A powerful integration for Databowl that enables AI agents to manage records and data workflows through a secure, automated interface.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install databowl
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 databowl 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 Databowl?
Databowl is a comprehensive data management platform focused on lead generation and marketing data optimization. This skill, part of the Openclaw Skills library, utilizes the Membrane CLI to provide a unified interface for interacting with Databowl. It abstracts the complexities of authentication and API management, allowing agents to focus on the core logic of record manipulation.
By leveraging this integration, developers can empower their AI agents to interact with Databowl records dynamically. The skill handles the entire lifecycle of data operations, from discovering available actions using natural language to executing complex API requests through an authenticated proxy, ensuring high security and efficiency in data-driven environments.
Databowl Use Cases
- Automating lead record generation and synchronization from diverse data sources.
- Updating and maintaining marketing data records within the Databowl ecosystem.
- Querying and listing specific record sets for data analysis or reporting tasks.
- Building multi-step automation workflows that trigger actions based on Databowl data changes.
How Databowl Works
- The AI agent initializes the environment by installing the Membrane CLI and authenticating with a specified agent type.
- A connection to the Databowl domain is established, with Membrane managing the server-side OAuth or API key lifecycle.
- The agent polls the connection status to ensure it is ready for operations, prompting the user if manual intervention is required.
- Available actions are discovered by querying intents, which returns a schema of available parameters and expected outputs.
- The agent executes the desired operations (Create, Read, Update, Delete) or uses the authenticated proxy for custom API requests.
Databowl Setup
Install the Membrane CLI globally to enable the connection to Databowl:
npm install -g @membranehq/cli@latest
Authenticate the CLI using openclaw as the client name to optimize for the Openclaw Skills environment:
membrane login --tenant --clientName=openclaw
Ensure a connection to the Databowl platform:
membrane connection ensure "https://www.databowl.com/" --json
Databowl Data Schema & Taxonomy
The skill organizes data around the central concept of Records. Below is the metadata taxonomy for interacting with Databowl via Openclaw Skills:
| Component | Type | Description |
|---|---|---|
| Records | Object | The primary data entity in Databowl supporting CRUD operations. |
| Connection ID | UUID | A unique identifier for the authenticated session with Databowl. |
| Actions | Schema | Dynamic endpoints discovered via natural language intent searching. |
| Proxy Request | HTTP | A passthrough mechanism for raw API access with automatic auth header injection. |
Databowl Advanced Features
- Natural language action discovery for finding specific data management tools without browsing documentation.
- Automatic credential refresh and server-side secret management to keep tokens secure.
- Machine-readable JSON output for all commands, perfect for programmatic consumption by Openclaw Skills.
- Support for authenticated proxying to handle custom Databowl API endpoints not covered by standard actions.
SKILL.md
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