From jeremylongshore-claude-code-plugins-plus-skills
Assists with model export helper operations for ML deployment, including model serving, mlops pipelines, monitoring, and production optimization.
How this skill is triggered — by the user, by Claude, or both
Slash command
/jeremylongshore-claude-code-plugins-plus-skills:model-export-helperThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
This skill provides automated assistance for model export helper tasks within the ML Deployment domain.
This skill provides automated assistance for model export helper tasks within the ML Deployment domain.
This skill activates automatically when you:
Example: Basic Usage Request: "Help me with model export helper" Result: Provides step-by-step guidance and generates appropriate configurations
| 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 |
Part of the ML Deployment skill category. Tags: mlops, serving, inference, monitoring, production
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin j-rigCreates TensorFlow SavedModel exports for ML model deployment. Guides through saving, versioning, and optimizing models for production serving and inference.
Deploys trained ML models to production with API endpoints, containerization, and monitoring. Automates the deployment workflow with CI/CD integration.
Builds production ML systems with PyTorch 2.x, TensorFlow, and modern frameworks for model serving, feature engineering, A/B testing, monitoring, and infrastructure.