Skills general-ocr-struct

Name: general-ocr-struct
Author: openclaw

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.

install

source · Clone the upstream repo

git clone https://github.com/openclaw/skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/9penny/general-ocr-struct" ~/.claude/skills/openclaw-skills-general-ocr-struct && rm -rf "$T"

OpenClaw · Install into ~/.openclaw/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/9penny/general-ocr-struct" ~/.openclaw/skills/openclaw-skills-general-ocr-struct && rm -rf "$T"

manifest: skills/9penny/general-ocr-struct/SKILL.md

General OCR Struct

Use this skill to separate OCR recognition from downstream content整理.

Workflow

Run the local OCR script on the image first.
Return the raw OCR text before making business interpretations when accuracy matters.
If the image is a transaction-detail screenshot, run structuring mode to group rows into fields.
Mark uncertain fields explicitly as
```
待确认
```
; do not guess missing content.
Only after the user confirms recognition quality, use the result for tables, summaries, or documents.

Commands

Raw OCR

python3 scripts/general_ocr.py raw /path/to/image.jpg

Structured transaction extraction

python3 scripts/general_ocr.py transactions /path/to/image.jpg

JSON output

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.