Andrii Bidochko

• Updated: March 18, 2026
• 7 min read

Getting Started with the OpenClaw Rating API: A Step‑by‑Step Integration Guide

Answer: The OpenClaw Rating API enables developers to programmatically submit content for rating, retrieve a confidence‑scored assessment, and integrate the results directly into UBOS‑hosted applications, allowing real‑time moderation, recommendation, or quality scoring.

Introduction

Whether you’re building a social network, a marketplace, or an AI‑driven content hub, reliable content rating is a cornerstone of trust. The OpenClaw Rating API offers a simple REST interface that evaluates text, images, or mixed media and returns a structured score. This guide walks you through every step—from installing the client library to deploying a fully‑functional rating service on the UBOS homepage—so you can start leveraging OpenClaw in minutes.

Prerequisites

• Basic knowledge of JavaScript/Node.js or Python (examples are provided for both).
• A UBOS account with access to the UBOS platform overview.
• API key for OpenClaw (obtainable from the OpenClaw dashboard).
• Git installed locally and familiarity with Workflow automation studio for CI/CD pipelines.

1. Setting Up the OpenClaw API Client

OpenClaw provides official SDKs for Node.js and Python. Choose the language that matches your UBOS web app.

Node.js Installation

npm install @openclaw/rating-sdk --save

Python Installation

pip install openclaw-rating-sdk

After installing the SDK, create a dedicated openclaw-client module inside your UBOS project. This isolates configuration and makes future updates painless.

2. Authentication

OpenClaw uses API‑key authentication via an HTTP Authorization header. Store the key securely using UBOS’s secret manager.

Storing the API Key in UBOS

1. Navigate to the UBOS partner program dashboard.
2. Select Secrets → Add New Secret.
3. Enter OPENCLAW_API_KEY as the name and paste your key.
4. Save the secret; it will be injected as an environment variable at runtime.

Node.js Example

const { OpenClawClient } = require('@openclaw/rating-sdk');

const client = new OpenClawClient({
  apiKey: process.env.OPENCLAW_API_KEY,
  endpoint: 'https://api.openclaw.io/v1'
});

Python Example

from openclaw_rating_sdk import OpenClawClient
import os

client = OpenClawClient(
    api_key=os.getenv('OPENCLAW_API_KEY'),
    endpoint='https://api.openclaw.io/v1'
)

3. Making Rating Requests (code examples)

Once authenticated, you can submit content for rating. The API accepts JSON payloads with type (e.g., text, image) and the actual content.

Node.js – Rating a Text Snippet

async function rateText(text) {
  try {
    const response = await client.rate({
      type: 'text',
      content: text
    });
    console.log('Score:', response.score);
    console.log('Confidence:', response.confidence);
  } catch (err) {
    console.error('Rating error:', err);
  }
}

rateText('This is a sample post that needs moderation.');

Python – Rating an Image URL

def rate_image(image_url):
    try:
        response = client.rate({
            'type': 'image',
            'content': image_url
        })
        print('Score:', response['score'])
        print('Confidence:', response['confidence'])
    except Exception as e:
        print('Rating error:', e)

rate_image('https://example.com/photo.jpg')

Both snippets return a JSON object with score (0‑100) and confidence (0‑1). Use these values to decide whether to approve, flag, or request manual review.

4. Error Handling Strategies

Robust error handling prevents downtime and ensures a graceful user experience. OpenClaw can return HTTP status codes ranging from 400 (bad request) to 429 (rate‑limit).

• Network failures: Implement exponential back‑off and retry up to three times.
• Rate limiting (429): Respect the Retry-After header; queue excess requests.
• Invalid payload (400): Validate content length and type before sending.
• Authentication errors (401/403): Verify that the secret is correctly loaded and not expired.

Node.js – Centralized Error Middleware

function errorHandler(err, req, res, next) {
  if (err.response) {
    const { status, data } = err.response;
    if (status === 429) {
      const wait = err.response.headers['retry-after'] || 5;
      return res.status(429).json({ message: 'Rate limit exceeded', retryAfter: wait });
    }
    return res.status(status).json({ message: data.error });
  }
  console.error('Unexpected error:', err);
  res.status(500).json({ message: 'Internal server error' });
}

Python – Retry Decorator

import time
from functools import wraps

def retry_on_exception(max_retries=3, backoff=2):
    def decorator(func):
        @wraps(func)
        def wrapper(*args, **kwargs):
            retries = 0
            delay = backoff
            while retries < max_retries:
                try:
                    return func(*args, **kwargs)
                except Exception as e:
                    retries += 1
                    if retries == max_retries:
                        raise
                    time.sleep(delay)
                    delay *= backoff
        return wrapper
    return decorator

@retry_on_exception()
def safe_rate(payload):
    return client.rate(payload)

5. Deploying the Integration on UBOS

UBOS streamlines deployment with its Web app editor on UBOS and built‑in CI pipelines. Follow these steps to push your rating service to production.

1. Repository setup: Commit your code to a GitHub or GitLab repo. UBOS can clone directly via OAuth.
2. Create a new UBOS app: In the UBOS solutions for SMBs console, click New Application and select Node.js or Python runtime.
3. Configure environment: Add OPENCLAW_API_KEY as a secret (see the authentication section).
4. Define a build pipeline: Use the Workflow automation studio to run npm install or pip install -r requirements.txt, then start the server.
5. Expose an endpoint: UBOS automatically provisions a subdomain (e.g., rating.myapp.ubos.io). Map your rating route to /api/rate.
6. Test in staging: UBOS provides a preview* environment*; run integration tests against the staging URL.
7. Promote to production: Once tests pass, click Deploy to Production. UBOS handles zero‑downtime rollouts.

For a deeper dive on hosting OpenClaw on UBOS, see the dedicated page OpenClaw hosting on UBOS.

6. Best‑Practice Tips

• Cache scores: Store recent rating results in Redis (available as a UBOS add‑on) to reduce API calls.
• Batch requests: When processing bulk uploads, send up to 20 items per request to stay within rate limits.
• Monitor latency: Use UBOS’s built‑in monitoring dashboards to alert if response times exceed 300 ms.
• Version your integration: Tag your repo with v1.0, v1.1, etc., and keep a changelog for compliance audits.
• Secure webhook endpoints: Verify a shared secret on incoming callbacks if you enable OpenClaw’s webhook mode.

Explore additional UBOS resources that complement these practices:

• Enterprise AI platform by UBOS – for scaling to millions of requests.
• AI marketing agents – to automatically promote high‑rated content.
• UBOS templates for quick start – jump‑start new projects with pre‑configured rating modules.

7. Real‑World Example: Moltbook Social Network Integration

Moltbook is a community platform where users share short posts, images, and videos. To keep the feed safe, Moltbook integrates the OpenClaw Rating API directly into its content pipeline.

Workflow Overview

1. User submits a post via the Moltbook front‑end.
2. The post payload is sent to a UBOS‑hosted rating microservice.
3. The microservice calls OpenClaw, receives score and confidence.
4. If score >= 70 and confidence >= 0.8, the post is auto‑approved.
5. Otherwise, the post is queued for manual moderation.

Sample Node.js Endpoint

const express = require('express');
const router = express.Router();
const { OpenClawClient } = require('@openclaw/rating-sdk');

const client = new OpenClawClient({
  apiKey: process.env.OPENCLAW_API_KEY,
  endpoint: 'https://api.openclaw.io/v1'
});

router.post('/rate', async (req, res) => {
  const { type, content } = req.body;
  try {
    const { score, confidence } = await client.rate({ type, content });
    if (score >= 70 && confidence >= 0.8) {
      // Auto‑approve
      res.json({ status: 'approved', score, confidence });
    } else {
      // Flag for review
      res.json({ status: 'review', score, confidence });
    }
  } catch (err) {
    console.error('Rating failure:', err);
    res.status(500).json({ error: 'Rating service unavailable' });
  }
});

module.exports = router;

This endpoint can be deployed as a Web app editor on UBOS microservice. Moltbook’s front‑end then consumes the JSON response to decide the UI flow.

By leveraging UBOS’s UBOS partner program, Moltbook also gains access to dedicated support and co‑marketing opportunities, accelerating adoption.

Conclusion

The OpenClaw Rating API is a powerful, low‑latency tool for content moderation, recommendation, and quality scoring. By following this step‑by‑step guide, developers can:

• Set up a secure client using UBOS secret management.
• Make robust rating requests with clear error handling.
• Deploy a scalable microservice on the UBOS platform overview with zero‑downtime.
• Apply best‑practice patterns that keep costs low and performance high.
• Integrate seamlessly into real‑world products like Moltbook.

Ready to power your next UBOS‑hosted app with intelligent content rating? Start by creating a new project in the UBOS solutions for SMBs console and bring the OpenClaw Rating API to life today.

Andrii Bidochko

CTO UBOS

Andrii Bidochko is an AI entrepreneur and researcher focused on AI agents, reinforcement learning, and autonomous systems. He writes about the technologies shaping the future of machine intelligence, from frontier models and agent architectures to real-world AI applications.