Rafflys Automation
Automate Rafflys raffle and contest operations via Composio's Rube MCP.
Install
npx promptshop add rafflys-automationDetails
What This Skill Does
This skill automates Rafflys operations using the Composio's Rafflys toolkit via Rube MCP. It allows users to streamline Rafflys tasks by discovering available tools, checking connections, and executing specific workflows. This is designed for users who want to integrate Rafflys with other systems and automate raffle and contest management processes.
When to Use
Automate raffle entryManage raffle participantsSelect raffle winnersDistribute raffle prizesManage Rafflys connectionsCreate new raffles
Key Features
Uses Rube MCP for Rafflys automation. Requires an active Rafflys connection. Employs RUBE_SEARCH_TOOLS for tool discovery. Utilizes RUBE_MANAGE_CONNECTIONS for connection management. Executes tools with RUBE_MULTI_EXECUTE_TOOL. Provides a structured workflow pattern.
Manual Installation
Manual installationView Full Skill ContentThe complete markdown content that gets installedRafflys Automation via Rube MCP
Automate Rafflys operations through Composio's Rafflys toolkit via Rube MCP.
Toolkit docs: composio.dev/toolkits/rafflys
Prerequisites
Rube MCP must be connected (RUBE_SEARCH_TOOLS available) Active Rafflys connection via RUBE_MANAGE_CONNECTIONS with toolkit rafflys 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 rafflys 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: "Rafflys 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 Rafflys task"}] session: {id: "existing_session_id"}
Step 2: Check Connection
RUBE_MANAGE_CONNECTIONS toolkits: ["rafflys"] 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 Rafflys-specific use case |
| Connect | RUBE_MANAGE_CONNECTIONS with toolkit rafflys |
| 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 |
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