Agent Skills: Onnx Converter

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UncategorizedID: jeremylongshore/claude-code-plugins-plus-skills/onnx-converter

Install this agent skill to your local

pnpm dlx add-skill https://github.com/jeremylongshore/claude-code-plugins-plus-skills/tree/HEAD/skills/08-ml-deployment/onnx-converter

Skill Files

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skills/08-ml-deployment/onnx-converter/SKILL.md

Skill Metadata

Name
onnx-converter
Description
'Convert onnx converter operations. Auto-activating skill for ML Deployment.

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