Googlebigquery Automation

When to use this skill

Use Googlebigquery Automation when an AI agent needs a reusable SKILL.md workflow for this job: Automate Google BigQuery tasks via Rube MCP (Composio): run SQL queries, explore datasets and metadata, execute MBQL queries via Metabase integration. Always search tools first for current schemas.

When not to use it

Skip Googlebigquery Automation when the task is outside the productivity category, or when a more specific skill in this directory already covers the same workflow with clearer triggers.

How to install

1. Personal install: create ~/.claude/skills/googlebigquery-automation/SKILL.md (and any bundled scripts) so Claude Code, Claude Desktop, and compatible agents can load it in every project.
2. Project install: commit the same folder at .claude/skills/googlebigquery-automation/ so teammates get the skill with the repo.
3. Restart the agent session after copying files so it re-scans the skills directory, then ask for the task in words that match the skill description.

Full install guide for Claude, Cursor, and Codex

What this skill does

# Google BigQuery Automation via Rube MCP

Run SQL queries, explore database schemas, and analyze datasets through the Metabase integration using Rube MCP (Composio).

**Toolkit docs**: [composio.dev/toolkits/googlebigquery](https://composio.dev/toolkits/googlebigquery)

## Prerequisites - Rube MCP must be connected (RUBE_SEARCH_TOOLS available) - Active connection via `RUBE_MANAGE_CONNECTIONS` with toolkit `metabase` - A Metabase instance connected to your BigQuery data source - Always call `RUBE_SEARCH_TOOLS` first to get current tool schemas

## Setup **Get Rube MCP**: Add `https://rube.app/mcp` as an MCP server in your client configuration. No API keys needed — just add the endpoint and it works.

1. Verify Rube MCP is available by confirming `RUBE_SEARCH_TOOLS` responds 2. Call `RUBE_MANAGE_CONNECTIONS` with toolkit `metabase` 3. If connection is not ACTIVE, follow the returned auth link to complete setup 4. Confirm connection status shows ACTIVE before running any workflows

> **Note**: BigQuery data is accessed through Metabase, a business intelligence tool that connects to BigQuery as a data source. The tools below execute queries and retrieve metadata through Metabase's API.

## Core Workflows

### 1. Run a Native SQL Query Use `METABASE_POST_API_DATASET` with type `native` to execute raw SQL queries against your BigQuery database. ``` Tool: METABASE_POST_API_DATASET Parameters: - database (required): Metabase database ID (integer) - type (required): "native" for SQL queries - native (required): Object with "query" string - query: Raw SQL string (e.g., "SELECT * FROM users LIMIT 10") - template_tags: Parameterized query variables (optional) - constraints: { "max-results": 1000 } (optional) ```

### 2. Run a Structured MBQL Query Use `METABASE_POST_API_DATASET` with type `query` for Metabase Query Language queries with built-in aggregation and filtering. ``` Tool: METABASE_POST_API_DATASET Parameters: - database (required): Metabase database ID - type (required): "query" for MBQL - query (required): Object with: - source-table: Table ID (integer) - aggregation: e.g., [["count"]] or [["sum", ["field", 5, null]]] - breakout: Group-by fields - filter: Filter conditions - limit: Max rows - order-by: Sort fields ```

### 3. Get Query Metadata Use `METABASE_POST_API_DATASET_QUERY_METADATA` to retrieve metadata about databases, tables, and fields available for querying. ``` Tool: METABASE_POST_API_DATASET_QUERY_METADATA Parameters: - database (required): Metabase database ID - type (required): "query" or "native" - query (required): Query object (e.g., {"source-table": 1}) ```

### 4. Convert Query to Native SQL Use `METABASE_POST_API_DATASET_NATIVE` to convert an MBQL query into its native SQL representation. ``` Tool: METABASE_POST_API_DATASET_NATIVE Parameters: - database (required): Metabase database ID - type (required): "native" - native (required): Object with "query" and optional "template_tags" - parameters: Query parameter values (optional) ```

### 5. List Available Databases Use `METABASE_GET_API_DATABASE` to discover all database connections configured in Metabase. ``` Tool: METABASE_GET_API_DATABASE Description: Retrieves a list of all Database instances configured in Metabase. Note: Call RUBE_SEARCH_TOOLS to get the full schema for this tool. ```

### 6. Get Database Schema Metadata Use `METABASE_GET_API_DATABASE_ID_METADATA` to retrieve complete table and field information for a specific database. ``` Tool: METABASE_GET_API_DATABASE_ID_METADATA Description: Retrieves complete metadata for a specific database including all tables and fields. Note: Call RUBE_SEARCH_TOOLS to get the full schema for this tool. ```

## Common Patterns

- **Discover then query**: Use `METABASE_GET_API_DATABASE` to find database IDs, then `METABASE_GET_API_DATABASE_ID_METADATA` to explore tables and fields, then `METABASE_POST_API_DATASET` to run queries. - **SQL-first approach**: Use `METABASE_POST_API_DATASET` with `type: "native"` and write standard SQL queries for maximum flexibility. - **Parameterized queries**: Use `template_tags` in native queries for safe parameterization (e.g., `SELECT * FROM users WHERE id = {{user_id}}`). - **Schema exploration**: Use `METABASE_POST_API_DATASET_QUERY_METADATA` to understand table structures before building complex queries. - **Get parameter values**: Use `METABASE_POST_API_DATASET_PARAMETER_VALUES` to retrieve possible values for filter dropdowns.

## Known Pitfalls

- The `database` parameter is a Metabase-internal **integer ID**, not the BigQuery project or dataset name. Use `METABASE_GET_API_DATABASE` to find valid database IDs first. - `source-table` in MBQL queries is also a Metabase-internal integer, not the BigQuery table name. Discover table IDs via metadata tools. - Native SQL queries use BigQuery SQL dialect (Standard SQL). Ensure your syntax is BigQuery-compatible. - `max-results` in constraints defaults can limit returned rows. Set explicitly for large result sets. - Responses from `METABASE_POST_API_DATASET` contain results nested under `data` -- parse carefully as the structure may be deeply nested. - Metabase field IDs used in MBQL `aggregation`, `breakout`, and `filter` arrays must be integers obtained from metadata responses.

## Quick Reference | Action | Tool | Key Parameters | |--------|------|----------------| | Run SQL query | `METABASE_POST_API_DATASET` | `database`, `type: "native"`, `native.query` | | Run MBQL query | `METABASE_POST_API_DATASET` | `database`, `type: "query"`, `query` | | Get query metadata | `METABASE_POST_API_DATASET_QUERY_METADATA` | `database`, `type`, `query` | | Convert to SQL | `METABASE_POST_API_DATASET_NATIVE` | `database`, `type`, `native` | | Get parameter values | `METABASE_POST_API_DATASET_PARAMETER_VALUES` | `parameter`, `field_ids` | | List databases | `METABASE_GET_API_DATABASE` | (see full schema via RUBE_SEARCH_TOOLS) | | Get database metadata | `METABASE_GET_API_DATABASE_ID_METADATA` | (see full schema via RUBE_SEARCH_TOOLS) |

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Intended uses

• Use Googlebigquery Automation when this documented workflow matches the task.