Xberg Extracting Tables
Use when extracting tabular data from PDFs, spreadsheets, or images.
Install
npx skills add xberg-io/xberg --skill xberg-extracting-tables -g -a claude-code -y- Repository
- xberg-io/xberg9.5k
- Category
- Engineering
- Updated
- 3d ago
- License
- MIT
- Context cost
- Lightabout 1,400 tokens
- Runs scripts
- No, instructions only
What it does
Use when extracting tabular data from PDFs, spreadsheets, or images. Covers layout-aware table detection, table model selection, output formats (markdown / JSON cells), and known limits.
Extracting tables
Use this when the user wants structured tabular data, financial statements, scientific tables, invoices, spreadsheet-style PDFs. Xberg detects tables via a layout model (RT-DETR v2) and reconstructs cell structure with a configurable table model.
Basic usage
# Markdown tables embedded in the content stream
xberg extract report.pdf --layout --content-format markdown
# Structured JSON output, tables appear under result.tables
xberg extract report.pdf --layout --format json
--layout turns on layout-aware extraction; without it, tables fall back
to plain text reflow and you lose cell boundaries.
Output shapes
Two surfaces, picked via --format (CLI shape) and --content-format
(content rendering):
- Markdown tables in
content,--content-format markdown. Tables appear inline as| col | col |blocks. Good for LLM ingestion. - Structured
tablesarray,--format json. Each entry hascells[][](rows × cols),markdown(pre-rendered),page_number,bounding_box. Use this when downstream code needs exact cell access. (bounding_boxis omitted when no position data is available.)
Both are populated at once when --layout is on. The tables array is
always structured; the content stream switches representation.
xberg extract financials.pdf --layout --format json \
| jq '.result.tables[] | {page: .page_number, rows: (.cells | length)}'
Table models
--layout-table-model picks the reconstruction backend:
