with gcloud.
Query execution: run SQL with cost estimates and confirmation prompts.
Dry Run: estimate query costs without executing.
Dataset & Table operations: list, describe, insert, load, and manage external tables.
Template system: named query templates with parameter substitution.
MCP/LSP server integration: semantic search and language server support for editors.

Quick Start

Example: run a simple, cost-aware query: bigquery query "SELECT 1"

Frequently Asked Questions about bigquery

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

FAQPage Schema

How do I run SQL queries against BigQuery with cost estimates before executing?▼

BigQuery CLI provides cost-aware query execution with dry-run estimation and confirmation prompts. Run `bigquery query "SELECT ..."` to see cost estimates, use the dry-run feature to preview costs without executing, and confirm before charges apply.

Can I manage BigQuery datasets and tables from the command line?▼

Yes, the CLI supports dataset and table operations including listing, describing, inserting, and loading data. Perform schema operations and manage external tables directly from your terminal without switching to the web console.

What's the best way to reuse SQL queries in BigQuery with parameters?▼

The template system stores named query templates with parameter substitution, eliminating repetitive SQL writing. Define templates once and execute them with different parameters across your data warehouse workflows.

Does BigQuery CLI work with editor integration and AI-assisted querying?▼

Yes, MCP and LSP server modes enable semantic search and language server support in editors. This provides AI-assisted querying and integration for both streaming inserts and bulk loads within your development environment.

How do I authenticate and verify BigQuery access from the CLI?▼

Check authentication status and log in using gcloud integration with built-in CLI commands. Verify your credentials and permissions before running queries or managing datasets.

Can I estimate query costs in BigQuery without running the full query?▼

The dry-run feature estimates query costs without execution, letting you assess data warehouse expenses upfront. Useful for validating large-scale ETL and data warehouse operations before committing resources.