Agent Skills › dathere/qsv › data-describe

data-describe

GitHub

基于LLM为CSV/Excel等表格数据生成数据字典、自然语言描述及语义标签。通过索引、统计和AI推理步骤，自动化构建数据集文档，支持多种输出格式与语言。

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

Trigger Scenarios

需要为表格数据生成元数据或文档分析CSV/Excel文件内容以获取结构化描述

Install

npx skills add dathere/qsv --skill data-describe -g -y

More Options

Non-standard path

npx skills add https://github.com/dathere/qsv/tree/master/.claude/skills/skills/data-describe -g -y

Use without installing

npx skills use dathere/qsv@data-describe

指定 Agent (Claude Code)

npx skills add dathere/qsv --skill data-describe -a claude-code -g -y

安装 repo 全部 skill

npx skills add dathere/qsv --all -g -y

预览 repo 内 skill

npx skills add dathere/qsv --list

SKILL.md

Frontmatter

{
    "name": "data-describe",
    "description": "Generate AI-powered Data Dictionary, Description, and Tags for a CSV\/TSV\/Excel file",
    "allowed-tools": [
        "mcp__qsv__qsv_sniff",
        "mcp__qsv__qsv_count",
        "mcp__qsv__qsv_headers",
        "mcp__qsv__qsv_index",
        "mcp__qsv__qsv_stats",
        "mcp__qsv__qsv_describegpt",
        "mcp__qsv__qsv_list_files",
        "mcp__qsv__qsv_get_working_dir",
        "mcp__qsv__qsv_set_working_dir"
    ],
    "argument-hint": "<file> [--dictionary|--description|--tags|--all]",
    "user-invocable": true
}

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

Index: Run mcp__qsv__qsv_index on the file for fast random access.
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.
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.
Present: Display the generated Data Dictionary table, Description, and Tags to the user.

Options

Option	Effect
`--all` (recommended)	Generate Dictionary + Description + Tags in one pass
`--dictionary`	Data Dictionary only — column labels, descriptions, types
`--description`	Natural-language dataset Description only
`--tags`	Semantic Tags only
`--format`	Output format: `Markdown` (default), `JSON`, `TSV`, `TOON`
`--language`	Generate output in a non-English language (e.g. `Spanish`, `French`)
`--addl-cols-list`	Enrich the dictionary with extra columns (e.g. `"everything"`, `"moar!"`)
`--tag-vocab`	Constrain tags to a controlled vocabulary (comma-separated)
`--num-tags`	Number of tags to generate (default: 5)
`--num-examples`	Number of example values per column in the dictionary
`--enum-threshold`	Max 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