richardhe-fundamenta/practical-gcp-examples/bigquery-basics

Claude Code and agent skill by richardhe-fundamenta/practical-gcp-examples

Trust tier 2
  • community
LLM review pending
Source check pending

Checking that the SKILL.md file is still in the repository.

Manages datasets, tables, and jobs in BigQuery, and integrates with BigQuery ML and Gemini for advanced data analytics and AI-driven insights. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources, or leverage BigQuery's built-in ML capabilities. Also use when performing data analysis, ingesting data into BigQuery, or developing AI applications on BigQuery.

Install

npx vskill@latest install richardhe-fundamenta/practical-gcp-examples/bigquery-basics

SKILL.md

BigQuery Basics

BigQuery is a serverless, AI-ready data platform that enables high-speed analysis of large datasets using SQL and Python. Its disaggregated architecture separates compute and storage, allowing them to scale independently while providing built-in machine learning, geospatial analysis, and business intelligence capabilities.

Setup and Basic Usage

  1. Enable the BigQuery API:

``bash gcloud services enable bigquery.googleapis.com --quiet ``

  1. Create a Dataset:

``bash bq mk --dataset --location=US my_dataset ``

  1. Create a Table:

Create a file named schema.json with your table schema:

``json [ { "name": "name", "type": "STRING", "mode": "REQUIRED" }, { "name": "post_abbr", "type": "STRING", "mode": "NULLABLE" } ] ``

Then create the table with the bq tool:

``bash bq mk --table my_dataset.mytable schema.json ``

  1. Run a Query:

``bash bq query --use_legacy_sql=false \ 'SELECT name FROM bigquery-public-data.usa_names.usa_1910_2013 \ WHERE state = "TX" LIMIT 10' ``

Reference Directory

workflows, and BigQuery Studio features.

operations for managing data and jobs.

client libraries for Python, Java, Node.js, and Go.

  • MCP Usage: Using the BigQuery remote MCP server and

Gemini CLI extension.

datasets, tables, and reservations.

governance best practices.

TimesFM model for forecasting without custom training.

deviations in time series data using pre-trained TimesFM model.

content generation using Gemini models.

If you need product information not found in these references, use the Developer Knowledge MCP server `search_documents` tool.

Related Skills

SKILL.md file for BigQuery AI and ML capabilities.

Reference files published for the BigQuery AI and ML skill.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
41
Repository forks
17
7-day trend score
19

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

  • Claude Code
  • Cursor
  • GitHub Copilot
  • Windsurf
  • Codex
  • Gemini CLI
  • Cline
  • Amp
  • Roo Code
  • Goose
  • Continue
  • Kilo Code
  • Junie
  • Trae
  • OpenHands
  • Qwen Code
  • AI Agent
  • Tabnine Chat
  • Sourcegraph Cody
  • Amazon Q
  • Firebase Genkit
  • Sweep
  • Devin
  • Phind
  • Mentat
  • Claude Desktop
  • Aider
  • GPT Pilot
  • Plandex
  • bolt.new
  • v0
  • Replit Agent
  • Anse
  • TypingMind
  • BetterChatGPT
  • LibreChat
  • Warp AI
  • Pieces
  • Fig AI
Embed badge
vskill VERIFIED badge
[![vskill VERIFIED](https://verified-skill.com/api/v1/skills/richardhe-fundamenta/practical-gcp-examples/bigquery-basics/badge)](https://verified-skill.com/skills/richardhe-fundamenta/practical-gcp-examples/bigquery-basics)

Something wrong with this skill or its page? Tell us.