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Auto-generates a Markdown codebook from a dataset (CSV, DTA, Excel, Parquet) with types and summary statistics. Use when documenting variables.

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How to use this skill

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  2. Copy the prompt below and paste it into your agent.
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I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/blob/HEAD/skills/29-quarcs-lab-project20XXy/dot-claude/skills/codebook/SKILL.md

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First, summarize what it does, its dependencies, license status if identifiable, and any risks. Show the exact files you propose to add under .agents/skills/codebook/. Do not write files or run scripts until I approve.

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Generate Variable Codebook

Auto-generate a Markdown codebook documenting all variables in a dataset.

Arguments

  • $ARGUMENTS — path to a dataset file (e.g., data/rawData/sample_data.csv, data/panel.dta)

Steps

  1. Determine the file format from the extension:

    • .csv — read with pandas read_csv
    • .dta — read with pandas read_stata
    • .xlsx / .xls — read with pandas read_excel
    • .parquet — read with pandas read_parquet
    • Other formats: ask the user how to load it

  2. Load the dataset using uv run python and extract metadata for each variable:

    • Variable name
    • Data type (numeric, string, categorical, datetime)
    • Non-missing count and missing count
    • Number of unique values
    • For numeric variables: min, max, mean, median, standard deviation
    • For categorical/string variables: top 5 most frequent values with counts
    • For datetime variables: min and max date

  3. Generate a Markdown codebook with:

    • Header: Dataset name, file path, number of observations, number of variables, date generated
    • Summary table: Variable name | Type | Non-missing | Unique | Description (placeholder)
    • Detailed sections per variable: Full statistics and a [FILL: description] placeholder for the user to add a human-readable description

  4. Derive the output filename from the dataset name:

    • data/rawData/sample_data.csv → references/sample-data-codebook.md

  5. Save to references/<dataset-name>-codebook.md

  6. Report the file path and the number of variables documented.

Error handling

  • If the file does not exist, report the error and suggest checking the path.
  • If the file cannot be read (corrupt, unsupported format), report the error and ask for guidance.
  • Never modify the source data file. This command is read-only with respect to data.