goody-automation
by ComposioHQgoody-automation helps agents run Goody workflow automation through Composio's Goody toolkit via Rube MCP. Use it to install the skill, connect Rube, authorize Goody, discover current tool schemas first, and execute with less guesswork.
This skill scores 66/100, which means it is acceptable for directory listing but should be presented as a lightweight Rube/Goody connector guide rather than a fully developed automation playbook. Directory users get enough information to understand when to install it and how an agent should start, but the repository evidence shows limited concrete workflow depth.
- Frontmatter clearly declares the triggerable purpose: automating Goody tasks through Rube MCP, with `mcp: [rube]` required.
- Setup and prerequisites are explicit, including adding `https://rube.app/mcp`, checking `RUBE_SEARCH_TOOLS`, and managing an active Goody connection with `RUBE_MANAGE_CONNECTIONS`.
- The skill gives agents an operational pattern to reduce schema guesswork by requiring `RUBE_SEARCH_TOOLS` before executing workflows.
- No support files, scripts, or reference examples are included beyond SKILL.md, so the skill depends heavily on live Rube tool discovery rather than documented task-specific recipes.
- The workflow guidance is generic for “Goody operations” and does not show concrete Goody use cases or completed end-to-end examples.
Overview of goody-automation skill
What goody-automation is for
The goody-automation skill helps an AI agent automate Goody operations through Composio’s Goody toolkit using Rube MCP. It is built for workflows where the agent must discover the current Goody tool schema, confirm the user’s Goody connection, and then execute the requested operation with the correct Rube tool call rather than guessing parameters from memory.
Best-fit users and jobs
Use this skill if you already work with Claude or another MCP-capable assistant and want it to handle Goody-related workflow automation through Composio. It is most useful for users who need repeatable Goody actions but do not want to manually inspect the Goody toolkit documentation before every request. The real job-to-be-done is not “write a generic automation plan”; it is “query the live Rube MCP tool registry, validate connection state, and run the right Goody operation with the latest schema.”
What makes this skill different
The key differentiator is its insistence on live tool discovery. The upstream SKILL.md explicitly says to call RUBE_SEARCH_TOOLS first because Goody tool names, fields, and execution plans may change. That makes the goody-automation skill better suited to live MCP execution than a static prompt that assumes fixed API fields.
Adoption considerations
This is a focused, single-file skill. There are no bundled scripts, reference examples, or local test harnesses in the repository path, so the value depends on whether your client has Rube MCP enabled and whether your Goody connection is active. If you cannot use MCP tools in your environment, this skill will not deliver its intended automation benefits.
How to Use goody-automation skill
goody-automation install context
Install from the Composio skills repository with your skill manager, for example:
npx skills add ComposioHQ/awesome-claude-skills --skill goody-automation
The skill itself requires Rube MCP, not a local package runtime. Add https://rube.app/mcp as an MCP server in your compatible client, then verify that RUBE_SEARCH_TOOLS is available. Next, use RUBE_MANAGE_CONNECTIONS with toolkit goody and complete the returned authorization flow if the connection is not active.
Inputs the skill needs
For reliable goody-automation usage, give the agent the business goal, relevant recipient or item details, timing constraints, and any policy limits before it searches tools. Avoid saying only “do the Goody task.” A stronger request is:
“Using goody-automation, check my Goody connection, discover the current Goody tools, and prepare the correct workflow to send a thank-you gift to this recipient. Ask me before final execution if a price, address, message, or approval field is required.”
This works better because it gives the agent permission to discover schemas first, clarifies the desired outcome, and defines when it should pause instead of inventing missing values.
Practical workflow to follow
Start by reading composio-skills/goody-automation/SKILL.md; it is the only source file surfaced for this skill and contains the operational sequence. In practice, the agent should:
- Call
RUBE_SEARCH_TOOLSfor the specific Goody task. - Reuse the returned session ID for follow-up tool calls.
- Check the
goodyconnection withRUBE_MANAGE_CONNECTIONS. - Follow the discovered schema exactly.
- Ask for missing required fields before execution.
- Report which tool was used and summarize the result.
This sequence is the main reason to install the skill instead of relying on an ordinary prompt.
Prompt pattern for better results
Phrase requests around the specific Goody outcome, not the underlying API. For example:
“Use the goody-automation skill for Workflow Automation. First discover current Goody tools through Rube MCP, then help me create a Goody workflow for [goal]. Here are the known details: [recipient/company/occasion/budget/message/deadline]. If the live schema requires anything else, ask before calling the execution tool.”
This prompt helps the agent avoid two common errors: using stale tool fields and proceeding without an active Goody connection.
goody-automation skill FAQ
Do I need Composio or Rube MCP?
Yes. The goody-automation skill depends on Rube MCP and the Composio Goody toolkit. The prerequisite tools named in the source are RUBE_SEARCH_TOOLS and RUBE_MANAGE_CONNECTIONS. Without those available in your client, the skill becomes only a procedural note rather than an executable automation layer.
Is this better than a normal prompt?
For live Goody automation, yes. A normal prompt may describe what to do, but it cannot reliably know the current Composio tool slug, required fields, or connection status. This skill directs the agent to discover tools first, confirm the active Goody connection, and then execute based on the returned schema.
Is goody-automation beginner friendly?
It is beginner friendly if your MCP client is already configured, because the workflow is simple: connect Rube, authorize Goody, search tools, then execute. It is less beginner friendly if you have never configured MCP servers, because the repository does not include screenshots, scripts, or a troubleshooting guide beyond the core setup steps.
When should I not use this skill?
Do not use it for non-Goody workflows, offline planning, or environments where MCP tool calls are disabled. Also avoid it when you need a fully documented automation package with examples, tests, and helper scripts. This is a compact execution guide for Goody through Rube MCP, not a broad integration framework.
How to Improve goody-automation skill
Improve goody-automation inputs
The fastest way to improve goody-automation results is to provide complete operational context before the tool search. Include the desired Goody action, recipient or object details, deadline, budget or approval limits, message text, and whether the agent may execute immediately or must draft first. The live schema may still require additional fields, but richer inputs reduce back-and-forth.
Prevent common failure modes
The main failure mode is skipping RUBE_SEARCH_TOOLS and assuming old schemas. A second common issue is attempting execution before the goody connection is active. A third is giving the agent a vague goal with no constraints, which can lead to incomplete tool calls or unnecessary clarification. Make “search tools first” and “confirm connection before execution” explicit in high-stakes prompts.
Iterate after the first output
After the first run, ask the agent to show the discovered tool name, required fields, missing fields, and planned execution step before it acts. If the output is too generic, respond with concrete corrections: “Use the same Rube session, narrow the search to sending a Goody gift, and do not execute until I approve the final message and cost-related fields.”
Repository improvements worth adding
For maintainers, the skill would be stronger with a short README.md, one or two realistic Goody workflow examples, and a troubleshooting section for inactive connections or missing MCP tools. Example prompts for approval-gated execution would also help users understand safe goody-automation usage without reading the entire Rube MCP documentation first.