weathermap-automation

Overview of weathermap-automation skill

What weathermap-automation is for

weathermap-automation is a Claude skill for running Weathermap operations through Composio’s Rube MCP server. It is not a standalone weather API wrapper; it is an agent workflow pattern that helps Claude discover the current Weathermap tools, verify the user’s connected account, and call the right Rube MCP action with the correct schema.

Use this skill when you want an AI agent to automate Weathermap-related tasks without manually browsing Composio toolkit docs every time.

Best-fit users and workflows

The weathermap-automation skill fits teams already using Claude with MCP and Composio Rube. It is most useful for workflow automation where the available Weathermap tool names or input schemas may change, because the skill explicitly tells the agent to search tools first instead of guessing.

Good fits include:

• Checking available Weathermap operations from an agent session
• Building repeatable Weathermap workflows inside Claude
• Connecting Weathermap actions to broader automation chains
• Reducing schema errors by forcing runtime tool discovery

Key differentiator: search tools before acting

The most important behavior in this skill is the instruction to call RUBE_SEARCH_TOOLS before executing any Weathermap action. That matters because Rube returns current tool slugs, required fields, input schemas, execution plans, and pitfalls. For install decisions, this is the main value over a generic “use Weathermap” prompt: the agent is guided to validate available tools before it calls them.

Adoption requirements and limits

Before installing weathermap-automation, confirm that your client supports MCP and that Rube MCP is available. The skill requires:

• MCP server endpoint: https://rube.app/mcp
• RUBE_SEARCH_TOOLS availability
• Active Weathermap connection through RUBE_MANAGE_CONNECTIONS
• User approval or authentication if Rube returns an auth link

The repository contains a single SKILL.md and no helper scripts, bundled examples, or reference files. That keeps the skill lightweight, but it also means your prompts must provide task context clearly.

How to Use weathermap-automation skill

weathermap-automation install context

Install the skill from the ComposioHQ skill collection:

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

Then add Rube MCP to your client configuration using:

https://rube.app/mcp

After installation, verify that Claude can see RUBE_SEARCH_TOOLS. If the MCP tools do not appear, fix your MCP client configuration before testing the skill. The weathermap-automation install is only useful when the Rube tools are actually callable from the same agent session.

First-run setup checklist

A practical first run should follow this order:

1. Ask Claude to use weathermap-automation.
2. Confirm RUBE_SEARCH_TOOLS responds.
3. Ask Claude to call RUBE_MANAGE_CONNECTIONS with toolkit weathermap.
4. If the connection is not ACTIVE, complete the returned authentication flow.
5. Re-check connection status before requesting any Weathermap operation.
6. Run RUBE_SEARCH_TOOLS for your specific use case.
7. Execute only after the current schema is known.

This sequence prevents the two most common failures: trying to call unavailable tools and sending outdated or incomplete input fields.

Prompt pattern for reliable usage

A weak prompt is:

Use Weathermap to get this done.

A stronger weathermap-automation usage prompt is:

Use the weathermap-automation skill. First call RUBE_SEARCH_TOOLS for the use case “find the available Weathermap operation for [task]”. Check my Weathermap connection with RUBE_MANAGE_CONNECTIONS. If the connection is active, select the best matching tool, explain the required fields, ask me for any missing inputs, then execute using the discovered schema.

This works better because it tells the agent to discover tools, verify auth, avoid guessing fields, and pause for missing information.

Repository files to read first

Start with:

• composio-skills/weathermap-automation/SKILL.md

There are no visible README.md, metadata.json, rules/, resources/, references/, or scripts/ files in this skill directory. That means the core operating instructions are all in SKILL.md. Pay special attention to the sections on prerequisites, setup, tool discovery, and core workflow pattern.

weathermap-automation skill FAQ

Is weathermap-automation for Workflow Automation?

Yes. weathermap-automation for Workflow Automation is the right framing if your goal is to let Claude coordinate Weathermap actions through Composio Rube MCP. It is especially useful when Weathermap is one step inside a larger agent workflow, because Claude can discover the available action schema at runtime and then continue with downstream steps.

How is this better than an ordinary prompt?

An ordinary prompt may make Claude infer tool names or fields from memory. The weathermap-automation skill explicitly instructs the agent to use RUBE_SEARCH_TOOLS first. That reduces brittle automation caused by stale schemas, renamed actions, or missing required fields.

Is this beginner-friendly?

It is beginner-friendly for users who already understand MCP basics. It is not a no-code Weathermap setup guide. You should be comfortable adding an MCP server to your client, checking whether tools are available, and completing a connection authorization flow when prompted.

When should I not use this skill?

Do not use it if you need an offline weather data library, a direct REST API integration, or a self-contained script. Also avoid it if your environment cannot connect to Rube MCP, because the skill depends on RUBE_SEARCH_TOOLS and RUBE_MANAGE_CONNECTIONS.

How to Improve weathermap-automation skill

Improve weathermap-automation inputs

You will get better results by giving the agent the actual task, location or entity details, expected output format, and any constraints before execution. For example:

Use weathermap-automation to find the current available Weathermap tool for [specific task]. I need the result as [format]. If required fields are missing, list them before running the tool. Do not invent schema fields; use only the schema returned by RUBE_SEARCH_TOOLS.

This prevents the agent from turning a vague goal into an incorrect tool call.

Common failure modes to watch

The most likely failure modes are:

• Rube MCP is not configured in the client
• Weathermap connection is not ACTIVE
• Claude skips RUBE_SEARCH_TOOLS
• The prompt does not include enough task detail
• The agent uses an assumed schema instead of the discovered schema

If output looks wrong, ask Claude to show the discovered tool slug, required fields, and the exact missing inputs before it retries.

Iteration after the first output

After the first run, refine the workflow by asking:

• Did the selected tool match the task intent?
• Were any fields inferred without confirmation?
• Did Rube return warnings or known pitfalls?
• Should the result be transformed, summarized, saved, or passed to another tool?

For recurring workflows, save a prompt template that includes connection checking, tool discovery, schema confirmation, execution, and result formatting.

Practical repository improvement ideas

The upstream skill would be stronger with a short README.md, one or two realistic example prompts, and a troubleshooting section for inactive connections or missing MCP tools. A small examples file showing complete RUBE_SEARCH_TOOLS and follow-up execution patterns would also make the weathermap-automation guide easier to adopt without changing the lightweight design.