re-amaze-automation
by ComposioHQre-amaze-automation helps Claude automate Re:amaze operations through Rube MCP by discovering current tools, checking the re_amaze connection, and using live schemas before execution.
This skill scores 68/100, which makes it acceptable but limited for directory listing. Directory users can understand that it is a Rube MCP wrapper workflow for Re Amaze and can install it when they need agents to discover and run current Re Amaze tools, but they should expect a lightweight guide rather than a complete, example-rich automation package.
- Clear trigger and scope: it is explicitly for automating Re Amaze operations through Composio/Rube MCP.
- Includes concrete prerequisites and setup checks, including RUBE_SEARCH_TOOLS availability and an ACTIVE re_amaze connection via RUBE_MANAGE_CONNECTIONS.
- Emphasizes dynamic tool discovery before execution, which should reduce stale-schema errors for agents using current Composio tool definitions.
- No support files, README, install command, or local scripts are provided; adoption depends on already knowing how to add and use the Rube MCP server.
- Workflow guidance appears mostly generic and schema-discovery-driven, so users looking for specific Re Amaze automations or edge-case handling may still need to infer details at runtime.
Overview of re-amaze-automation skill
What re-amaze-automation does
re-amaze-automation is a Claude skill for automating Re:amaze customer support operations through Composio’s Rube MCP server. Instead of assuming fixed API schemas, the skill instructs the agent to call RUBE_SEARCH_TOOLS first, discover the current Re:amaze tool set, verify the re_amaze connection, and then execute the appropriate workflow.
This makes the re-amaze-automation skill most useful when you want an AI agent to work with live Re:amaze data through approved MCP tools rather than draft generic support text.
Best-fit users and workflows
Use re-amaze-automation for Workflow Automation when you need Claude to help with operational Re:amaze tasks such as finding conversations, preparing support actions, routing work, updating records, or coordinating customer-service workflows through available Composio tools.
It is a good fit for:
- Support operations teams using Re:amaze.
- Builders configuring Claude with MCP-based SaaS automation.
- Teams that need tool discovery before execution because schemas may change.
- Users who want controlled automation rather than manual copy-paste between systems.
Key differentiator: schema discovery first
The strongest design choice in re-amaze-automation is its “search tools first” pattern. The skill does not hard-code Re:amaze actions. It tells the agent to query RUBE_SEARCH_TOOLS for the specific use case, then use the returned tool slugs, input schemas, execution plan, and pitfalls.
That matters because MCP tool availability, required fields, and authentication state can differ by workspace. This skill reduces failed calls caused by outdated assumptions.
Adoption considerations
The skill depends on Rube MCP and an active Re:amaze connection. It is not a standalone script, browser extension, or Re:amaze API wrapper. If your Claude environment cannot use MCP tools, or if you cannot authorize the re_amaze toolkit through RUBE_MANAGE_CONNECTIONS, the skill will not be able to execute live automation.
How to Use re-amaze-automation skill
re-amaze-automation install context
Install the skill from the Composio skills repository if your Claude-compatible environment supports skill installation:
npx skills add ComposioHQ/awesome-claude-skills --skill re-amaze-automation
Then configure Rube MCP in your client by adding:
https://rube.app/mcp
Before expecting the skill to work, confirm that RUBE_SEARCH_TOOLS is available. Next, use RUBE_MANAGE_CONNECTIONS with toolkit re_amaze and complete the returned authorization flow if the connection is not ACTIVE.
Inputs the skill needs from you
For reliable re-amaze-automation usage, provide the agent with the business goal, relevant identifiers, and safe execution boundaries. A weak request is:
“Update my Re:amaze conversations.”
A stronger prompt is:
“Use re-amaze-automation to find open Re:amaze conversations tagged billing from the last 48 hours. First discover current tools with RUBE_SEARCH_TOOLS, verify the re_amaze connection, then summarize matching conversations. Do not modify conversations until I approve the proposed actions.”
This works better because it defines the task, filter criteria, required discovery step, connection check, and approval boundary.
Recommended workflow
A practical re-amaze-automation guide should follow this sequence:
- Ask the agent to call
RUBE_SEARCH_TOOLSfor the exact Re:amaze task. - Review the returned tool schemas and required fields.
- Check the
re_amazeconnection withRUBE_MANAGE_CONNECTIONS. - Run read-only discovery before write actions when possible.
- Ask for a proposed execution plan if the workflow changes customer data.
- Execute the selected tool calls using the discovered schema, not guessed fields.
This is especially important for actions such as updating conversations, changing assignments, or applying tags, where an incorrect target can affect customer-facing support work.
Repository files to read first
The upstream skill is compact and centered in SKILL.md. Read that file before installation to confirm the required MCP server, connection flow, and core workflow pattern. There are no extra scripts, rule folders, or reference files in the current skill directory, so the main value is the prompt-level operating procedure rather than bundled automation code.
re-amaze-automation skill FAQ
Is re-amaze-automation a Re:amaze API client?
No. re-amaze-automation is a Claude skill that guides an agent to use Composio’s Re:amaze toolkit through Rube MCP. It does not replace the Re:amaze API, and it does not include standalone code for direct API calls.
How is it better than an ordinary prompt?
An ordinary prompt may tell Claude to “use Re:amaze,” but it may not force tool discovery or connection validation. The re-amaze-automation skill encodes the safer sequence: discover current tools, check the re_amaze connection, inspect schemas, then execute. That structure reduces guesswork and failed MCP calls.
Is it beginner-friendly?
It is beginner-friendly if you already understand MCP basics and can add the Rube MCP endpoint to your client. Complete beginners may need help confirming that RUBE_SEARCH_TOOLS and RUBE_MANAGE_CONNECTIONS are available before using the skill productively.
When should I not use this skill?
Do not use this skill if you only need static support copy, have no Re:amaze account, cannot authorize the re_amaze toolkit, or need a fully custom integration with deterministic code and tests. For regulated or high-risk support operations, keep human approval before any write action.
How to Improve re-amaze-automation skill
Improve re-amaze-automation prompts
The biggest quality gain comes from giving the skill precise operational context. Include:
- The Re:amaze object type you care about, such as conversations, customers, tags, or assignments.
- Filters such as date range, status, inbox, tag, assignee, or priority.
- Whether the first step must be read-only.
- What counts as success.
- Which actions require approval.
Example:
“Find unresolved VIP customer conversations older than 24 hours, group them by likely issue type, and propose next actions. Use tool discovery first and do not update Re:amaze until I approve.”
Avoid common failure modes
Common problems include skipping RUBE_SEARCH_TOOLS, assuming outdated input fields, running write actions before confirming targets, and asking for broad automation without filters. If the agent appears uncertain, redirect it to search for current tools again using the exact use case.
For sensitive workflows, ask the agent to show the tool name, required inputs, and planned records before execution.
Iterate after the first output
After the first result, refine the workflow with operational feedback. For example, change “all open conversations” to “open conversations in the support inbox excluding spam and already escalated tickets.” Ask the agent to preserve the discovered schema and reuse the same session where appropriate, but re-run discovery when the task changes materially.
Extend the skill safely
If you adapt re-amaze-automation for your team, add internal conventions outside the upstream file: approved tag names, escalation rules, inbox ownership, write-action approval policy, and examples of successful prompts. Keep the core discovery-first behavior intact, because that is what makes the skill resilient across changing Rube MCP schemas.