A powerful integration for AI agents to interact with Totango customer success data, handle authentication, and automate account management tasks.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install totango
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install totango using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Totango Integration for AI Agents?
This Totango integration is one of the most effective Openclaw Skills for developers looking to bridge the gap between AI agents and customer success platforms. It provides a robust interface for monitoring customer health, identifying at-risk accounts, and automating engagement strategies directly through an AI-driven workflow.
By leveraging the Membrane framework, this skill removes the complexity of manual authentication. It handles credential refreshes and secure connectivity server-side, allowing your AI agent to focus on executing logic and managing records rather than managing API keys. This ensures a more secure and efficient developer experience when building customer-centric automations.
Totango Integration for AI Agents Use Cases
- Automatically identifying at-risk customer accounts based on health scores.
- Updating account profiles and user records through natural language commands.
- Orchestrating automated engagement strategies to improve customer retention.
- Fetching real-time customer health data for internal business intelligence reports.
- Managing user profiles and tracking customer success milestones without manual data entry.
How Totango Integration for AI Agents Works
- The AI agent initiates a connection to the Totango API using Openclaw Skills via the Membrane CLI.
- Membrane handles the OAuth or API key handshake, providing a secure connection ID.
- The agent uses natural language intent to search for specific Totango actions (e.g., fetching an account profile).
- Actions are executed with JSON parameters, with Membrane managing all authentication headers and token refreshes.
- For custom needs, the agent sends proxy requests through Membrane to reach specific Totango endpoints while maintaining security.
Totango Integration for AI Agents Setup
To get started with this integration among your Openclaw Skills, first install the Membrane CLI:
npm install -g @membranehq/cli@latest
Next, authenticate your agent (specify your agent type like openclaw or claude):
membrane login --tenant --clientName=openclaw
Finally, create a connection to the Totango instance:
membrane connection ensure "https://totango.com" --json
Totango Integration for AI Agents Data Schema & Taxonomy
The Totango skill organizes data around core customer success entities. The following table describes the primary objects managed:
| Object | Description |
|---|---|
| Account | High-level customer records containing health scores and contract details. |
| Account Profile | Metadata and specific attributes belonging to a customer account. |
| User | Individual contacts associated with specific accounts. |
| User Profile | Detailed engagement data and activity logs for specific users. |
All interactions return structured JSON output, including inputSchema and outputSchema for every action to ensure predictable agent behavior.
Totango Integration for AI Agents Advanced Features
- Natural Language Intent Search: Find the exact API capability needed by describing the goal in plain English.
- Automatic Credential Refresh: Zero-maintenance authentication that works in both interactive and headless environments.
- Intelligent Proxying: Send raw requests to any Totango endpoint while the skill automatically injects base URLs and security headers.
- Long-polling Connection Status: Built-in support for waiting on user actions or background build processes using the
--waitflag. - Machine-readable Output: Standardized JSON responses across all commands for seamless parsing by Openclaw Skills.
SKILL.md
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