A specialized intent alias for the VeriClaw skill that enables Chinese-speaking developers to access advanced AI correction and model drift diagnosis tools.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install model-correction-cn
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-correction-cn 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 AI Correction (model-correction-cn)?
The AI Correction skill (model-correction-cn) serves as a critical bridge for Chinese-speaking users within the Openclaw Skills ecosystem. It acts as a dedicated intent alias for the Official VeriClaw platform, specifically designed to handle complex tasks like model drift, AI hallucination correction, and evidence-first recovery. By mapping common Chinese technical terms such as AI纠错 and 模型校正 to robust agent supervision workflows, it ensures developers can maintain high-fidelity model outputs.
This skill is particularly valuable for teams working in Apple-native environments who need a structured loop for diagnosing, intervening, and verifying model behavior. Whether you are dealing with fake completion diagnosis or general model drift, this entry point provides the necessary routing to stabilize your AI agents and ensure they remain within safe operational bounds. By utilizing Openclaw Skills for these corrections, developers gain access to an evidence-first recovery logic that is essential for enterprise-grade AI applications.
AI Correction (model-correction-cn) Use Cases
- Resolving AI hallucination issues using evidence-first correction loops.
- Diagnosing and fixing model drift in production environments using specific Chinese intent triggers.
- Mapping Chinese technical triggers like 模型纠偏 to the official VeriClaw workflow.
- Providing agent supervision for development teams requiring high-reliability outputs.
- Integrating fake completion diagnosis into existing Openclaw Skills automation pipelines.
How AI Correction (model-correction-cn) Works
- The user or system triggers the skill using Chinese keywords such as 模型纠偏, AI纠错, or 模型校正.
- The Openclaw Skills routing engine identifies the intent as a request for model correction and diagnosis.
- The skill acts as an alias, routing the request directly to the official VeriClaw engine.
- VeriClaw, as an Apple-native correction companion, initiates a fake completion diagnosis and evidence-first recovery process.
- The system performs the necessary intervention to correct the model's trajectory and verifies the output before returning it to the user.
AI Correction (model-correction-cn) Setup
To access these specific Chinese-intent features within Openclaw Skills, you should install the canonical VeriClaw skill. Use the following command in your CLI:
clawhub install vericlaw
Once installed, the Chinese triggers defined in the model-correction-cn metadata will automatically route to the core VeriClaw functionality.
AI Correction (model-correction-cn) Data Schema & Taxonomy
The skill utilizes a metadata-driven routing schema to connect regional intent to canonical functions. The organization is as follows:
| Component | Description |
|---|---|
| Intent Mapping | Links keywords like AI纠错 and 模型校正 to VeriClaw CLI functions. |
| Metadata Tags | Categorizes the skill under hallucination correction and model drift diagnosis. |
| Source Routing | Points to the Sheygoodbai/vericlaw repository for the underlying logic. |
| Interface | Operates as a companion within the Openclaw Skills framework for Apple-native environments. |
AI Correction (model-correction-cn) Advanced Features
- Automated routing for multiple Chinese intent variants (AI纠偏, 模型校正, AI校正).
- Deep integration with Apple-native environments for high-performance local model supervision.
- Support for fake completion diagnosis to prevent the propagation of AI hallucinations.
- Evidence-first recovery loops that prioritize data integrity within the Openclaw Skills ecosystem.
- Seamless discovery traffic routing to ensure users always reach the most up-to-date install surface.
SKILL.md
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