big-data-cloud-automation
npx machina-cli add skill ComposioHQ/awesome-claude-skills/big-data-cloud-automation --openclawBig Data Cloud Automation via Rube MCP
Automate Big Data Cloud operations through Composio's Big Data Cloud toolkit via Rube MCP.
Toolkit docs: composio.dev/toolkits/big_data_cloud
Prerequisites
- Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
- Active Big Data Cloud connection via
RUBE_MANAGE_CONNECTIONSwith toolkitbig_data_cloud - Always call
RUBE_SEARCH_TOOLSfirst 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.
- Verify Rube MCP is available by confirming
RUBE_SEARCH_TOOLSresponds - Call
RUBE_MANAGE_CONNECTIONSwith toolkitbig_data_cloud - If connection is not ACTIVE, follow the returned auth link to complete setup
- Confirm connection status shows ACTIVE before running any workflows
Tool Discovery
Always discover available tools before executing workflows:
RUBE_SEARCH_TOOLS
queries: [{use_case: "Big Data Cloud operations", known_fields: ""}]
session: {generate_id: true}
This returns available tool slugs, input schemas, recommended execution plans, and known pitfalls.
Core Workflow Pattern
Step 1: Discover Available Tools
RUBE_SEARCH_TOOLS
queries: [{use_case: "your specific Big Data Cloud task"}]
session: {id: "existing_session_id"}
Step 2: Check Connection
RUBE_MANAGE_CONNECTIONS
toolkits: ["big_data_cloud"]
session_id: "your_session_id"
Step 3: Execute Tools
RUBE_MULTI_EXECUTE_TOOL
tools: [{
tool_slug: "TOOL_SLUG_FROM_SEARCH",
arguments: {/* schema-compliant args from search results */}
}]
memory: {}
session_id: "your_session_id"
Known Pitfalls
- Always search first: Tool schemas change. Never hardcode tool slugs or arguments without calling
RUBE_SEARCH_TOOLS - Check connection: Verify
RUBE_MANAGE_CONNECTIONSshows ACTIVE status before executing tools - Schema compliance: Use exact field names and types from the search results
- Memory parameter: Always include
memoryinRUBE_MULTI_EXECUTE_TOOLcalls, even if empty ({}) - Session reuse: Reuse session IDs within a workflow. Generate new ones for new workflows
- Pagination: Check responses for pagination tokens and continue fetching until complete
Quick Reference
| Operation | Approach |
|---|---|
| Find tools | RUBE_SEARCH_TOOLS with Big Data Cloud-specific use case |
| Connect | RUBE_MANAGE_CONNECTIONS with toolkit big_data_cloud |
| Execute | RUBE_MULTI_EXECUTE_TOOL with discovered tool slugs |
| Bulk ops | RUBE_REMOTE_WORKBENCH with run_composio_tool() |
| Full schema | RUBE_GET_TOOL_SCHEMAS for tools with schemaRef |
Powered by Composio
Source
git clone https://github.com/ComposioHQ/awesome-claude-skills/blob/master/composio-skills/big-data-cloud-automation/SKILL.mdView on GitHub Overview
This skill automates Big Data Cloud operations using Composio's Rube MCP toolkit. It guides you to always search for current tool schemas first with RUBE_SEARCH_TOOLS to avoid hardcoding tool slugs or args. It covers setup, tool discovery, and core workflow steps to safely run workflows.
How This Skill Works
Connect Rube MCP and verify the connection with RUBE_SEARCH_TOOLS. Then discover available tools for your Big Data Cloud task, ensure the connection is ACTIVE with RUBE_MANAGE_CONNECTIONS, and finally execute the chosen tools using RUBE_MULTI_EXECUTE_TOOL with the required memory object and a session_id derived from discovery.
When to Use It
- You are automating a Big Data Cloud workflow and need to adapt to changing tool schemas without manual reconfiguration.
- You want to validate the Big Data Cloud connection is ACTIVE before running any workflows.
- You follow a core pattern of discover, check, and execute for each data task.
- You plan to perform bulk or multi-tool operations in a single workflow.
- You need to reuse session IDs within a workflow instead of creating new ones for every step.
Quick Start
- Step 1: Run RUBE_SEARCH_TOOLS with your Big Data Cloud use case to discover available tools and schemas.
- Step 2: Run RUBE_MANAGE_CONNECTIONS for toolkit big_data_cloud and verify the status is ACTIVE.
- Step 3: Run RUBE_MULTI_EXECUTE_TOOL with the discovered tool_slug, memory, and a valid session_id.
Best Practices
- Always search first: tool schemas change, so never hardcode tool slugs or arguments.
- Check connection: ensure RUBE_MANAGE_CONNECTIONS shows ACTIVE before executing tools.
- Schema compliance: use exact field names and types from the search results.
- Memory parameter: always include memory in RUBE_MULTI_EXECUTE_TOOL calls, even if empty.
- Session reuse: reuse session IDs within a workflow to maintain context.
Example Use Cases
- Schedule a nightly ETL by discovering tools with RUBE_SEARCH_TOOLS and then executing the appropriate tool slug with memory and a session_id.
- Validate and establish a big_data_cloud connection before a data load, ensuring the connection remains ACTIVE.
- Run a multi-step workflow in a single run by reusing the same session_id across tools.
- Perform bulk data operations using RUBE_REMOTE_WORKBENCH and run_composio_tool for multiple tasks.
- Fetch full tool schemas with RUBE_GET_TOOL_SCHEMAS to verify required fields before execution.
