CSV Editor
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TDQS
Scored across 39 tools
Most tools have distinct purposes, but there is slight overlap between statistics-related tools (get_statistics, get_column_statistics, get_value_counts) and between outlier/anomaly detection (detect_outliers, find_anomalies). Overall, an agent can distinguish them with careful description reading.
All tool names follow a consistent verb_noun pattern in lowercase snake_case (e.g., add_column, load_csv_from_url). No mixing of conventions, making the naming predictable and easy to understand.
With 39 tools, the server is heavy but covers the full scope of CSV editing, including data loading, manipulation, analysis, session management, and export. The count is appropriate for the comprehensive feature set, though slightly above the ideal range.
The toolkit covers the entire lifecycle of CSV operations: loading (from various sources), exploration (statistics, profiling), manipulation (add/remove/rename columns, fill missing, remove duplicates, sorting, filtering, grouping), validation, undo/redo, session management, and export. No obvious gaps for typical CSV editing tasks.