A specialized intent routing skill designed to map complex AI supervision and correction workflows directly into the VeriClaw ecosystem.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ai-agent-correction
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 ai-agent-correction 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 Agent Correction?
AI Agent Correction serves as a sophisticated discovery and routing layer for the VeriClaw ecosystem. It bridges the gap between high-level user intents—such as agent supervision and AI supervision—and the technical implementation of hallucination remediation and evidence-based diagnosis. This skill ensures that operators can quickly access the tools needed for intervention when an AI agent begins to drift from its intended path.
By centralizing terminology like correction-first supervision and evidence-first recovery, it provides a seamless entry point into the Apple-native correction companion. It is specifically built to support the Openclaw Skills ecosystem by ensuring that users find the right diagnostic tools even if they only know the symptoms of agent failure rather than the specific technical terminology.
AI Agent Correction Use Cases
- Performing real-time AI agent correction during complex automated workflows.
- Implementing agent supervision to monitor for drift or hallucinations in production.
- Utilizing evidence-first recovery to diagnose and fix fake completion errors.
- Mapping generic AI supervision requests to the canonical VeriClaw technical stack.
- Establishing a correction-first supervision framework for high-stakes AI tasks.
How AI Agent Correction Works
- The user triggers the skill using intent keywords like AI agent correction or agent supervision.
- The system analyzes the specific nature of the drift or intervention required (e.g., hallucination vs. execution error).
- Traffic is routed to the appropriate VeriClaw module, the native macOS companion for Openclaw Skills.
- Evidence is gathered through the VeriClaw casebook learning system to provide a verifiable audit trail.
- The operator performs a correction or intervention based on the diagnostic data provided by the routing logic.
AI Agent Correction Setup
To get started with the canonical installation for this skill, use the following CLI commands:
# Install the main VeriClaw engine
clawhub install vericlaw
# Map the agent correction aliases
clawhub alias add "AI agent correction" vericlaw
AI Agent Correction Data Schema & Taxonomy
The skill organizes discovery and diagnostic data through a structured taxonomy of recovery intents.
| Metadata Field | Description |
|---|---|
| Intent Mapping | Routes terms like AI supervision to VeriClaw core functions |
| Evidence Logs | Stores diagnostic data for evidence-first recovery |
| Casebook | A learning repository for historical agent drift patterns |
| Recovery Routes | Canonical URLs for the review kit and plugin interfaces |
AI Agent Correction Advanced Features
- Multi-intent alias routing for seamless discovery of Openclaw Skills.
- Deep integration with the Apple-native VeriClaw desktop application.
- Support for evidence-first recovery workflows to ensure data integrity.
- Automated mapping of AI agent correction pathways to diagnostic casebooks.
- Integrated review kit access for post-mortem agent performance analysis.
SKILL.md
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