Splitting Datasets Agent Skill
| Split datasets into training, validation, and test partitions with the right stratification and temporal rules. Use as a narrow preprocessing helper once the broader ML workflow is already chosen, not as the main route owner for an end-to-end ML task.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/foryourhealth111-pixel/Vibe-Skills --skill splitting-datasetsWhat comes with it
9 425 bytes besides the instructionWhat it tells the agent to use
found in the instruction textThe instruction itself
6 sections, as written by the authorDataset Splitter
Positioning
Treat this skill as a narrow helper for partition strategy.
When to Use
Use this skill when:
- Prepare a dataset for machine learning model training.
- Create training, validation, and testing sets.
- Partition data to evaluate model performance.
Not For / Boundaries
- Full preprocessing-pipeline ownership: use
preprocessing-data-with-automated-pipelines - Leakage audits and prediction-time checks: use
ml-data-leakage-guard - Model training and tuning after the split: use
scikit-learn
Typical Outputs
- Partition strategy with ratios, random seeds, and stratification rules
- Notes on temporal or grouped split constraints
- Handoff guidance for leakage review and downstream training
Related Skills
preprocessing-data-with-automated-pipelinesfor the broader preprocessing sequenceml-data-leakage-guardto verify the split does not leak future or test information
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How to use it
Take foryourhealth111-pixel/splitting-datasets from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.