A professional utility for converting web content from major platforms into structured Feishu documents while preserving image placement and bypassing anti-leech protections.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install article-to-feishu
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install article-to-feishu using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Article to Feishu?
Article to Feishu is a robust tool designed for Openclaw Skills that bridges the gap between web-based content and professional documentation. It automates the process of scraping articles from popular platforms like WeChat, CSDN, and Zhihu, ensuring that images are downloaded locally to bypass anti-hotlinking restrictions before being re-uploaded to Feishu.
This skill is particularly valuable for research teams and content managers who need to archive or collaborate on web-based information within the Feishu ecosystem. By utilizing specialized scripts and AI agent protocols, it maintains the original reading flow by interleaving text and media in the correct sequential order.
Article to Feishu Use Cases
- Archiving technical blog posts from CSDN or CNBlogs into a shared team knowledge base.
- Converting WeChat Official Account articles into editable Feishu documents for internal review.
- Saving news reports or research papers from Toutiao or Zhihu into Feishu for long-term storage.
- Automating the migration of public web content into a private documentation workspace.
How Article to Feishu Works
- The system fetches the raw article content using tools like web_fetch, curl, or Jina AI Reader for sites with heavy anti-scraping measures.
- It extracts all image URLs from the content while maintaining their relative position to the text.
- A specialized script downloads images to a local temporary directory, automatically applying the correct Referer headers to bypass anti-leech security.
- A new Feishu document is initialized via the feishu_create_doc API.
- The content is built segment-by-segment, alternating between appending Markdown text and inserting local image files.
- Temporary local files are purged once the document is successfully synchronized to the cloud.
Article to Feishu Setup
To integrate this with your Openclaw Skills environment, ensure you have the necessary scripts in your base directory. You can initiate the image download and document creation via the CLI:
# Download images with automatic anti-leech handling
bash {baseDir}/scripts/download_article_images.sh "$ARTICLE_URL" /tmp/article-img/
# Fetch content from protected sites
bash {baseDir}/scripts/fetch_article.sh "$ARTICLE_URL"
# Clean up after processing
rm -rf /tmp/article-img/
Article to Feishu Data Schema & Taxonomy
The skill organizes data through a sequential numbering system to ensure document integrity. Images are handled as follows:
| Data Type | Organization Method |
|---|---|
| Images | Stored in /tmp/article-img/ named as 01.jpg, 02.jpg, etc. |
| Metadata | The skill identifies the source domain to apply specific Referer headers. |
| Document | Created via Feishu Open API using a segmented append mode. |
| Formatting | Supports standard Markdown, including headers, lists, and image alignment. |
Article to Feishu Advanced Features
- Anti-Leech Bypass: Automatic Referer header detection for platforms like CSDN, WeChat, and Toutiao.
- Jina AI Reader Integration: Enhanced scraping capabilities for websites with complex JavaScript or anti-bot protections.
- Sequential Segment Building: Ensures that images appear exactly where they did in the original article rather than being bulk-uploaded at the end.
- Custom Referer Support: Allows users to manually specify headers for unsupported or private websites.
- Multi-format Support: Handles various image types and ensures they meet Feishu's 20MB size limit requirements.
SKILL.md
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