BigQuery

Triggers0

Things that can wake up your BigQuery coworker.

No triggers published for BigQuery yet — but you can still run it on a schedule or from a chat.

Actions20

Things your coworker can do in BigQuery.

• Create Analytics Hub Listing

  Tool to create a new listing in a BigQuery Analytics Hub data exchange. Use when you need to share a BigQuery dataset with specific subscribers or make it available for discovery. The dataset must exist and be in the same region as the data exchange.

  GOOGLEBIGQUERY_CREATE_DATAEXCHANGES_LISTINGS
• Create BigQuery Dataset

  Tool to create a new BigQuery dataset with explicit location, labels, and description using the BigQuery Datasets API. Use when the workflow needs to set up a staging/warehouse dataset and correctness of region is critical to avoid downstream job location mismatches. Surfaces 409 Already Exists errors cleanly without retrying.

  GOOGLEBIGQUERY_CREATE_DATASET
• Create BigQuery Routine

  Tool to create a new user-defined routine (function or procedure) in a BigQuery dataset. Use when you need to define SQL, JavaScript, Python, Java, or Scala functions/procedures for reusable logic, data transformations, or custom masking. Supports scalar functions, table-valued functions, procedures, and aggregate functions with comprehensive type definitions.

  GOOGLEBIGQUERY_CREATE_ROUTINE
• Create BigQuery Table

  Tool to create a new, empty table in a BigQuery dataset. Use when setting up data infrastructure for standard tables, external tables, views, or materialized views. Supports partitioning, clustering, and encryption configuration.

  GOOGLEBIGQUERY_CREATE_TABLE
• Delete BigQuery Dataset

  Tool to delete a BigQuery dataset specified by datasetId via the datasets.delete API. Before deletion, you must delete all tables unless deleteContents=True is specified. Use when cleaning up test datasets or removing unused data warehouses. Immediately after deletion, you can create another dataset with the same name.

  GOOGLEBIGQUERY_DELETE_DATASET
• Delete BigQuery ML Model

  Tool to delete a BigQuery ML model from a dataset. Use when you need to remove a trained machine learning model permanently. The operation deletes the model and cannot be undone.

  GOOGLEBIGQUERY_DELETE_MODEL
• Delete BigQuery Table

  Tool to delete a BigQuery table from a dataset. Use when you need to remove a table and all its data permanently. The operation deletes all data in the table and cannot be undone.

  GOOGLEBIGQUERY_DELETE_TABLE
• Get BigQuery Dataset Metadata

  Tool to retrieve BigQuery dataset metadata including location via the datasets.get API. Use this before creating jobs/queries if the workflow has been failing with location mismatch to confirm the dataset's region and correct the job location accordingly.

  GOOGLEBIGQUERY_GET_DATASET
• Get BigQuery Job

  Tool to retrieve information about a specific BigQuery job. Returns job configuration, status, and statistics. Use this to check job status after running queries or to get details about job execution.

  GOOGLEBIGQUERY_GET_JOB
• Get BigQuery Query Results

  Tool to get the results of a BigQuery query job via RPC. Use this to retrieve results after running a query, or to check job completion status and fetch paginated results.

  GOOGLEBIGQUERY_GET_QUERY_RESULTS
• Get BigQuery Table Schema

  Tool to fetch a BigQuery table's schema and metadata without querying row data. Use before generating SQL queries to avoid column name typos and confirm field types and nullable modes. This is especially useful when INFORMATION_SCHEMA access is restricted.

  GOOGLEBIGQUERY_GET_TABLE_SCHEMA
• Insert Data into BigQuery Table

  Tool to stream data into BigQuery one record at a time without running a load job. Use when you need immediate data availability or inserting small batches. Supports row-level deduplication via insertId and error handling via skipInvalidRows.

  GOOGLEBIGQUERY_INSERT_ALL
• Insert BigQuery Job

  Tool to start a new asynchronous BigQuery job (query, load, extract, or copy). Use when you need to run a query as a job, load data from Cloud Storage, extract table data to GCS, or copy tables. For dry-run validation without execution, set dryRun to true in configuration.

  GOOGLEBIGQUERY_INSERT_JOB
• Insert BigQuery Job with Upload

  Tool to start a new BigQuery load job with file upload. Uploads a file (CSV, JSON, etc.) and loads it into a BigQuery table in a single operation. Use when you need to upload data from a local file directly to BigQuery rather than loading from Cloud Storage.

  GOOGLEBIGQUERY_INSERT_JOB_WITH_UPLOAD
• List BigQuery Datasets

  Tool to list datasets in a specific BigQuery project, including dataset locations. Use after identifying an accessible project to discover available datasets and their locations before querying. The dataset location is critical for avoiding location-related query/job errors.

  GOOGLEBIGQUERY_LIST_DATASETS
• List BigQuery Jobs

  Tool to list all jobs that you started in a BigQuery project. Job information is available for a six month period after creation. Jobs are sorted in reverse chronological order by creation time. Use to monitor query execution, track job statuses, and retrieve job history.

  GOOGLEBIGQUERY_LIST_JOBS
• List BigQuery Models

  Tool to list all BigQuery ML models in a specified dataset. Requires READER dataset role. Use this to discover available models before getting detailed information via models.get method.

  GOOGLEBIGQUERY_LIST_MODELS
• List BigQuery Projects

  Tool to list BigQuery projects to which the user has been granted any project role. Returns projects with at least READ access. For enhanced capabilities, consider using the Resource Manager API.

  GOOGLEBIGQUERY_LIST_PROJECTS
• List BigQuery Table Data

  Tool to list the content of a BigQuery table in rows via the REST API. Use this to retrieve actual data from a table without writing SQL queries. Returns paginated results with row data in the native BigQuery format.

  GOOGLEBIGQUERY_LIST_TABLE_DATA
• List BigQuery Tables

  Tool to list tables in a BigQuery dataset via the REST API. Use this early in exploration to discover accessible tables without relying on INFORMATION_SCHEMA, especially when SQL-based metadata queries are blocked or restricted. This provides a deterministic inventory of tables even when dataset-level permissions prevent INFORMATION_SCHEMA access.

  GOOGLEBIGQUERY_LIST_TABLES