What does this skill do?

Automates Sendbird AI Chabot tasks via Rube MCP (Composio) with tool discovery and execution.

What prerequisites are needed?

Rube MCP connected; RUBE_SEARCH_TOOLS available; RUBE_MANAGE_CONNECTIONS for the sendbird_ai_chabot toolkit; always call RUBE_SEARCH_TOOLS before executing.

How do I run a workflow?

Search tools to get current schemas, ensure the connection is ACTIVE, then execute tools with RUBE_MULTI_EXECUTE_TOOL using a session_id and memory.

sendbird-ai-chabot-automation

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SKILL.md

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Sendbird AI Chabot Automation via Rube MCP

Automate Sendbird AI Chabot operations through Composio's Sendbird AI Chabot toolkit via Rube MCP.

Toolkit docs: composio.dev/toolkits/sendbird_ai_chabot

Prerequisites

Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
Active Sendbird AI Chabot connection via RUBE_MANAGE_CONNECTIONS with toolkit sendbird_ai_chabot
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.

Verify Rube MCP is available by confirming RUBE_SEARCH_TOOLS responds
Call RUBE_MANAGE_CONNECTIONS with toolkit sendbird_ai_chabot
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: "Sendbird AI Chabot 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 Sendbird AI Chabot task"}]
session: {id: "existing_session_id"}

Step 2: Check Connection

RUBE_MANAGE_CONNECTIONS
toolkits: ["sendbird_ai_chabot"]
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_CONNECTIONS shows ACTIVE status 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. 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 Sendbird AI Chabot-specific use case
Connect	`RUBE_MANAGE_CONNECTIONS` with toolkit `sendbird_ai_chabot`
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/sendbird-ai-chabot-automation/SKILL.md

View on GitHub

Overview

Automate Sendbird AI Chabot operations through Composio's Sendbird AI Chabot toolkit via Rube MCP. It enables discovery of current tool schemas, management of Active connections, and execution of orchestrated workflows.

How This Skill Works

First, discover available tools with RUBE_SEARCH_TOOLS to obtain slugs and schemas for your use case. Then verify the Sendbird tool connection with RUBE_MANAGE_CONNECTIONS and ensure it is ACTIVE. Finally, run tools with RUBE_MULTI_EXECUTE_TOOL, passing the discovered tool_slug, memory, and a session_id; always include memory and reuse sessions when appropriate.

When to Use It

You need to automate a sequence of Sendbird AI Chabot operations.
Tool schemas frequently change and you must fetch current slugs first.
You are establishing a new Sendbird AI Chabot integration and must validate the connection.
You want to execute multiple tools in a single workflow using a session.
You need to troubleshoot or optimize a workflow by re-discovering available tools.

Quick Start

Step 1: Verify Rube MCP is available and that RUBE_SEARCH_TOOLS responds.
Step 2: Discover tools for your task using RUBE_SEARCH_TOOLS with use_case set to your specific Sendbird AI Chabot task.
Step 3: Manage connection and execute tools via RUBE_MULTI_EXECUTE_TOOL using the discovered tool_slug, memory, and a session_id.

Best Practices

Always search first for current tool schemas to avoid broken automation.
Verify the connection status is ACTIVE before executing tools.
Use exact field names and types from the search results; avoid hardcoding.
Always include memory in RUBE_MULTI_EXECUTE_TOOL calls, even if empty.
Reuse session IDs within a workflow and manage pagination when fetching results.

Example Use Cases

Health-check a Sendbird AI Chabot integration by discovering tools and running a status tool.
Update bot responses by discovering the correct tool slug from current schemas and executing with fresh arguments.
Bulk maintenance: discover multiple tools and run them in a single session to update configs across several bots.
Validate schemas for a specific use case like Sendbird AI Chabot operations before automation.
If a workflow fails, re-discover tools, re-establish an ACTIVE connection, and retry using the same session when possible.

Frequently Asked Questions

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