From jeremylongshore-claude-code-plugins-plus-skills
Creates A/B test configurations for ML deployment operations including model serving, MLOps pipelines, monitoring, and production optimization. Useful when writing or running ML tests.
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin langchain-py-packThis skill is limited to using the following tools:
This skill provides automated assistance for a b test config creator tasks within the ML Deployment domain.
Designs and executes A/B tests for production ML models using traffic splitting, statistical significance testing, and canary/shadow deployments. Use for validating new versions, comparing candidates, or measuring business impacts before rollout.
Guides MLOps workflows for ML model deployment: readiness checklists, serving infrastructure (FastAPI, SageMaker, Triton), inference optimization, versioning, A/B testing, drift detection, retraining, and monitoring.
Builds production ML systems with PyTorch 2.x, TensorFlow, Hugging Face, and tools for model serving, feature engineering, A/B testing, and monitoring.
Share bugs, ideas, or general feedback.
This skill provides automated assistance for a b test config creator tasks within the ML Deployment domain.
This skill activates automatically when you:
Example: Basic Usage Request: "Help me with a b test config creator" 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