xberg-extracting-tables
Use when extracting tabular data from PDFs, spreadsheets, or images.
Skill by xberg-io
Install
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About
Use cases: documents, data
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Files it touches
~/.claude/skills/xberg-extracting-tables
What's inside
- Skill name
xberg-extracting-tables- Description
- 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.
- License
- MIT
- Instructions
- 145 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- name: missing
Files (2)
- SKILL.md
- index.md
SKILL.md (first lines)
# 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
```bash
# 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 `tables` array** — `--format json`. Each entry has
`cells[][]` (rows × cols), `markdown` (pre-rendered), `page_number`,
`bounding_box`. Use this when downstream code needs exact cell access.
(`bounding_box` is 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.
```bash
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:
| Model | Best for | Notes |
| ------------------ | ----------------------------------------------------- | ------------------------------------------- |
| `tatr` | dense complex tables (academic, financial) | **Default.** Heaviest, highest accuracy. |
| `slanet_auto` | dispatches per-table to wired/wireless | Good when table styles are mixed. |
| `slanet_wired` | tables with visible borders | Faster than tatr. |
| `slanet_wireless` | tables without borders (whitespace-separated) | For invoices, simple grids. |
| `slanet_plus` | hybrid wired / wireless | Lighter than `slanet_auto`. |
| `disabled` | layout detection only, no table structure | Use to skip table model cost. |
```bash
xberg extract bank-statement.pdf \
--layout --layout-table-model tatr --content-format markdown
```
Drop `--layout-confidence` when the layout model misses tables (default
threshold ~0.5):
```bash
xberg extract noisy-scan.pdf --layout --layout-confidence 0.3
```
## Spreadsheets
`.xlsx`, `.ods`, `.csv`, `.tsv` are extracted by dedicated parsers — no
layout model needed. Each sheet becomes a markdown table (or structured
table) automatically:
```bash
xberg extract workbook.xlsx --content-format markdown
xberg extract data.csv --format json
```
Pass `--no-cache=true` only when iterating on the same file with different
configs.
## Config file alternative
```toml
# `output_format` in config files equals `--content-format` on the CLI.
output_format = "markdown"
[layout]
confidence_threshold = 0.5
table_model = "tatr"
```
Then:
```bash
xberg extract report.pdf --format json
```
## Programmatic access
From Python, structured tables live on the document in the result envelope
(`result.results[0].tables`):
```python
from xberg import ExtractInput, extract, ExtractionConfig, LayoutDetectionConfig
config = ExtractionConfig(
layout=LayoutDetectionConfig(table_model="tatr"),
output_format="markdown",
)
result = await extract(ExtractInput(uri="report.pdf"), config)
for table in result.results[0].tables:
print(table.markdown) # rendered markdown
print(table.cells[0][0]) # cell access
```
Node.js mirrors this (`extract`, `output.results[0].tables`, camelCase fields).
See `../../references/python-api.md` and `../../references/nodejs-api.md` for full type signatures.
## Known limitationsFrom xberg-io/xberg, MIT.
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Compare and alternatives
Featured in
Signals
- Stars
- 9,441
- Forks
- 600
- Open issues
- 7
- Last commit (this folder)
- Oct 14, 2026 (13 days ago)
- Last release
- Oct 13, 2026 (14 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/xberg-io/xberg
- Website
- docs.xberg.io
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
xberg-extracting-tables skill. Agent Mart. https://agentmart.dev/skills/xberg-io-xberg-extracting-tables (last updated 2026-10-24)