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CamScanner-Image2Markdown

通过三步 HTTP 管线把图片转换为 Markdown:先上传图片获取 file_id,再调用转换接口得到结果 file_id,最后以原始模式下载 .md 文件到本地指定路径。依赖 curl 与 jq,需联网,图片会发送至第三方服务处理,不含本地离线解析能力。

camscanner-ai
camscanner-ai
热度 40.15
最近更新 2026-05-11 17:40:52
分类:效率依赖:代码执行 / 读写文件 / 第三方 API应用场景:文件转换 / 数据处理

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add camscanner-image2markdown-office
Metadata
name
camscanner-image2markdown
description
Use CamScanner to convert images to Markdown format, powered by a high-precision document parsing engine that intelligently decomposes paragraphs, precisely recognizes tables and multiple element types, handles complex image scenarios, and outputs structured results in reading order, empowering large language models to accurately understand document content. Use when the user wants to convert images (PNG, JPG, etc.) to Markdown, or when images contain text, tables, code, or structured content that needs to be extracted. Also use when the user's input contains images - convert to Markdown first to better understand the image before responding. Triggers on "image to Markdown", "extract text from image", "OCR to Markdown", or when an image needs to be converted to text for processing.
metadata
{"author":"CamScanner","version":"1.0","openclaw":{"emoji":"📷","requires":{"bins":["curl","jq"]}},"homepage":"https://www.camscanner.com"}

CamScanner Image to Markdown

Overview

CamScanner provides a high-precision document parsing engine that converts images to Markdown format. It intelligently decomposes document paragraphs, precisely recognizes tables and multiple element types, handles complex image scenarios, and outputs structured results in reading order — empowering large language models to accurately understand document content. The workflow is a 3-step pipeline: upload the image, convert it, then download the result.

When to Use

  • User wants to convert an image to Markdown
  • User wants to extract text/content from an image as Markdown (OCR)
  • User has a screenshot or photo with text, tables, or structured content
  • User's input contains images — convert to Markdown first, then use the extracted text to better understand and respond to the user's request

Privacy & Data

Important: Privacy & Data Flow Notice

  • Third-party service: This skill sends your files to CamScanner's official servers (ai-tools.camscanner.com) for processing.
  • Data retention: CamScanner servers process your files in real-time. Files are not permanently stored on the server.
  • Local files: Output files are saved to your local filesystem at the path you specify.

API Reference

Base URL: https://ai-tools.camscanner.com

Supported Conversions

source_type target_type Output
image md .md

Step 1: Upload Image

BASE="https://ai-tools.camscanner.com"

IN_FILE_ID=$(curl -sS -X POST "$BASE/v1/tools/upload_file/execute" \
  -H "Content-Type: application/octet-stream" \
  --data-binary "@/path/to/image.png" | jq -r '.tool_result.data.file_id')

Response:

{
  "code": 200,
  "tool": "upload_file",
  "tool_result": {
    "success": true,
    "data": {
      "file_id": "file_1741857600_ab12cd34ef56",
      "size": 24576
    }
  }
}

Step 2: Convert Image to Markdown

OUT_FILE_ID=$(curl -sS -X POST "$BASE/v1/tools/convert_image/execute" \
  -H "Content-Type: application/json" \
  -d "{\"file_id\":\"$IN_FILE_ID\",\"source_type\":\"image\",\"target_type\":\"md\",\"output_mode\":\"file_id\"}" \
  | jq -r '.tool_result.data.file_id')

Response:

{
  "code": 200,
  "tool": "convert_image",
  "tool_result": {
    "success": true,
    "data": {
      "file_id": "file_1741857701_9988aabbccdd",
      "target_type": "md"
    }
  }
}

Step 3: Download Result

curl -sS -X POST "$BASE/v1/tools/download_file/execute?response_mode=raw" \
  -H "Content-Type: application/json" \
  -d "{\"file_id\":\"$OUT_FILE_ID\"}" \
  -o /path/to/output.md

Critical: The response_mode=raw query parameter is required to get the binary file. Without it, the response is JSON.

Quick Reference: Complete Pipeline

BASE="https://ai-tools.camscanner.com"
INPUT_IMAGE="/path/to/image.png"
OUTPUT_FILE="/path/to/output.md"

# Upload
IN_FILE_ID=$(curl -sS -X POST "$BASE/v1/tools/upload_file/execute" \
  -H "Content-Type: application/octet-stream" \
  --data-binary "@$INPUT_IMAGE" | jq -r '.tool_result.data.file_id')

# Convert
OUT_FILE_ID=$(curl -sS -X POST "$BASE/v1/tools/convert_image/execute" \
  -H "Content-Type: application/json" \
  -d "{\"file_id\":\"$IN_FILE_ID\",\"source_type\":\"image\",\"target_type\":\"md\",\"output_mode\":\"file_id\"}" \
  | jq -r '.tool_result.data.file_id')

# Download
curl -sS -X POST "$BASE/v1/tools/download_file/execute?response_mode=raw" \
  -H "Content-Type: application/json" \
  -d "{\"file_id\":\"$OUT_FILE_ID\"}" \
  -o "$OUTPUT_FILE"

Common Mistakes

Mistake Fix
Forgetting response_mode=raw on download Always append ?response_mode=raw to the download URL
Wrong Content-Type on upload Upload uses application/octet-stream, not multipart/form-data
Using GET instead of POST All three endpoints use POST
Missing source_type in convert request Always include "source_type": "image"
Missing output_mode in convert request Always include "output_mode": "file_id" to get a downloadable file_id

Error Handling

Check each step before proceeding:

# After upload
if [ -z "$IN_FILE_ID" ] || [ "$IN_FILE_ID" = "null" ]; then
  echo "Upload failed"; exit 1
fi

# After convert
if [ -z "$OUT_FILE_ID" ] || [ "$OUT_FILE_ID" = "null" ]; then
  echo "Conversion failed"; exit 1
fi