A comprehensive integration for managing serverless stream and batch data processing jobs via an AI-enhanced interface.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install google-cloud-dataflow
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 google-cloud-dataflow 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 Google Cloud Dataflow?
The Google Cloud Dataflow skill for Openclaw Skills enables developers to interact with Google's fully managed, serverless data processing service. This integration simplifies the complexities of developing and executing data pipelines for ETL, real-time analytics, and large-scale data integration. By leveraging Openclaw Skills, technical teams can bypass the manual overhead of authentication and credential management, focusing instead on the logic of their data processing workflows.
Built on top of the Membrane framework, this skill provides a secure and high-level interface for job management. It allows AI agents to discover actions dynamically and execute them with precision, ensuring that your data infrastructure remains agile and automated.
Google Cloud Dataflow Use Cases
- Orchestrating serverless stream and batch data processing jobs.
- Automating ETL pipelines and complex data integration workflows.
- Monitoring job status and managing templates programmatically.
- Real-time analytics pipeline management through AI-driven automation.
- Executing custom data processing tasks using Openclaw Skills and the built-in proxy.
How Google Cloud Dataflow Works
- Install the CLI tool to provide a bridge between your local environment and the Google Cloud Dataflow API.
- Authenticate using the login command to establish a secure tenant session.
- Ensure a connection is active by providing the Google Cloud Dataflow service URL.
- Search for specific actions using natural language intents to find the right job or template management tools.
- Run the selected actions or perform direct proxy requests for advanced API operations.
Google Cloud Dataflow Setup
To get started, install the required CLI using npm:
npm install -g @membranehq/cli@latest
Next, log in and specify your agent type to optimize the tooling for Openclaw Skills:
membrane login --tenant --clientName=openclaw
Finally, establish a connection to the Google Cloud Dataflow service:
membrane connection ensure "https://cloud.google.com/dataflow/" --json
Google Cloud Dataflow Data Schema & Taxonomy
The skill organizes its data and interactions around the core Google Cloud Dataflow resource model. The following entities are primarily managed:
| Resource | Description |
|---|---|
| Job | The individual execution of a data pipeline |
| Template | Reusable pipeline definitions for batch or stream processing |
| Location | The regional endpoint where data processing occurs |
All actions return structured JSON objects containing metadata such as id, inputSchema, and outputSchema for easy parsing.
Google Cloud Dataflow Advanced Features
- Seamless credential lifecycle management and transparent token refreshes provided by Openclaw Skills.
- Natural language discovery for API actions using intent-based search.
- Secure proxy request system for accessing any Google Cloud Dataflow API endpoint not covered by pre-built actions.
- Support for long-polling connection states to handle asynchronous authentication flows.
- Agent-specific tool adjustments to ensure compatibility with various AI agent architectures.
SKILL.md
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