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---
name: onnx-converter
description: 'Convert onnx converter operations. Auto-activating skill for ML Deployment.
Triggers on: onnx converter, onnx converter
Part of the ML Deployment skill category. Use when working with onnx converter functionality.
Trigger with phrases like "onnx converter", "onnx converter", "onnx".
'
allowed-tools: Read, Write, Edit, Bash(cmd:*), Grep
version: 1.0.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- ai
- mlops
compatibility: Designed for Claude Code
---
# Onnx Converter
## Overview
This skill provides automated assistance for onnx converter tasks within the ML Deployment domain.
## When to Use
This skill activates automatically when you:
- Mention "onnx converter" in your request
- Ask about onnx converter patterns or best practices
- Need help with machine learning deployment skills covering model serving, mlops pipelines, monitoring, and production optimization.
## Instructions
1. Provides step-by-step guidance for onnx converter
2. Follows industry best practices and patterns
3. Generates production-ready code and configurations
4. Validates outputs against common standards
## Examples
**Example: Basic Usage**
Request: "Help me with onnx converter"
Result: Provides step-by-step guidance and generates appropriate configurations
## Prerequisites
- Relevant development environment configured
- Access to necessary tools and services
- Basic understanding of ml deployment concepts
## Output
- Generated configurations and code
- Best practice recommendations
- Validation results
## Error Handling
| Error | Cause | Solution |
|-------|-------|----------|
| Configuration invalid | Missing required fields | Check documentation for required parameters |
| Tool not found | Dependency not installed | Install required tools per prerequisites |
| Permission denied | Insufficient access | Verify credentials and permissions |
## Resources
- Official documentation for related tools
- Best practices guides
- Community examples and tutorials
## Related Skills
Part of the **ML Deployment** skill category.
Tags: mlops, serving, inference, monitoring, production