listclean-automation

Overview of listclean-automation skill

What listclean-automation does

listclean-automation is a Claude skill for automating Listclean operations through Composio’s Rube MCP server. Instead of hard-coding old tool names or parameters, the skill’s central pattern is to search Rube tools first, inspect the current Listclean schema, confirm the Listclean connection, and then run the appropriate workflow.

This is most useful when you want an AI agent to operate Listclean from inside an MCP-enabled client without guessing API fields or manually checking Composio toolkit docs each time.

Best fit for Workflow Automation users

The listclean-automation skill fits teams that already use Claude or another MCP-capable assistant for Workflow Automation and want Listclean actions handled inside the same agent workflow. It is especially relevant if your work involves recurring list hygiene, contact validation, enrichment-adjacent cleanup steps, or operational tasks where the available Listclean actions may change over time.

It is not a standalone Listclean client. The skill assumes Rube MCP is available and that the Listclean toolkit can be connected through Composio.

Key differentiator: schema-first execution

The main value of listclean-automation is its “discover before execute” discipline. The source skill explicitly requires RUBE_SEARCH_TOOLS before running workflows so the agent can retrieve current tool slugs, input schemas, execution plans, and pitfalls.

That matters because MCP tool schemas can change. A generic prompt may ask the assistant to “clean this list,” but this skill pushes the agent to verify what Listclean tools are currently exposed and what inputs they require before taking action.

How to Use listclean-automation skill

listclean-automation install context

Install the skill from the GitHub skill directory with:

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

Then configure Rube MCP in your client by adding:

https://rube.app/mcp

The upstream skill says no API keys are needed for the MCP endpoint itself, but you still need an active Listclean connection through Rube. Confirm that RUBE_SEARCH_TOOLS is available before relying on the skill in a workflow.

Required setup before running Listclean actions

A reliable listclean-automation usage flow starts with connection verification:

1. Call RUBE_SEARCH_TOOLS to confirm Rube MCP responds.
2. Use RUBE_MANAGE_CONNECTIONS or the available Rube connection-management tool for toolkit listclean.
3. If the Listclean connection is not ACTIVE, follow the returned authentication link.
4. Re-check status before asking the agent to perform any Listclean operation.

Do not skip discovery. The skill’s own guidance is to search tools first because that returns the current schemas and known execution pitfalls.

Turn a rough goal into a complete prompt

Weak prompt:

Clean this list with Listclean.

Better prompt for listclean-automation:

Use the listclean-automation skill. First call RUBE_SEARCH_TOOLS for the specific Listclean task and inspect the current schemas. Confirm the Listclean connection is active. Then propose the safest execution plan before running tools. My input is a CSV/contact list with these columns: email, first_name, last_name, company, source. I want invalid or risky entries identified, not silently deleted. Return a summary of tool calls, records affected, and any rows requiring manual review.

This works better because it defines the data shape, desired action, safety preference, and reporting format. It also reinforces the skill’s schema-first behavior.

Files to read before adoption

The repository path is:

composio-skills/listclean-automation/SKILL.md

Read SKILL.md first because this skill has no visible support folders, scripts, metadata file, or separate README in the provided tree. The important sections are Prerequisites, Setup, Tool Discovery, and Core Workflow Pattern. For deeper toolkit behavior, open the linked Composio Listclean docs at composio.dev/toolkits/listclean.

listclean-automation skill FAQ

Is listclean-automation useful without Rube MCP?

No. listclean-automation depends on Rube MCP and requires access to Rube tools such as RUBE_SEARCH_TOOLS and the Rube connection-management flow. If your assistant client cannot add MCP servers or cannot reach https://rube.app/mcp, this skill will not execute as intended.

How is this better than an ordinary prompt?

An ordinary prompt can describe the desired Listclean outcome, but it may guess tool names, use stale parameters, or skip connection checks. The listclean-automation guide is valuable because it instructs the agent to discover the live tool schema first, confirm the Listclean connection, and only then execute a workflow.

That makes it better for operational automation where correctness and current schemas matter more than conversational convenience.

Is this beginner-friendly?

It is beginner-friendly if you are comfortable adding an MCP server and following an auth link. It is less beginner-friendly if you expect a one-click UI. The skill is short and practical, but it assumes you understand that Claude will call MCP tools, not run Listclean directly from the markdown.

When should I not use this skill?

Do not use it when you need an offline-only workflow, when Listclean is not available through your Composio/Rube account, or when your process requires hard-coded deterministic API behavior without runtime tool discovery. Also avoid it for destructive cleanup unless your prompt explicitly asks for previews, summaries, and manual review before deletion or irreversible updates.

How to Improve listclean-automation skill

Improve listclean-automation inputs

The biggest quality gain comes from giving the agent precise task and data context. Include:

• The Listclean outcome you want, such as validation, cleanup, review, or export preparation
• Input format and column names
• Whether records can be modified, flagged, archived, or only reported
• Required output format, such as CSV summary, markdown report, or row-level audit
• Any compliance or retention constraints

For example, say “flag suspicious rows and produce a review table” instead of “clean the list” if you do not want automatic changes.

Reduce common failure modes

Common issues are usually setup-related: Rube MCP is not connected, the Listclean connection is inactive, or the assistant tries to run a tool before discovering the schema. Prevent these by adding this instruction to your prompt:

Before execution, call RUBE_SEARCH_TOOLS for my exact Listclean use case and confirm the Listclean connection is ACTIVE. If the required tool or schema is unclear, stop and ask me before proceeding.

This keeps the skill aligned with its core design.

Iterate after the first output

After the first run, review three things: which tools were selected, which records were affected, and which assumptions the agent made. Then refine the next prompt with examples of acceptable and unacceptable records.

A strong iteration prompt is:

Re-run the Listclean workflow using the same discovered schema, but treat disposable domains as “manual review” instead of “reject.” Keep all original row IDs and return a separate exceptions table.

This turns listclean-automation for Workflow Automation into a safer repeatable process rather than a one-off tool call.

Add local operating rules if needed

If your team uses this skill often, create a local wrapper note or project instruction that defines approved actions, naming conventions, review thresholds, and reporting requirements. Keep the upstream SKILL.md schema-first behavior intact, but add your own guardrails around deletion, suppression, exports, and audit trails. This improves listclean-automation without depending on undocumented Listclean behavior.