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feathery-automation skill

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/feathery-automation

This skill automates Feathery tasks via Rube MCP, always discovering current tool schemas before execution to ensure accurate, up-to-date workflows.

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

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

# Feathery Automation via Rube MCP

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

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

## Prerequisites

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

### Step 2: Check Connection

```
RUBE_MANAGE_CONNECTIONS
toolkits: ["feathery"]
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 Feathery-specific use case |
| Connect | `RUBE_MANAGE_CONNECTIONS` with toolkit `feathery` |
| 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 Feathery tasks using Composio’s Feathery toolkit via Rube MCP. It guides discovery, connection management, and execution of Feathery tools while enforcing schema compliance. The workflow emphasizes calling RUBE_SEARCH_TOOLS first and validating an ACTIVE Feathery connection before running operations.

How this skill works

It first queries RUBE_SEARCH_TOOLS to discover available Feathery tool slugs, input schemas, and recommended execution plans. Next it verifies or establishes a connection with RUBE_MANAGE_CONNECTIONS for the feathery toolkit and ensures the connection is ACTIVE. Finally it runs the selected tools through RUBE_MULTI_EXECUTE_TOOL (or RUBE_REMOTE_WORKBENCH for bulk ops), always supplying schema-compliant arguments, a session_id, and a memory object.

When to use it

Automate form creation, updates, or data workflows in Feathery programmatically
Integrate Feathery tasks into larger AI or CI/CD workflows via Rube MCP
Run bulk or repeatable Feathery operations across environments
When you need reliable schema-driven execution of Composio tools
Before launching production runs that require validated tool schemas

Best practices

Always call RUBE_SEARCH_TOOLS first — tool schemas and slugs can change frequently
Confirm RUBE_MANAGE_CONNECTIONS shows ACTIVE for toolkit feathery before executing any tools
Use exact field names and types returned by search results; never hardcode arguments
Include memory in every RUBE_MULTI_EXECUTE_TOOL call (can be an empty object {})
Reuse session_id within a workflow; generate a new session_id for a new workflow
Watch for pagination tokens in search responses and fetch until complete

Example use cases

Discover available Feathery actions and arguments, then programmatically create forms or components
Validate and refresh Feathery connections before running nightly automation jobs
Execute a batch of Feathery updates using RUBE_REMOTE_WORKBENCH with run_composio_tool()
Build a workflow that searches tools, checks connection status, then runs specific Feathery actions with schema-compliant payloads

FAQ

What is the first action I should always take when using this skill?

Always call RUBE_SEARCH_TOOLS to fetch the current tool slugs, input schemas, and execution guidance before doing anything else.

What if RUBE_MANAGE_CONNECTIONS returns a non-ACTIVE status?

Follow the returned auth link to complete setup and re-check RUBE_MANAGE_CONNECTIONS until the toolkit feathery shows ACTIVE.