Query and manage Google BigQuery datasets via CLI and REST API.
npx skills add https://github.com/TeamDay-AI/agents --skill bigquery-teamday-ai
Please help me install this Agent Skill. Skill: bigquery Source: https://github.com/TeamDay-AI/agents/tree/main/skills/teamday/bigquery Command: npx skills add https://github.com/TeamDay-AI/agents --skill bigquery-teamday-ai
Efficiently query, export, and manage Google BigQuery datasets from the command line or REST API, reducing manual toil and speeding data workflows.
Run a sample query against a dataset to verify access and outputs.
High-intent search queries and answers about installing and using this skill.
Run SQL queries against BigQuery datasets using the bq CLI or REST API to execute standard SQL statements. This enables ad-hoc analytics and ETL pipeline automation directly from the command line.
To authenticate BigQuery REST API requests, you need the bq CLI installed and credentials provided via GOOGLE_APPLICATION_CREDENTIALS_JSON and BIGQUERY_PROJECT_ID environment variables to authorize dataset and table operations.
Yes, you can export BigQuery query results to CSV or JSON formats. The Skill supports exporting data outputs and monitoring job status for data migration tasks and analytics workflows.
List and manage BigQuery datasets and tables by executing dataset-management operations through the bq CLI. This supports data catalog maintenance and allows you to create, list, and organize tables across projects.
Yes, the bq CLI is required for BigQuery dataset management and export operations. The Skill relies on the bq CLI installed locally alongside GOOGLE_APPLICATION_CREDENTIALS_JSON to authenticate and authorize operations.
The best way to automate ETL pipelines with BigQuery is using the bq CLI and REST API to run standard SQL queries, manage datasets, and export results. This reduces manual toil and speeds up data workflows.
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