Name: ocr-pipeline-and-quality
Author: xberg-io

Imported from xberg-io/xberg (.ai-rulez/skills/ocr-pipeline-and-quality/SKILL.md). Install upstream with npx skills add xberg-io/xberg --skill ocr-pipeline-and-quality. Copyright stays with the author.

OCR pipeline and quality

OCR flows through preprocessing, backend execution, structured conversion, page acceptance, and caching. Backend outputs are not interchangeable measurements.

Backends and execution

All backends implement OcrBackend. Tesseract is the default and is bound through the in-repo crates/xberg-tesseract C FFI crate; there is no leptess dependency.
OcrBackendType is Tesseract | PaddleOCR | Candle | Custom. Sceptre is selected by name through Custom, not a dedicated enum variant.
Run blocking OCR work through tokio::task::spawn_blocking, minimize runtime/FFI lock duration, and respect backend resource limits.
Check PageOrientationHandling before assuming a backend handles rotated input.
Validate ISO 639 language codes and required tessdata before execution. Language detection runs after extraction and does not choose traineddata automatically.

Configuration and cache

Public types::formats::TesseractConfig and internal ocr::types::TesseractConfig have independent defaults. Change both and keep their synchronization test passing.
The OCR cache key combines image hash, backend, config hash, and output format. The config hash includes TESSERACT_RESULT_SCHEMA_VERSION and the ordered Tesseract variable set; it contains no build or code identity.
Bump TESSERACT_RESULT_SCHEMA_VERSION when unchanged image/config inputs can produce different output, or disable the cache for an A/B or revert check.
Default preprocessing is 300 DPI, deskew, and Otsu binarization. Auto-rotation, denoise, contrast enhancement, and color inversion are off unless configured. Native PSM defaults to 3; WASM defaults to 6.

Quality invariants

Query confidence_semantics() before interpreting confidence. Never threshold Uncalibrated output using a Tesseract-derived scale.
Tesseract font size is typography from hOCR x_fsize; Sceptre/Paddle font size is a geometric detection-box proxy. Do not compare or threshold them as the same quantity.
hocr_font_info=1 is required for Tesseract typography; without it font sizes fall back to 12 pt. Sceptre/Paddle do not provide hOCR style fractions.
accept_or_reject_ocr_page can discard an entire page and its structured paragraphs. Compare accepted pages before word counts. A missing dictionary-invalid ratio is unknown, not zero.
Precision is the scarce resource on the current benchmark corpus. Require an independently grounded F1 A/B for recall-oriented rewrites; use the benchmark-workflow skill.
Measure structural output such as headings and lists in Markdown, not Plain.

Tables and geometry

OCR table detection clusters word bounding boxes; it does not detect ruled lines or re-OCR cells.
Detect rows, merge words into cell tokens, then detect columns on the merged tokens. Use reconstruct_table_with_columns; detecting columns on raw words creates spurious columns for multi-word cells.
The PDF OCR raster is normalized to MediaBox-oriented user space. OCR segments carry rotation_degrees: 0.0; code reasoning about /Rotate pages must carry page rotation explicitly.
Preserve word-level bounding boxes, confidence, and reading order through hOCR parsing and validate a reconstructed grid before emitting Markdown.

Install ocr-pipeline-and-quality and it becomes one more candidate the router can pick - when it fits.

A listing is a routing target with a manifest: what it does, which domains it covers, what it costs and who publishes it. Once installed it sits beside your own models and tools, is scored like any other candidate for each request, and shows up in the trace when it wins. Ratings come from workspaces that installed it, one per account.

{ "ocm": "1", "id": "xberg-io-xberg-ocr-pipeline-and-quality", "kind": "skill", "name": "ocr-pipeline-and-quality", "description": "Change or evaluate Xberg OCR backends, preprocessing, caching, page acceptance, geometry, hOCR structure, table reconstruction, or cross-backend quality. Load for OCR behavior and A/B quality work, not ordinary PDF text extraction.", "publisher": "xberg-io", "version": "1.0.0", "capabilities": { "domains": [ "math", "data_analysis" ], "tags": [ "skill-md", "skills-sh" ], "languages": [ "en" ] }, "quality_prior": 0.6, "examples": [ "Change or evaluate Xberg OCR backends, preprocessing, caching, page acceptance, geometry, hOCR structure, table reconstruction, or cross-backend quality. Load for OCR behavior and A/B quality work, not ordinary PDF text extraction." ], "primary": false, "metadata": { "source": { "provider": "skills.sh", "repository": "https://github.com/xberg-io/xberg", "path": ".ai-rulez/skills/ocr-pipeline-and-quality/SKILL.md", "ref": "HEAD", "url": "https://github.com/xberg-io/xberg/blob/HEAD/.ai-rulez/skills/ocr-pipeline-and-quality/SKILL.md", "key": "xberg-io/xberg/.ai-rulez/skills/ocr-pipeline-and-quality/SKILL.md" } }, "instructions": "# OCR pipeline and quality\n\nOCR flows through preprocessing, backend execution, structured conversion, page acceptance, and caching. Backend\noutputs are not interchangeable measurements.\n\n## Backends and execution\n\n- All backends implement `OcrBackend`. Tesseract is the default and is bound through the in-repo\n `crates/xberg-tesseract` C FFI crate; there is no `leptess` dependency.\n- `OcrBackendType` is `Tesseract | PaddleOCR | Candle | Custom`. Sceptre is selected by name through `Custom`, not a\n dedicated enum variant.\n- Run blocking OCR work through `tokio::task::spawn_blocking`, minimize", "cost": { "context_tokens": 827 } }

ocr-pipeline-and-quality

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