Nomad changes

.ai-rulez/domains/ocr-integration/rules/ocr-backend-standards.md

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+---
+priority: critical
+---
+
+- Pluggable backend architecture: all backends implement the OcrBackend trait
+- Backend independence: switching backends must not require API changes
+- Tesseract is the default backend (native C FFI via leptess)
+- Python backends (EasyOCR, PaddleOCR): use tokio::task::spawn_blocking, release GIL for Rust work
+- Graceful degradation: if preferred backend unavailable, fall back to next available
+- All backends must return structured results with confidence scores
+- Document installation requirements and troubleshooting for each backend

.ai-rulez/domains/ocr-integration/rules/ocr-language-and-config.md

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+---
+priority: medium
+---
+
+- Validate language packs exist before OCR execution — fail fast with helpful message
+- Support ISO 639 language codes, map to backend-specific formats
+- Configuration cascade: CLI args > environment > config file > defaults
+- Provide troubleshooting guides for common issues (missing tessdata, backend not found)
+- Language pack installation: document per-platform instructions

.ai-rulez/domains/ocr-integration/rules/ocr-performance.md

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+---
+priority: high
+---
+
+- Cache OCR results: key = hash(image_bytes + language + config)
+- Invalidate cache when OCR config changes (backend, language, PSM mode)
+- Batch processing: process multiple images concurrently with configurable parallelism
+- Resource management: limit concurrent OCR operations to avoid memory exhaustion
+- Performance targets: <2s for single page, <10s for 10-page document
+- Monitor and log OCR processing times for regression detection

.ai-rulez/domains/ocr-integration/rules/ocr-quality.md

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+---
+priority: high
+---
+
+- Track confidence scores on all OCR results — expose in API
+- Image preprocessing (denoise, deskew, binarize) should improve accuracy by 10-30%
+- PSM mode selection: auto-detect layout, allow user override (single block, single line, sparse text, etc.)
+- Language detection: validate requested languages are available, provide install hints if not
+- Multi-language support: allow multiple languages per OCR request
+- Test OCR accuracy against ground-truth documents in CI

.ai-rulez/domains/ocr-integration/rules/ocr-table-and-hocr.md

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+---
+priority: high
+---
+
+- hOCR parsing: extract word-level bounding boxes, confidence scores, and text content
+- Preserve spatial relationships from hOCR output for layout reconstruction
+- Table detection: use cell boundary detection (line detection + intersection analysis)
+- Validate grid structure before treating detected regions as tables
+- OCR each cell individually for better accuracy
+- Convert tables to markdown format with proper column alignment