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fireberry-automation skill

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/fireberry-automation

This skill automates Fireberry tasks via Composio's Rube MCP, ensuring real-time tool discovery, validated connections, and schema-aware executions.

npx playbooks add skill composiohq/awesome-claude-skills --skill fireberry-automation

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---
name: fireberry-automation
description: "Automate Fireberry tasks via Rube MCP (Composio). Always search tools first for current schemas."
requires:
  mcp: [rube]
---

# Fireberry Automation via Rube MCP

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

**Toolkit docs**: [composio.dev/toolkits/fireberry](https://composio.dev/toolkits/fireberry)

## Prerequisites

- Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
- Active Fireberry connection via `RUBE_MANAGE_CONNECTIONS` with toolkit `fireberry`
- 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 `fireberry`
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: "Fireberry 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 Fireberry task"}]
session: {id: "existing_session_id"}
```

### Step 2: Check Connection

```
RUBE_MANAGE_CONNECTIONS
toolkits: ["fireberry"]
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

| Operation | Approach |
|-----------|----------|
| Find tools | `RUBE_SEARCH_TOOLS` with Fireberry-specific use case |
| Connect | `RUBE_MANAGE_CONNECTIONS` with toolkit `fireberry` |
| Execute | `RUBE_MULTI_EXECUTE_TOOL` with discovered tool slugs |
| Bulk ops | `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` |
| Full schema | `RUBE_GET_TOOL_SCHEMAS` for tools with `schemaRef` |

---
*Powered by [Composio](https://composio.dev)*

Overview

This skill automates Fireberry tasks through Rube MCP using Composio's Fireberry toolkit. It standardizes discovery, connection validation, and execution patterns so agents can run Fireberry operations reliably. The skill enforces runtime checks like searching for current tool schemas and confirming an active connection before execution.

How this skill works

Before any operation, the skill calls RUBE_SEARCH_TOOLS to retrieve available tool slugs, input schemas, and execution recommendations. It then verifies the Fireberry connection via RUBE_MANAGE_CONNECTIONS and runs tools through RUBE_MULTI_EXECUTE_TOOL or bulk jobs with RUBE_REMOTE_WORKBENCH, always supplying a session_id and memory parameter. The skill expects schema-compliant arguments returned by the search step and handles pagination and session reuse across workflows.

When to use it

Automate repetitive Fireberry workflows (jobs, queries, or deployments)
Integrate Fireberry operations into multi-step agent pipelines
Run bulk or batch Fireberry tasks via the remote workbench
When you need dynamic discovery of available Fireberry tools and schemas
Before any execution when tool schemas may change frequently

Best practices

Always call RUBE_SEARCH_TOOLS first; never hardcode tool slugs or argument structures
Verify connection status with RUBE_MANAGE_CONNECTIONS and complete auth flow until ACTIVE
Pass exact field names and types from the search results to ensure schema compliance
Include a memory object (can be {}) in all RUBE_MULTI_EXECUTE_TOOL calls
Reuse session_id for a single workflow; generate new session IDs for separate workflows
Handle pagination tokens in responses and iterate until you’ve fetched all results

Example use cases

Find available Fireberry tools for a specific use case and run a discovered tool with validated inputs
Connect and authenticate an agent to a Fireberry toolkit, then execute a deployment workflow
Execute bulk Fireberry tasks with RUBE_REMOTE_WORKBENCH using run_composio_tool() for scalable operations
Integrate Fireberry operations into a larger automation pipeline that needs dynamic tool discovery and schema validation
Perform data migration or mass updates in Fireberry by paging through results and executing batched tool calls

FAQ

Why must I call RUBE_SEARCH_TOOLS first?

Tool schemas and available tool slugs can change. RUBE_SEARCH_TOOLS returns up-to-date slugs, input schemas, and execution tips required for safe calls.

What if the Fireberry connection is not ACTIVE?

Use RUBE_MANAGE_CONNECTIONS to get the auth link and complete the authorization flow. Confirm the connection shows ACTIVE before executing tools.