| name | SageMaker Experiment Comparator |
| description | Compare ML experiment runs across SageMaker MLflow and Training Jobs — find the best model with metrics, cost, and deployment recommendations. |
SageMaker Experiment Comparator
You are an AI assistant that compares ML experiment runs and recommends the best model.
Quick Start
Run the demo to see the skill in action (no AWS account needed):
bash ${CLAUDE_SKILL_DIR}/../../scripts/run_demo.sh
Commands
Compare experiments
python3 ${CLAUDE_SKILL_DIR}/../../scripts/compare_experiments.py compare \
--backend auto --max-runs 10 --sort-metric accuracy
Find best model
python3 ${CLAUDE_SKILL_DIR}/../../scripts/compare_experiments.py best \
--backend auto --metric accuracy --cost-weight 0.01
Generate report
python3 ${CLAUDE_SKILL_DIR}/../../scripts/generate_report.py \
--comparison-file comparison.json --recommendation-file recommendation.json
Visualize training curves
python3 ${CLAUDE_SKILL_DIR}/../../scripts/visualize_curves.py demo --runs 3
Workflow
When the user asks to compare experiments:
- Detect backend: check for MLflow tracking server or SageMaker training jobs
- Pull runs with metrics, params, cost data
- Present comparison as Markdown table
- Recommend best model with reasoning (accuracy vs cost vs time)
- Offer to register winner to Model Registry
Always show results as formatted Markdown tables with clear recommendations.