Data

查看数据结构、质量和可分析性(schema 数据概览 profiling)

gabrielmoreira Updated 17 repo stars

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数据诊断

先获取 schema 和必要样本,报告表规模、字段类型、缺失、重复、异常、时间范围和关键分布。区分事实、风险与建议,指出可直接分析的字段及需要用户确认的口径。

Tool routing

  1. Use get_schema first to inspect tables, fields, row counts, and source structure.
  2. Use get_table_detail when one table needs deeper field-level metadata.
  3. Use profile_data for data quality, missingness, type, and distribution diagnostics.
  4. Use query_data for small verification samples or targeted aggregates.
  5. Use generate_chart only when a compact diagnostic chart materially helps explain the data.

Implementation reference

  • Data tool entries: agent/tools/business/data.py
  • Profiling implementation: Function/Clean/data_profile.py
  • Chart implementation: Function/Charts_generation/chart_generate.py

gabrielmoreira/agent-skills-mirror/tree/main/mirrors/repos/Zafer-Liu@Data-Analysis-Agent/skills/data commit 7e7cc57746

Frequently asked questions

npx skillmds@latest add gabrielmoreira/data