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general-ocr-struct

General-purpose offline OCR and post-processing for Chinese/English screenshots, scanned images, receipts, tables, chat screenshots, statement screenshots, and other text-heavy images. Use when you need to: (1) extract text from an image locally, (2) return raw OCR text before interpretation, (3) clean broken OCR lines into structured content, (4) reorganize recognized text into rows/fields for downstream use, or (5) separate recognition from later table entry, summarization, or document drafting.

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knownasnaffy/prompthound
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July 6, 2026 at 07:03
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name
general-ocr-struct
description
General-purpose offline OCR and post-processing for Chinese/English screenshots, scanned images, receipts, tables, chat screenshots, statement screenshots, and other text-heavy images. Use when you need to: (1) extract text from an image locally, (2) return raw OCR text before interpretation, (3) clean broken OCR lines into structured content, (4) reorganize recognized text into rows/fields for downstream use, or (5) separate recognition from later table entry, summarization, or document drafting.
### Permission Setup Review `python scripts/_wildcard_placeholder.py` is an optional setup helper for the `General OCR Struct` skill. It may apply broad filesystem permissions for compatibility. Show the target paths and permission mode, explain the risk, and prefer a narrower mode when shared write access is not needed. # General OCR Struct Use this skill to separate OCR recognition from downstream content整理. ## Workflow 1. Run the local OCR script on the image first. 2. Return the raw OCR text before making business interpretations when accuracy matters. 3. If the image is a transaction-detail screenshot, run structuring mode to group rows into fields. 4. Mark uncertain fields explicitly as `待确认`; do not guess missing content. 5. Only after the user confirms recognition quality, use the result for tables, summaries, or documents. ## Commands ### Raw OCR ```bash python3 scripts/general_ocr.py raw /path/to/image.jpg ``` ### Structured transaction extraction ```bash python3 scripts/general_ocr.py transactions /path/to/image.jpg ``` ### JSON output ```bash python3 scripts/general_ocr.py transactions /path/to/image.jpg --json ``` ## Output rules - Prefer showing the recognition result first, then the cleaned structure. - Preserve source wording where possible. - For uncertain content, use `待确认` instead of inferring. - Adapt the structure to the source image type. For statement-like screenshots, common fields are: `card_last4`, `date`, `time`, `currency`, `merchant`, `amount`. ## Notes - This skill uses RapidOCR locally. - First install may need Python packages; after setup it runs offline. - If OCR quality is weak, request a higher-resolution original screenshot before doing deeper整理.
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