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Track an experiment so a result can be reproduced: seeds, data versions, and the holdout that never gets peeked at.
Passed 16 of 19 test cases with the skill, and 11 of 19 without it.
and 6 more in the full report
7 fixed11 passed either way2 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
An ML engineer is writing a Python training script using scikit-learn. They plan to rely on default random states without setting explicit seeds. Generate an experiment tracking checklist for this script.
| Checked | Without skill | With skill |
|---|---|---|
| Mandates setting explicit random seed values | Missed | Passed |
| Mandates logging dataset version metadata | Passed | Passed |
The instructions your model reads when the skill loads.
Track an experiment so a result can be reproduced: seeds, data versions, and the holdout that never gets peeked at.
test cases passed, vs 11 / 19 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.