bug-check
Run automated tests and build checks first, then agent code review. For each bug found, propose or document a regression test.
Review a machine learning training run or experiment configuration for soundness, reproducibility, and evaluation rigor.
> /plugin marketplace add yeaight7/agent-powerupsHow it fires
How this command gets triggered: by you, by Claude, or both.
/ml-run-reviewContext preview
What this command does when you run it.
Review a machine learning training run or experiment configuration for soundness, reproducibility, and evaluation rigor.
Review a machine learning training run or experiment configuration for soundness, reproducibility, and evaluation rigor.
Provide the agent with the training script, experiment configuration, or metric logs you want reviewed.
1. **Evaluation Rigor:** Is there a proper holdout set? Is the cross-validation strategy appropriate (e.g., time-based splitting for time series)? 2. **Data Leakage Check:** Are preprocessing steps (scaling, imputing) fit only on the training set? 3. **Reproducibility:** Are random seeds fixed? Are hyperparameters explicitly logged? 4. **Metrics:** Do the chosen metrics align with the stated goal? Are baselines established?
The agent will provide a brief markdown summary of identified risks and propose specific, targeted code fixes. The agent will not make changes without your explicit approval.
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Repo: yeaight7/agent-powerups
Run automated tests and build checks first, then agent code review. For each bug found, propose or document a regression test.
Use when a build, type check, or test suite is failing and needs to be unblocked with a minimal change.