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docnify-automation

Automate Docnify operations through Rube MCP, a connection between an AI agent and external tools. The skill discovers supported actions, verifies an active connection, and executes requested workflows with the input requirements found during tool discovery.

OriginalShow the original description

Automate Docnify tasks via Rube MCP (Composio). Always search tools first for current schemas.

AI rating90/ 100See how to install

Good for

  • Finding available Docnify actions
  • Checking the Docnify connection before execution
  • Running Docnify tasks with current input requirements

Overview

What it does

This skill lets you ask an AI agent to carry out Docnify operations through Rube MCP. It searches Composio’s tools to find an action that matches your task and identify its required inputs. The workflow checks that the Docnify connection is active, then executes the task using the search results.

When it helps

Use it when you want to explore the operations available in Docnify or delegate a workflow that includes checking the connection. Instead of relying on fixed operation names or arguments, it uses the latest specifications returned by tool discovery. The instructions also cover reusing sessions within a task, running bulk operations, and retrieving results spread across multiple pages.

Example requests

  • “Find the operations available in Docnify and the input fields they require.”
  • “Check the Docnify connection, then carry out the task I specify.”

Notes

Rube MCP and an active Docnify connection are required. Adding Rube MCP itself is described as requiring no API key. If the connection is inactive, set it up using the authentication link returned by the connection management tool. The material does not list individual supported operations, so tool discovery must establish what is possible before execution.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Objective evaluation

AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.

Clear instructionsIs it clear when to use it and what it does?
AGoodThe material explicitly describes finding Docnify operations, checking the connection, and executing tasks.
Concrete stepsAre steps, inputs, outputs, and examples spelled out?
AGoodSearch, connection, and execution call examples specify returned tool identifiers and input schemas.
SafetyAre sending data, deleting files, and running commands disclosed?
BPartly lackingExternal operations and bulk execution are covered, but no procedure checks the effects of those operations.
Easy setupDoes it need few tools or API keys, and are they documented?
AGoodSetup provides the Rube MCP endpoint, authentication link procedure, and steps to confirm an active connection.

The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 21, 2026. Treat it as a guide and read the original before installing.

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Files included (1)

  • SKILL.md2.9 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Docnify Automation via Rube MCP

Automate Docnify operations through Composio's Docnify toolkit via Rube MCP.

Toolkit docs: composio.dev/toolkits/docnify

Prerequisites

  • Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
  • Active Docnify connection via RUBE_MANAGE_CONNECTIONS with toolkit docnify
  • 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 docnify
  3. If connection is not ACTIVE, follow the returned auth link to complete setup
  4. Confirm connection status shows ACTIVE before running any workflows

Tool Discovery

Always discover available tools before executing workflows:

RUBE_SEARCH_TOOLS
queries: [{use_case: "Docnify 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 Docnify task"}]
session: {id: "existing_session_id"}

Step 2: Check Connection

RUBE_MANAGE_CONNECTIONS
toolkits: ["docnify"]
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

OperationApproach
Find toolsRUBE_SEARCH_TOOLS with Docnify-specific use case
ConnectRUBE_MANAGE_CONNECTIONS with toolkit docnify
ExecuteRUBE_MULTI_EXECUTE_TOOL with discovered tool slugs
Bulk opsRUBE_REMOTE_WORKBENCH with run_composio_tool()
Full schemaRUBE_GET_TOOL_SCHEMAS for tools with schemaRef

Powered by Composio

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