A diagnostic utility that concurrently tests all configured AI models to ensure connectivity and performance across providers.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install model-healthcheck
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 model-healthcheck 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 Model Healthcheck?
The Model Healthcheck is a specialized diagnostic tool designed to maintain the reliability of your AI infrastructure. As a key utility within the Openclaw Skills ecosystem, it allows developers and power users to verify that every configured model—from OpenAI and Anthropic to local LLMs—is responsive and correctly authenticated. By automating the verification process, it prevents unexpected downtime in agent workflows.
This skill eliminates the manual effort of testing individual API endpoints. By integrating directly with your gateway configuration, it provides a transparent view of your model health, ensuring that your Openclaw Skills always have a functional backend to rely on for complex tasks.
Model Healthcheck Use Cases
- Validating API credentials and provider availability after a configuration update.
- Troubleshooting latency issues by measuring the response duration of different models.
- Performing a system-wide audit of all enabled Openclaw Skills backends.
- Quick verification of local model availability in self-hosted environments.
How Model Healthcheck Works
- The skill is triggered by natural language commands such as "check models" or "test all models".
- It fetches the current provider and model inventory using the gateway config.get function.
- The skill filters out the currently active model to avoid redundant testing.
- It initiates concurrent session spawns for every other model, sending a lightweight "model ok" verification prompt.
- It monitors each request with a 30-second timeout to identify slow or hung connections.
- The skill aggregates performance metrics, including success status, response time, and error details, into a comprehensive summary.
Model Healthcheck Setup
To use this healthcheck within your Openclaw Skills setup, ensure your model providers are correctly defined in your configuration file. No additional installation is required if the skill is enabled in your environment.
To trigger a full system check, use the following command in your chat interface:
model healthcheck
To test a specific model, include the model name:
test model gpt-4o
Model Healthcheck Data Schema & Taxonomy
The skill generates a structured report designed for high readability across all messaging platforms supported by Openclaw Skills. The output schema includes:
- Model Identifier: The specific provider/model-id combination.
- Status Indicator: A visual ✅ OK for successful responses or ❌ Failed for errors.
- Latency Metric: Response time measured in seconds (Xs).
- Error Detail: Contextual information for failures, such as API timeouts or authentication errors.
- Final Tally: A summary count of total models tested, passed, and failed.
Model Healthcheck Advanced Features
- Parallel Execution: Tests all models concurrently to deliver results in seconds, regardless of the number of providers.
- Intelligent Filtering: Automatically skips the active model to save tokens and prevent recursion.
- Cross-Platform Formatting: Uses list-based summaries instead of markdown tables to ensure perfect rendering on mobile apps like WhatsApp and Feishu.
- Automated Session Cleanup: Automatically disposes of test sub-sessions to keep your Openclaw Skills environment clean and efficient.
SKILL.md
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