A professional-grade interface for executing machine learning model inference and receiving instant, data-driven predictions.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ml-prediction-service
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 ml-prediction-service 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 Machine Learning Prediction Service?
The Machine Learning Prediction Service is designed to bridge the gap between trained models and production environments. As a versatile entry in the Openclaw Skills directory, it provides a standardized API for running inference on demand, allowing developers to bypass the complexities of hosting and scaling their own model servers. It is built for speed, reliability, and ease of integration into larger automated workflows.
This skill enables developers to leverage the power of Openclaw Skills to perform sophisticated data analysis without managing heavy backend infrastructure. By focusing on a simple JSON-based communication protocol, it ensures that your AI agents or applications can query predictions with minimal overhead, paying only for the compute used.
Machine Learning Prediction Service Use Cases
- Real-time fraud detection for securing financial transactions and identifying suspicious activity.
- Personalized recommendation engines for e-commerce and streaming platforms within the Openclaw Skills framework.
- Predictive maintenance and demand forecasting for logistics and supply chain optimization.
- Automated classification of data points in high-volume research and analytical projects.
How Machine Learning Prediction Service Works
- The user identifies the specific model to be used by its unique model_id.
- Input data containing the necessary features is sent to the service in a structured JSON format.
- The system processes the request through the hosted inference engine, utilizing optimized hardware.
- A transparent micropayment of 0.001 USDT is handled automatically through the SkillPay.me integration.
- The service returns a JSON response containing the prediction result, a confidence score, and a success status.
Machine Learning Prediction Service Setup
To get started with this service in your environment, ensure your API keys are configured correctly within your Openclaw Skills manager. Use the following bash command to test the integration:
# Trigger a prediction request using the command line interface
openclaw call ml-prediction --model "rf_12345" --features '{"f1": 0.5, "f2": 1.2}'
Ensure your SkillPay.me wallet is funded to cover the 0.001 USDT per-call fee.
Machine Learning Prediction Service Data Schema & Taxonomy
The service utilizes a strict JSON schema for predictable integration. Below are the primary data fields:
| Attribute | Type | Purpose |
|---|---|---|
| model_id | string | The unique identifier for the pre-trained model instance. |
| input_data | object | A map of feature names to numeric or categorical values. |
| prediction | float | The numeric result or classification index generated by the model. |
| confidence | string | The statistical certainty of the prediction (e.g., "91%"). |
| success | boolean | Indicates if the inference lifecycle completed without errors. |
Machine Learning Prediction Service Advanced Features
- Seamless financial integration with SkillPay.me for automated per-request billing.
- High-performance inference engine capable of sub-second response times for Openclaw Skills users.
- Support for scalable model hosting to accommodate fluctuating traffic demands.
- Easy-to-parse metadata and confidence scoring for building robust conditional logic in AI agents.
SKILL.md
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