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Plugin
machine-learning-ops
ML pipeline design, experiment tracking, model evaluation, training debugging, and reproducibility.
$
npx claudepluginhub yeaight7/agent-powerups --plugin machine-learning-opsPopularity
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Med: 0·Avg: 265
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Med: 0·Avg: 1
What's Inside
Slash Commands4
Evaluation Report Command
/evaluation-report
Generate a comprehensive evaluation report for a trained model, highlighting performance, baselines, and subgroup metrics.
Experiment Preflight Command
/experiment-preflight
Audit an ML training script or pipeline for reproducibility, tracking, and basic hygiene before a long run.
Leakage Check Command
/leakage-check
Audit data preprocessing and splitting logic for target leakage.
ml-run-review
/ml-run-review
Review a machine learning training run or experiment configuration for soundness, reproducibility, and evaluation rigor.
Agents4
leakage-auditor
/leakage-auditor
Specialized agent for detecting data leakage, train-test contamination, and temporal leakage in ML pipelines.
ml-experiment-reviewer
/ml-experiment-reviewer
Evaluates ML experiment setups for rigorous baseline comparisons, proper metric tracking, and reproducibility.
Model Evaluation Analyst
/model-evaluation-analyst
Audits evaluation code to ensure test sets are clean, metrics are appropriate for the problem, and confidence intervals are computed.
training-pipeline-debugger
/training-pipeline-debugger
Diagnoses and resolves training loop bottlenecks, memory leaks, vanishing gradients, and hardware underutilization.
Skills7
baseline-comparison-review
/baseline-comparison-review
Ensure that new complex models actually outperform simple, naive baselines.
dataset-split-review
/dataset-split-review
Audit the methodology used to split data into train, validation, and test sets.
experiment-tracking-review
/experiment-tracking-review
Verify that all hyperparameters, metrics, and data references are properly logged.
ml-leakage-check
/ml-leakage-check
Identify and prevent target leakage in ML preprocessing pipelines.
model-evaluation-reporting
/model-evaluation-reporting
Standardize the reporting of model metrics to ensure statistical rigor and business relevance.
Stats
Version0.1.0
Released
LanguageTypeScript
Stars5
Forks1
MaintenanceExcellent
LicenseApache-2.0
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Uses power tools
Uses Bash, Write, or Edit tools
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