/extracting-with-ocr
Use when extracting text from scanned PDFs, photographed pages, or images that have no embedded text layer. Covers OCR backends, language packs, force-OCR, and performance tuning.
$ npx -y skills add xberg-io/xberg --skill extracting-with-ocr --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/extracting-with-ocr
Context preview
The summary Claude sees to decide when to auto-load this skill.
Use when extracting text from scanned PDFs, photographed pages, or images that have no embedded text layer. Covers OCR backends, language packs, force-OCR, and performance tuning.
SKILL.md
extracting-with-ocr.SKILL.mdname: extracting-with-ocr
description: Use when extracting text from scanned PDFs, photographed pages, or images that have no embedded text layer. Covers OCR backends, language packs, force-OCR, and performance tuning.
<!-- AI-RULEZ :: GENERATED FILE — DO NOT EDIT Content-Hash: blake3:3ec8b7cf60f56cbe5cc15a5a0b29d0c2f8e3cf4c3823503eb1128fb7f9ee11db Source-Hash: blake3:5907a9cc29a5d72bbd3eaf5b820cac5133c8724895664c64fa8eafc2227716af Schema-Version: v1 -->
Extracting with OCR
Use this when a document is image-based: scanned PDFs, photographed pages, screenshots, JPEG/PNG/TIFF with text. Xberg auto-OCRs raster images and auto-detects PDFs that lack a text layer. Force it on when extraction returned empty/garbled text from a PDF that "looks" textual.
When to force OCR
- Extraction returned an empty `content` field, but the file opens visually.
- The PDF text layer is junk (copy-paste from a viewer produces gibberish).
- You want consistent output across mixed scanned + digital PDFs.
xberg extract scan.pdf --force-ocr=true
xberg extract scan.pdf --ocr=true --ocr-language eng
If a page has an unreliable text layer, `--force-ocr=true` re-rasterizes and runs OCR on every page.
Backends
Tesseract is the default and ships with the CLI — no extra install. Other backends are opt-in:
| Backend | Flag | Install | Notes | | ------------- | ------------------------------------- | ------------------------------------------------ | -------------------------------------------------------------- | | Tesseract | `--ocr-backend tesseract` (default) | bundled | Best general-purpose, 100+ languages via tessdata. | | PaddleOCR | `--ocr-backend paddle-ocr` | bundled (ONNX Runtime) | Strong on Asian scripts. Not available on WASM or Windows. | | Candle VLM | `--ocr-backend candle-trocr` (and other `candle-*`) | bundled (Candle) | Local vision OCR models (`candle-trocr`, `candle-paddleocr-vl`, `candle-glm-ocr`, `candle-deepseek-ocr`). | | VLM (hosted) | `--ocr-backend vlm` + `--vlm-model` | liter-llm provider (`--vlm-api-key`) | Multimodal LLM via liter-llm. Use when OCR fails on dense or handwritten layouts. |
Pick Tesseract first. Switch only when accuracy is unacceptable.
Language packs
Tesseract uses ISO 639-2 codes. Default is `eng`. Combine with `+`:
xberg extract menu.jpg --ocr=true --ocr-language "eng+deu"
xberg extract bilingual.pdf --ocr-language "eng+jpn"
xberg extract any.pdf --ocr-language all # all installed packs
Install missing packs at the OS level:
# macOS
brew install tesseract-lang
# Debian/Ubuntu
sudo apt install tesseract-ocr-deu tesseract-ocr-jpn tesseract-ocr-fra
# Specific lang only
sudo apt install tesseract-ocr-<iso639-2>
Xberg fails fast with a helpful error if you request a language pack that is not installed. Read the error — it names the missing file.
Useful flags
- `--ocr=true` — enable OCR (auto-enabled for images and scanned PDFs).
- `--force-ocr=true` — OCR every page even if a text layer exists.
- `--disable-ocr=true` — never OCR (extract embedded text only or fail).
- `--ocr-language <lang>` — single code or `+`-joined list, or `all`.
- `--ocr-backend <tesseract|paddle-ocr|vlm|candle-trocr|candle-paddleocr-vl|candle-glm-ocr|candle-deepseek-ocr>` — pick backend.
- `--ocr-auto-rotate=true` — pre-rotate via the auto-rotate model.
- `--acceleration <cpu|coreml|cuda|tensorrt|auto>` — ONNX accelerator for
paddle-ocr / auto-rotate / layout models.
Performance tips
- Cache is on by default. Repeated extraction of the same file + config is
instant. Do not pass `--no-cache=true` unless you have a reason.
- For batch OCR, use `xberg batch *.pdf --ocr=true` — internal worker
pool parallelizes across CPU cores. Cap with `--max-concurrent N` if memory is tight.
- Raise `--target-dpi` (default 300) only for low-resolution scans. Higher
DPI is slower; 200 is usually enough for printed text.
- Enable `--ocr-auto-rotate=true` only when pages may be rotated; the
classifier adds latency.
- On Apple Silicon, `--acceleration coreml` typically beats CPU for
paddle-ocr and layout detection.
Config file alternative
Long flag chains belong in `xberg.toml` — auto-discovered from cwd upward.
force_ocr = true
output_format = "markdown"
[ocr]
backend = "tesseract"
language = "eng+deu"
auto_rotate = true
Then just run:
xberg extract document.pdf
Common failure modes
- **"missing tessdata"** — install the language pack at OS level (see above).
- **Empty content on a scanned PDF without `--force-ocr`** — the file has a
bogus zero-width text layer. Re-run with `--force-ocr=true`.
- **OCR on a rotated page** — add `--ocr-auto-rotate=true` or pre-rotate.
- **Garbled CJK output** — ensure the right language pack is installed and
passed via `--ocr-language`; consider `paddle-ocr` for Chinese/Japanese.
See `references/cli-reference.md` and `references/configuration.md` in the sibling `xberg` skill for the full flag and config schema.
Read more
name: extracting-with-ocr description: Use when extracting text from scanned PDFs, photographed pages, or images that have no embedded text layer. Covers OCR backends, language packs, force-OCR, and performance tuning.
<!-- AI-RULEZ :: GENERATED FILE — DO NOT EDIT Content-Hash: blake3:3ec8b7cf60f56cbe5cc15a5a0b29d0c2f8e3cf4c3823503eb1128fb7f9ee11db Source-Hash: blake3:5907a9cc29a5d72bbd3eaf5b820cac5133c8724895664c64fa8eafc2227716af Schema-Version: v1 -->
Extracting with OCR
Use this when a document is image-based: scanned PDFs, photographed pages, screenshots, JPEG/PNG/TIFF with text. Xberg auto-OCRs raster images and auto-detects PDFs that lack a text layer. Force it on when extraction returned empty/garbled text from a PDF that "looks" textual.
When to force OCR
- Extraction returned an empty `content` field, but the file opens visually.
- The PDF text layer is junk (copy-paste from a viewer produces gibberish).
- You want consistent output across mixed scanned + digital PDFs.
xberg extract scan.pdf --force-ocr=true xberg extract scan.pdf --ocr=true --ocr-language eng
If a page has an unreliable text layer, `--force-ocr=true` re-rasterizes and runs OCR on every page.
Backends
Tesseract is the default and ships with the CLI — no extra install. Other backends are opt-in:
| Backend | Flag | Install | Notes | | ------------- | ------------------------------------- | ------------------------------------------------ | -------------------------------------------------------------- | | Tesseract | `--ocr-backend tesseract` (default) | bundled | Best general-purpose, 100+ languages via tessdata. | | PaddleOCR | `--ocr-backend paddle-ocr` | bundled (ONNX Runtime) | Strong on Asian scripts. Not available on WASM or Windows. | | Candle VLM | `--ocr-backend candle-trocr` (and other `candle-*`) | bundled (Candle) | Local vision OCR models (`candle-trocr`, `candle-paddleocr-vl`, `candle-glm-ocr`, `candle-deepseek-ocr`). | | VLM (hosted) | `--ocr-backend vlm` + `--vlm-model` | liter-llm provider (`--vlm-api-key`) | Multimodal LLM via liter-llm. Use when OCR fails on dense or handwritten layouts. |
Pick Tesseract first. Switch only when accuracy is unacceptable.
Language packs
Tesseract uses ISO 639-2 codes. Default is `eng`. Combine with `+`:
xberg extract menu.jpg --ocr=true --ocr-language "eng+deu" xberg extract bilingual.pdf --ocr-language "eng+jpn" xberg extract any.pdf --ocr-language all # all installed packs
Install missing packs at the OS level:
# macOS brew install tesseract-lang # Debian/Ubuntu sudo apt install tesseract-ocr-deu tesseract-ocr-jpn tesseract-ocr-fra # Specific lang only sudo apt install tesseract-ocr-<iso639-2>
Xberg fails fast with a helpful error if you request a language pack that is not installed. Read the error — it names the missing file.
Useful flags
- `--ocr=true` — enable OCR (auto-enabled for images and scanned PDFs).
- `--force-ocr=true` — OCR every page even if a text layer exists.
- `--disable-ocr=true` — never OCR (extract embedded text only or fail).
- `--ocr-language <lang>` — single code or `+`-joined list, or `all`.
- `--ocr-backend <tesseract|paddle-ocr|vlm|candle-trocr|candle-paddleocr-vl|candle-glm-ocr|candle-deepseek-ocr>` — pick backend.
- `--ocr-auto-rotate=true` — pre-rotate via the auto-rotate model.
- `--acceleration <cpu|coreml|cuda|tensorrt|auto>` — ONNX accelerator for
paddle-ocr / auto-rotate / layout models.
Performance tips
- Cache is on by default. Repeated extraction of the same file + config is
instant. Do not pass `--no-cache=true` unless you have a reason.
- For batch OCR, use `xberg batch *.pdf --ocr=true` — internal worker
pool parallelizes across CPU cores. Cap with `--max-concurrent N` if memory is tight.
- Raise `--target-dpi` (default 300) only for low-resolution scans. Higher
DPI is slower; 200 is usually enough for printed text.
- Enable `--ocr-auto-rotate=true` only when pages may be rotated; the
classifier adds latency.
- On Apple Silicon, `--acceleration coreml` typically beats CPU for
paddle-ocr and layout detection.
Config file alternative
Long flag chains belong in `xberg.toml` — auto-discovered from cwd upward.
force_ocr = true output_format = "markdown" [ocr] backend = "tesseract" language = "eng+deu" auto_rotate = true
Then just run:
xberg extract document.pdf
Common failure modes
- **"missing tessdata"** — install the language pack at OS level (see above).
- **Empty content on a scanned PDF without `--force-ocr`** — the file has a
bogus zero-width text layer. Re-run with `--force-ocr=true`.
- **OCR on a rotated page** — add `--ocr-auto-rotate=true` or pre-rotate.
- **Garbled CJK output** — ensure the right language pack is installed and
passed via `--ocr-language`; consider `paddle-ocr` for Chinese/Japanese.
See `references/cli-reference.md` and `references/configuration.md` in the sibling `xberg` skill for the full flag and config schema.
The fast, precise document-intelligence engine — for every language. Point Xberg at anything — a PDF, a scanned image, a spreadsheet, an audio file, a URL, a whole archive, or a source tree — and get back clean text, tables, metadata, and structured data.
Repo: xberg-io/xberg
Other skills on xberg.
- /batch-extraction
Use when extracting from many files at once with shared config, bounded parallelism, per-file overrides, and error recovery. Covers the `batch` command, `--file-configs`, `--max-concurrent`, and output layout.
Open skill - /chunking
Use when splitting extracted text into chunks for LLM context windows or RAG ingestion. Covers chunk size, overlap, markdown/yaml/semantic chunkers, tokenizer-based sizing, and the standalone `chunk` command.
Open skill - /extracting-keywords
Use when extracting keywords (YAKE/RAKE) from documents — and, secondarily, when detecting document language or generating embeddings for RAG and search. Covers the keyword config (and its feature gating), `--detect-language`, and the standalone `embed` command with real flags.
Open skill - /extracting-tables
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.
Open skill - /picking-a-format
Use when choosing an output format for extracted documents — text, markdown, djot, html, or JSON. Maps consumer (LLM, parser, archive) to the right `--format` / `--content-format` pair.
Open skill - /xberg
Extract text, tables, metadata, and images from 101 document formats (PDF, Office, images, HTML, email, archives, academic) using Xberg. Use when writing code that calls Xberg APIs in Python, Node.js/TypeScript, Rust, or CLI. Covers installation, extraction (sync/async),
Open skill

