refiner-automation

Overview of refiner-automation skill

What refiner-automation does

refiner-automation is a Claude skill for running Refiner operations through Composio’s Rube MCP server. Its core value is not a fixed set of hardcoded actions; it teaches the agent to discover the current Refiner tool schemas first, verify the Refiner connection, and then execute the available workflow through Rube.

Use this skill when you want an AI agent to automate Refiner-related work without guessing tool names, parameters, or authentication state.

Best fit for Workflow Automation users

The refiner-automation skill is best for teams already using Refiner and willing to connect it through Rube MCP. It fits workflow automation tasks where the agent needs to inspect available Refiner actions at runtime, then act through the official Composio toolkit.

It is especially useful if your Refiner workflows change over time, because the skill emphasizes RUBE_SEARCH_TOOLS before execution instead of relying on stale examples.

Main differentiator

The important behavior is tool discovery before action. The skill instructs the agent to call RUBE_SEARCH_TOOLS for the specific Refiner task, then use RUBE_MANAGE_CONNECTIONS to confirm the refiner toolkit is active. That reduces failures caused by outdated schemas, missing fields, or disconnected accounts.

What to know before installing

This is a focused connector skill, not a complete Refiner playbook. The repository contains a single SKILL.md and no extra scripts, references, rules, or metadata files. Install it if you need a lightweight operational pattern for Rube MCP and Refiner; skip it if you need rich business-process templates, custom validation logic, or offline automation.

How to Use refiner-automation skill

refiner-automation install and setup context

Install the skill in a compatible skills environment, for example:

npx skills add ComposioHQ/awesome-claude-skills --skill refiner-automation

Then configure Rube MCP in your AI client by adding:

https://rube.app/mcp

The skill requires the Rube MCP tools to be available, especially RUBE_SEARCH_TOOLS and RUBE_MANAGE_CONNECTIONS. After MCP is connected, the agent should call RUBE_MANAGE_CONNECTIONS with toolkit refiner. If the connection is not ACTIVE, complete the returned authentication flow before asking the agent to run any Refiner operation.

Inputs the skill needs from you

A weak request is:

“Automate something in Refiner.”

A stronger request gives the agent a concrete use case, target object, constraints, and success criteria:

“Use refiner-automation to check which Refiner tools are available for managing survey responses. First discover current schemas with RUBE_SEARCH_TOOLS, confirm the refiner connection is active, then prepare an execution plan before making changes. Do not run destructive actions without asking me.”

Useful inputs include:

• The exact Refiner task you want automated
• Whether the agent may read only, create records, update records, or delete data
• IDs, names, filters, dates, or workspace context when relevant
• Whether you want a plan first or immediate execution
• Any fields that must not be modified

Practical usage workflow

Start with the repository file composio-skills/refiner-automation/SKILL.md. It contains the operational sequence the agent should follow:

1. Call RUBE_SEARCH_TOOLS with your specific Refiner use case.
2. Review returned tool slugs, schemas, required fields, and pitfalls.
3. Check the Refiner connection with RUBE_MANAGE_CONNECTIONS.
4. Confirm the connection is ACTIVE.
5. Execute only against the current schema returned by Rube.
6. Report what was done, what failed, and what requires user confirmation.

For safer refiner-automation usage, ask the agent to show the discovered tool schema and proposed parameters before executing changes.

Prompt pattern that works well

Use prompts that force discovery and confirmation:

“Invoke the refiner-automation skill. My goal is to [task]. First run RUBE_SEARCH_TOOLS for this exact use case and summarize the available Refiner tools. Then check RUBE_MANAGE_CONNECTIONS for toolkit refiner. If active, propose the execution parameters. Wait for approval before making changes.”

This pattern improves results because the skill depends on live MCP schemas, not static documentation.

refiner-automation skill FAQ

Is refiner-automation a full Refiner integration?

No. The refiner-automation skill is an agent instruction layer for using Composio’s Refiner toolkit through Rube MCP. The actual available operations come from the live Rube tool discovery response, so capabilities may depend on the current Composio toolkit and your connected Refiner account.

How is this better than an ordinary prompt?

A generic prompt may ask the model to guess API behavior. This skill tells the agent to discover available Refiner tools first, check connection status, and use current schemas. That makes it more reliable for Workflow Automation where field names, required parameters, and supported actions matter.

Is this suitable for beginners?

Yes, if you are comfortable connecting an MCP server and following an authentication link. Beginners should ask for a dry-run plan before execution and should avoid broad write permissions until they understand what the discovered Refiner tools can do.

When should I not use it?

Do not use refiner-automation if you do not have a Refiner account, cannot connect Rube MCP, need a standalone script, or require audited production automation with custom approval gates. The skill helps an AI agent operate tools; it does not replace access control, review policy, or business-specific validation.

How to Improve refiner-automation skill

Give refiner-automation clearer task boundaries

The most common failure mode is an underspecified goal. Improve output quality by defining scope before the agent searches tools:

• “Read only” versus “create/update”
• Which Refiner workspace, project, survey, segment, or record set is in scope
• Whether bulk actions are allowed
• What should happen if required fields are missing

This helps the agent choose better search queries and avoid unsafe execution.

Ask for schema-grounded plans

Because the skill’s core rule is “search tools first,” make the first deliverable a schema-grounded plan. Ask the agent to list the tool slug, required fields, optional fields, assumptions, and proposed parameters. This catches mismatches before any Refiner action runs.

Example:

“Before execution, show the tool returned by RUBE_SEARCH_TOOLS, the exact input object you plan to send, and any missing values you need from me.”

Iterate after the first result

After the first run, improve the next prompt with the actual response: failed fields, unavailable tools, authentication state, rate or permission issues, and partial results. The skill becomes more useful when you feed back the live Rube errors instead of asking the agent to retry blindly.

A strong follow-up is:

“The previous call failed because [error]. Re-run tool discovery for this narrower use case, compare the required schema with our last parameters, and propose a corrected call.”

Add local operating rules if needed

The upstream skill is intentionally minimal. If your team uses Refiner in production, consider adding your own wrapper instructions outside the repository: approval before destructive changes, naming conventions, required audit summaries, environment labels, and data-handling limits. These rules make refiner-automation safer without changing its core discovery-first workflow.