{"skill":{"slug":"clean-csv-toolkit","displayName":"Clean CSV Toolkit","summary":"Local CSV / TSV / JSONL inspection and cleanup toolkit. Profile a tabular file (row count, auto-detected column types, nulls, distincts, samples), validate i...","tags":{"convert":"0.1.0","csv":"0.1.0","data":"0.1.0","dedupe":"0.1.0","diff":"0.1.0","jsonl":"0.1.0","latest":"0.1.0","markdown":"0.1.0","stdlib":"0.1.0","tsv":"0.1.0","validation":"0.1.0"},"stats":{"comments":0,"downloads":71,"installsAllTime":0,"installsCurrent":0,"stars":1,"versions":1},"createdAt":1778588010830,"updatedAt":1778588508486},"latestVersion":{"version":"0.1.0","createdAt":1778588010830,"changelog":"v0.1.0 initial release. Local CSV/TSV/JSONL toolkit. Five scripts: inspect.py profiles a tabular file with auto-detected column types (int/float/bool/date/datetime/string), null counts, distincts, samples, encoding, and dialect. validate.py checks a file against a small JSON schema (required columns, per-column type, min/max, enum, regex, unique). dedupe.py removes duplicates by full-row or key columns with optional --keep first/last, --case-insensitive, --trim, and JSONL removed-rows report. diff.py compares two files by key column(s) and classifies rows as added/removed/changed/unchanged with per-column before/after for changed rows. convert.py converts between csv/tsv/jsonl/json/md. Pure Python 3 standard library, no pandas, no numpy, no subprocess, no remote calls. Consistent 0/1/2 exit codes across all scripts. 26 end-to-end tests covering CSV/TSV/JSONL inputs, schema validation, full-row and keyed dedup, file diffing, round-trip format conversion, 10k-row performance, error paths.","license":"MIT-0"},"metadata":{"os":null,"systems":null},"owner":{"handle":"gopendrasharma89-tech","userId":"s17cp87fy279ggwne1mqcb6675843tdy","displayName":"gopendrasharma89-tech","image":"https://avatars.githubusercontent.com/u/226691732?v=4"},"moderation":null}