About this skill

Problem

When business data already lives in Feishu Base or Sheets, manual copying, cleaning, ad hoc SQL, and report drafting can become fragmented. This skill turns table export, data exploration, and report generation into a local workflow for csv or excel files.

How It Works

Export: scripts/main.py calls the Feishu CLI to export wiki/base/sheets URLs, including multi-table or multi-worksheet output, and converts rich-text cells to plain text.
Analysis: scripts/duckdb_analyzer.py uses DuckDB for describe or query modes. It can inspect schema, distributions, and data quality, generate SQL, retry failed queries, correct syntax, column names, and quoting, and validate logic with --sample_fraction.
Reporting: AI produces a Markdown report, scripts/append_data_to_report.py appends result rows, and scripts/generate_report.py can build a self-contained HTML report with KPI cards, bar/line/pie/radar charts, and insights.

Boundaries

This is an offline export-query-report tool, not a real-time dashboard. It depends on pandas, openpyxl, duckdb, numpy, and the Feishu CLI; use the provided scripts for data access, SQL execution, and report updates rather than pasting large result sets into chat.

Screenshots

Use Cases

Export a Feishu Base table to CSV and query 30-day order trends with SQL.
Inspect sheet field distributions, validate SQL aggregation with sampling, then generate a Markdown report.
Export multiple worksheets to Excel and produce an HTML report with KPI cards and charts.
Append analyzed results to the Markdown report, preserving SQL, conclusions, and up to 100 detail rows.

Best For

Operations analysts who turn Feishu tables into local queryable files for review.
BI engineers who validate SQL aggregation and document conclusions in reports.
Product project managers who export project ledgers and add KPI charts.
Data engineers who analyze CSV/Excel files with DuckDB.

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