EDA Desk - check a train/test split for leakage before modeling

Drop a CSV or TSV, name its split, subject, group and time columns, and your browser runs the exploratory-data-analysis skill's own profile, missingness/split-leakage audit and outlier sensitivity, same output as the Python, free, rows never leave the page. Paid lanes review the split (resplit plan + scikit-learn code) or draft the EDA report from aggregates only. Derived from @k-dense-ai/exploratory-data-analysis (k-dense-ai/scientific-agent-skills, MIT).

Every public app is built from a security-scanned skill and must pass a clean scan — skill and frontend — before it can be listed. Have a skill of your own? Turn it into an app — or read the step-by-step walkthrough.