bigquery-api Skill
Run SQL against Google BigQuery and browse its catalog — submit queries (sync or async), poll job status, page through results, list datasets/tables, and read table schemas. Use this whenever the user wants to query a BigQuery table, ask "what's in this dataset", check a BigQuery job's status, or mentions bigquery.goog Published by anthropics in claude-tag-plugins.
What is bigquery-api Skill?
Run SQL against Google BigQuery and browse its catalog — submit queries (sync or async), poll job status, page through results, list datasets/tables, and read table schemas. Use this whenever the user wants to query a BigQuery table, ask "what's in this dataset", check a BigQuery job's status, or mentions bigquery.goog Published by anthropics in claude-tag-plugins. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Database workflows
- Data analysis
- Database workflows use cases
- Data analysis use cases
Technical details
- Install or run with Copy skill directory
When to use bigquery-api Skill
- Use it for database workflows.
- Use it for data analysis.
Built with
Editorial notes
Source
- Creator: anthropics
- Repository: anthropics/claude-tag-plugins
- Skill file: bigquery/skills/bigquery-api/SKILL.md
What it does
Run SQL against Google BigQuery and browse its catalog — submit queries (sync or async), poll job status, page through results, list datasets/tables, and read table schemas. Use this whenever the user wants to query a BigQuery table, ask "what's in this dataset", check a BigQuery job's status, or mentions bigquery.goog
Skill instructions
BigQuery's REST API (bigquery.googleapis.com/bigquery/v2) lets you run SQL, inspect jobs, and browse datasets and table schemas with plain curl — no SDK required. The central concept is a job. Every query runs as a job in a project (the project is billed, and is not necessarily where the data lives). Under the hood a query runs one of two ways — scripts/bqquery.sh (operation 1) drives this for you: - Synchronous (jobs.query) — one POST that blocks up to a timeout and returns rows inline if the query finishes in time. - Asynchronous (jobs.insert → jobs.get → jobs.getQueryResults) — submit, poll, then page results. The route you use directly for destination tables, BATCH priority, or load/extract/copy jobs. Everything else (datasets, tables, schemas) is a simple GET. Request setup Authentication is handled by the runtime — credentials are injected into outbound requests to this API, so there is nothing to set up. Do not try to create, mint, refresh, or validate tokens or keys. Credential
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Frequently asked questions
What is bigquery-api?
bigquery-api is a open-source AI agent skill with Copy skill directory. Run SQL against Google BigQuery and browse its catalog — submit queries (sync or async), poll job status, page through results, list datasets/tables, and read table schemas.
Who is bigquery-api best for?
bigquery-api is best for reusing agent instructions, scripts, and references, database workflows, data analysis workflows.
How do I install bigquery-api?
Install or run bigquery-api using Copy skill directory. Check bigquery-api for the latest setup command.
Is bigquery-api actively maintained?
bigquery-api may need a closer maintenance check before production use.
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