Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add aotenjou/silicon-PaddleOCR --skill silicon-paddle-ocrgit clone --depth 1 https://github.com/aotenjou/silicon-PaddleOCRWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aotenjou/silicon-paddleocr/silicon-paddle-ocr)<a href="https://agentmods.dev/skills/aotenjou/silicon-paddleocr/silicon-paddle-ocr"><img src="https://agentmods.dev/badge/skills/aotenjou/silicon-paddleocr/silicon-paddle-ocr/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aotenjou/silicon-paddleocr/silicon-paddle-ocr"><img src="https://agentmods.dev/badge/skills/aotenjou/silicon-paddleocr/silicon-paddle-ocr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.00927 |
| Opus 5 | $0.00036 | $0.00464 |
| Sonnet 5 | $0.00014 | $0.00185 |
| Haiku 4.5 | $0.00007 | $0.00093 |
Grade A, and why
silicon-paddle-ocr scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OCR - Image Text Recognition
Use PaddleOCR to extract text content from images. Supports single image or batch processing.
Overview
This skill provides optical character recognition (OCR) capabilities using the PaddlePaddle/PaddleOCR-VL-1.5 model via the SiliconFlow API. Extract text from JPG, PNG, WebP, BMP, and GIF images.
When to Use
Invoke this skill when:
- User wants to extract text from an image
- User asks to OCR a screenshot or photo
- User needs to read text from an image file
- User mentions text recognition from images
How to Use
Prerequisites
Ensure the SILICONFLOW_API_KEY environment variable is set:
export SILICONFLOW_API_KEY="your_api_key"
Basic Usage
Execute the OCR script:
python3 scripts/ocr_skill.py [options] image_path
Arguments
| Argument | Description |
|---|---|
images |
Image file path(s) or glob pattern (required) |
-k, --api-key |
API key (default: from SILICONFLOW_API_KEY env) |
-m, --model |
OCR model name (default: PaddlePaddle/PaddleOCR-VL-1.5) |
-p, --prompt |
Recognition prompt for custom behavior |
-j, --json |
Output results in JSON format |
-o, --output |
Save results to specified file |
--max-tokens |
Maximum tokens in response (default: 2000) |
Examples
Single image:
python3 scripts/ocr_skill.py /path/to/image.jpg
Multiple images with glob:
python3 scripts/ocr_skill.py /path/to/images/*.png
JSON output format:
python3 scripts/ocr_skill.py --json /path/to/image.jpg
Custom prompt for table extraction:
python3 scripts/ocr_skill.py -p "Please identify and format table content as Markdown" /path/to/table.jpg
Save to file:
python3 scripts/ocr_skill.py --json --output results.json /path/to/images/*.jpg
Output Format
Text output (default):
--- image.jpg ---
识别到的文字内容
识别到 X 处文字区域
JSON output:
{
"image.jpg": {
"image_path": "/path/to/image.jpg",
"image_size": [width, height],
"texts": [
{
"text": "识别的文字",
"box": [[x1, y1], [x2, y2], [x3, y3], [x4, y4]]
}
],
"full_text": "所有文本的组合"
},
"image2.png": { ... }
}
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 144 lines · 72 tokens per session scan A fea9302f719f
silicon-paddle-ocr is a skill published in the GitHub repository aotenjou/silicon-PaddleOCR (1 stars, last pushed 7mo ago), licensed MIT. It adds 72 tokens to every session and 927 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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