Query BigQuery datasets, retrieve table metadata, and generate analytical insights including time-series forecasting and contribution analysis using standard SQL and BigQuery AI/ML functions.
Skill for BigQuery AI and Machine Learning queries using standard SQL and `AI.*` functions (preferred over dedicated tools).
Use these skills when you need to handle advanced data intelligence and predictive tasks. Use when a user asks "why" data changed or needs future projections. Provides automated insight generation and time-series forecasting.
Use these skills when you need to handle large-scale data exploration and dataset management. Use when users need to find data assets or run SQL at scale. Provides metadata discovery and query execution across the data warehouse.
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Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
This plugin requires configuration values that are prompted when the plugin is enabled. Sensitive values are stored in your system keychain.
bigquery_projectID of the Google Cloud project
${user_config.bigquery_project}bigquery_location(Optional) Location of the BigQuery resources
${user_config.bigquery_location}[!NOTE] Currently in beta (pre-v1.0), and may see breaking changes until the first stable release (v1.0).
Developers can effortlessly connect, interact, and generate data insights with BigQuery datasets and data using natural language commands.
[!IMPORTANT] We Want Your Feedback! Please share your thoughts with us by filling out our feedback form. Your input is invaluable and helps us improve the project for everyone.
Before you begin, ensure you have the following:
roles/bigquery.user)roles/bigquery.connectionUser)roles/aiplatform.user)Please keep these env vars handy during the installation process:
BIGQUERY_PROJECT: The GCP project ID.BIGQUERY_LOCATION: (Optional) The dataset location.[!NOTE]
- Ensure Application Default Credentials are available in your environment.
To start interacting with your database, install the skills for your preferred AI agent, then launch the agent and use natural language to ask questions or perform tasks.
For the latest version, check the releases page.
You can use either of these two agents for Antigravity:
💡 Tip — Migrating from Gemini CLI?
If you previously installed this extension withgemini extensions install, you can convert it to an Antigravity plugin instead of reinstalling from scratch:See Migrating from Gemini CLI for details on plugins, context files (
- On first launch of Antigravity CLI, accept the Migration Options prompt to automatically convert your installed Gemini CLI extensions to Antigravity plugins.
- Or, from your terminal, run:
agy plugin import geminiGEMINI.md/AGENTS.md), and MCP server config differences.
1. Clone the Repo:
git clone --branch 0.2.1 https://github.com/gemini-cli-extensions/bigquery-data-analytics.git
2. Install the skills:
Choose a location for the skills:
~/.gemini/antigravity/skills/<workspace-root>/.agents/skills/Copy the skill folders from the cloned repository's skills/ directory to your chosen location:
cp -R bigquery-data-analytics/skills/* ~/.gemini/antigravity/skills/
npx claudepluginhub gemini-cli-extensions/bigquery-data-analytics --plugin bigquery-data-analyticsThis plugin provides a specialized suite of skills for data engineers and database practitioners working on Google Cloud. It acts as an expert assistant, allowing you to use natural language prompts in your preferred coding agent to architect complex data pipelines, transform data with dbt, write Spark and BigQuery SQL notebooks, and orchestrate end-to-end workflows across GCP's data ecosystem.
🐉 Specialised SRE skills for outage investigations, monitoring graphs, and post-mortems on Google Cloud Platform.
Connect to Looker and interact with your data using LookML.
The CI/CD extension provides Gemini powered AI assisted CI/CD. It supports deployment to Cloud Run and Cloud Storage as well as creation of a robust CI/CD pipeline.
Create, connect, and interact with a Cloud SQL for PostgreSQL database and data.
Comprehensive BigQuery skill suite: query optimization, SQL generation, schema design, cost optimization, and feature guidance.
Data analysis expert for SQL queries, BigQuery operations, and data insights. Use proactively for data analysis tasks and queries.
BigQuery cost analysis and optimization utilities
This plugin provides a specialized suite of skills for data engineers and database practitioners working on Google Cloud. It acts as an expert assistant, allowing you to use natural language prompts in your preferred coding agent to architect complex data pipelines, transform data with dbt, write Spark and BigQuery SQL notebooks, and orchestrate end-to-end workflows across GCP's data ecosystem.
Skills and tools powered by the Honeydew MCP that help coding agents query data and build semantic models
Data engineering and time series analysis mastery. Expert in jq, SQL, pandas, time series forecasting, ETL pipelines, streaming, and analytics visualization.