A powerful diagnostic tool that automatically validates, configures, and tests LLM provider connections within Openclaw Skills.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install model-config-check
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-config-check 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 Configuration Check?
This skill is essential for maintaining the reliability of your AI coding environment by providing a robust framework for verifying that Large Language Model (LLM) configurations are accurate. It ensures that base URLs, API keys, and model IDs are functioning correctly across various providers. By integrating deeply with Openclaw Skills, it eliminates the guesswork involved in setting up new providers like OpenAI, Anthropic, or DeepSeek, offering both manual diagnostics and automated background checks whenever configuration changes occur.
Model Configuration Check Use Cases
- Automatically verifying model connectivity after updating provider settings or API keys in Openclaw Skills.
- Diagnosing 401/403 authentication errors or connection timeouts during agent operations.
- Rapidly onboarding new LLM providers by providing only a model name and API key.
- Ensuring high availability of multiple model endpoints by running periodic diagnostic checks.
How Model Configuration Check Works
- The skill monitors for triggers such as manual requests or system-level configuration patches via gateway commands.
- It reads the local configuration file to extract model provider metadata including base URLs, API types, and keys.
- It performs a network connectivity check to ensure the provider endpoint is reachable from the current environment.
- A live API call is executed using the appropriate protocol (e.g., openai-completions or anthropic-messages) to verify token validity.
- It parses the response body to confirm the presence of generated text or reasoning content, ensuring the model is truly functional.
- A detailed validation report is generated for Openclaw Skills users, highlighting specific failures and suggesting actionable fixes.
Model Configuration Check Setup
The skill is typically triggered automatically by the system. To manually initiate a check, you can use the following command:
bash ~/.openclaw/workspace/skills/model-config-check/scripts/check_models.sh
Ensure your configuration file at ~/.openclaw/openclaw.json is accessible.
Model Configuration Check Data Schema & Taxonomy
The skill interacts with the following data structure to validate Openclaw Skills environments:
| Property | Type | Description |
|---|---|---|
| baseUrl | String | The endpoint URL for the API provider (e.g., https://api.openai.com) |
| apiKey | String | The authentication token provided by the LLM vendor |
| api | String | The protocol type: openai-completions, anthropic-messages, or anthropic-completions |
| contextWindow | Number | The maximum input context allowed for the specific model ID |
| maxTokens | Number | The maximum output tokens allowed for the specific model ID |
Model Configuration Check Advanced Features
- Automated provider identification based on model name prefixes like gpt, claude, deepseek, or qwen.
- Real-time configuration patching that automatically fills in context windows and max token values for unknown models.
- Deep integration with Openclaw Skills gateway lifecycle, triggering validation after every update.run or config.apply.
- Intelligent URL path resolution that correctly appends versioned endpoints like /v1/messages based on API type rules.
- Specific diagnostic handling for reasoning models that return content in thought fields rather than standard message fields.
SKILL.md
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