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data-describe

Generate AI-powered Data Dictionary, Description, and Tags for a CSV/TSV/Excel file

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SKILL.md
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Data Describe

Generate AI-powered documentation for a tabular data file using describegpt. Produces a Data Dictionary (column labels, descriptions, types), a natural-language Description of the dataset, and semantic Tags — all via the connected LLM (no API key needed in MCP mode).

Cowork note: If relative paths don't resolve, call mcp__qsv__qsv_get_working_dir and mcp__qsv__qsv_set_working_dir to sync the working directory.

Steps

  1. Index: Run mcp__qsv__qsv_index on the file for fast random access.

  2. Profile: Run mcp__qsv__qsv_stats with cardinality: true, stats_jsonl: true to generate the stats cache. describegpt reads this cache for column metadata, so it must exist first.

  3. Describe: Run mcp__qsv__qsv_describegpt with the requested options (recommend all: true for comprehensive output). At least one inference option (dictionary, description, tags, or all) is required. Output defaults to <filestem>.describegpt.md.

  4. Present: Display the generated Data Dictionary table, Description, and Tags to the user.

Options

OptionEffect
--all (recommended)Generate Dictionary + Description + Tags in one pass
--dictionaryData Dictionary only — column labels, descriptions, types
--descriptionNatural-language dataset Description only
--tagsSemantic Tags only
--formatOutput format: Markdown (default), JSON, TSV, TOON
--languageGenerate output in a non-English language (e.g. Spanish, French)
--addl-cols-listEnrich the dictionary with extra columns (e.g. "everything", "moar!")
--tag-vocabConstrain tags to a controlled vocabulary (comma-separated)
--num-tagsNumber of tags to generate (default: 5)
--num-examplesNumber of example values per column in the dictionary
--enum-thresholdMax cardinality to treat a column as an enum in the dictionary

Notes

  • No API key needed in MCP mode — uses the connected LLM automatically via MCP sampling
  • The stats cache must exist first for best results (step 2 creates it)
  • Output defaults to <filestem>.describegpt.md
  • For Excel/JSONL files, the MCP server auto-converts to CSV first
  • Use --format JSON when you need machine-readable output for downstream processing
  • Use --language to generate documentation in the user's preferred language
Repository
dathere/qsv
Path

.claude/skills/skills/data-describe/SKILL.md

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17c10db

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