wechat-to-notebooklm

name	wechat-to-notebooklm
description	WeChat article to NotebookLM sync tool. Use when user provides a WeChat Official Account article URL (mp.weixin.qq.com) and wants to add it to their NotebookLM. Automatically fetches article content, converts to Markdown, creates notebook, and uploads to NotebookLM.

WeChat to NotebookLM

Automatically sync WeChat Official Account articles to Google NotebookLM for AI-powered analysis, summarization, and content generation.

What This Does

This skill automates the entire workflow of getting a WeChat article into NotebookLM:

1. Fetches the article content from the URL
2. Converts to clean Markdown format
3. Creates a NotebookLM notebook (optionally with custom title)
4. Uploads the article as a source
5. Returns the notebook ID for further interaction

When to Use

Use this skill when you:

• Have a WeChat Official Account article URL (mp.weixin.qq.com)
• Want to save the article to NotebookLM for analysis
• Want to create a podcast/video from the article
• Want to chat with the article content using AI
• Want to summarize or extract insights from the article

Example triggers:

• "Sync this WeChat article to NotebookLM"
• "Add this mp.weixin.qq.com link to my notebook"
• "Create a notebook from this WeChat article"
• "Save this article to NotebookLM"

Prerequisites

Before using this skill, ensure NotebookLM CLI is authenticated:

notebooklm login          # Opens browser for Google OAuth
notebooklm status         # Verify authentication

Workflow

Complete Sync Process

Step 1: Fetch Article Content

Use the web reader MCP tool to fetch the WeChat article:

mcp__web_reader__webReader
URL: <WeChat article URL>
return_format: markdown
retain_images: false (optional, saves bandwidth)

This returns the article content in Markdown format.

Step 2: Save Content to File

Save the fetched content to a temporary Markdown file:

# Extract title from content or use default
# Save to /tmp/<sanitized_title>.md

The file should be saved with a descriptive name based on the article title.

Step 3: Create NotebookLM Notebook

Create a new notebook with the article title:

notebooklm create "<article_title>" --json

Parse the JSON response to get the notebook ID:

{"notebook": {"id": "abc-123-def", "title": "..."}}

Step 4: Upload Article to Notebook

Add the Markdown file as a source to the notebook:

notebooklm source add /tmp/<article_title>.md --notebook <notebook_id> --json

Parse the response to get the source ID:

{"source": {"id": "source-xyz-789", "title": "...", "type": "text"}}

Step 5: Confirm Success

Report to the user:

• Notebook title and ID
• Source file name
• Notebook ID for further use
• Suggested next steps (ask questions, generate podcast, etc.)

Progress Updates

Provide brief, clear status updates:

✅ Fetching article from WeChat...
✅ Converting to Markdown...
✅ Creating notebook "Article Title"...
✅ Uploading to NotebookLM...
✅ Done! Notebook ID: abc-123-def

Output Summary

When complete, provide:

Successfully synced WeChat article to NotebookLM!

📓 Notebook: [Article Title]
   ID: abc-123-def

📄 Source: article_title.md
   ID: source-xyz-789

💡 Next steps:
   - Use: notebooklm use abc-123-def
   - Ask: notebooklm ask "Summarize this article"
   - Generate: notebooklm generate audio "Create a podcast"

Error Handling

Common Issues

1. Article URL is invalid or inaccessible

• Error: Failed to fetch content
• Solution: Verify the URL is correct and accessible
• Alternative: Try copying the article content manually

2. NotebookLM authentication failed

• Error: Auth/cookie error
• Solution: Run notebooklm login again
• Check: notebooklm status to verify

3. File upload failed

• Error: Invalid file or upload error
• Solution: Check if Markdown file was created correctly
• Verify: File path and permissions

4. Notebook creation failed

• Error: Rate limiting or API error
• Solution: Wait a few minutes and retry
• Alternative: Add to existing notebook with --notebook flag

Advanced Features

Add to Existing Notebook

If user wants to add to an existing notebook:

# Get list of notebooks
notebooklm list --json

# Use existing notebook ID
notebooklm source add /tmp/article.md --notebook <existing_notebook_id> --json

Batch Processing

For multiple WeChat articles:

# Create notebook once
notebooklm create "WeChat Articles Collection" --json

# Add multiple articles
for url in "${urls[@]}"; do
  # Fetch, save, upload to same notebook
done

Follow-up Actions

After successful upload, suggest:

For analysis:

notebooklm use <notebook_id>
notebooklm ask "What are the key insights?"
notebooklm ask "Summarize in 3 bullet points"

For content generation:

notebooklm generate audio "Create an engaging podcast"
notebooklm generate video "Make an explanatory video"
notebooklm generate quiz "Test understanding"

For research:

notebooklm source add-research "related topics" --mode deep
notebooklm ask "Compare with other sources"

Limitations

• WeChat articles only: Optimized for mp.weixin.qq.com URLs
• Text content: Focuses on text, images are preserved as links
• Public articles: Requires publicly accessible articles
• Rate limits: NotebookLM has rate limits on uploads

Troubleshooting

Problem: Article content is incomplete

• Cause: WeChat page uses JavaScript rendering
• Solution: web reader tool handles most cases, but some dynamic content may be missed

Problem: Chinese characters display incorrectly

• Cause: File encoding issues
• Solution: Ensure UTF-8 encoding when saving files

Problem: NotebookLM says "Processing" for too long

• Cause: Large articles take time to index
• Solution: Wait 1-2 minutes, then check status with notebooklm source list

Best Practices

1. Use descriptive notebook titles: Extract from article title or topic
2. Keep articles organized: Use separate notebooks for different topics
3. Verify uploads: Check notebooklm source list after upload
4. Clean up temp files: Remove /tmp files after successful upload
5. Handle rate limits: If uploads fail, wait 5-10 minutes before retry

Quick Reference

Task	Command/Tool
Fetch article	mcp__web_reader__webReader
Create notebook	notebooklm create "Title" --json
Upload file	notebooklm source add file.md --notebook <id> --json
Check sources	notebooklm source list --notebook <id> --json
Chat with article	notebooklm use <id>; notebooklm ask "question"
Generate podcast	notebooklm generate audio "instructions" --notebook <id>

Example Usage

User: "Sync this WeChat article to NotebookLM: https://mp.weixin.qq.com/s/xxxxx"

Agent workflow:

1. Fetch article using web reader
2. Save to /tmp/article_title.md
3. Create notebook "Article Title"
4. Upload markdown file
5. Report success with IDs and next steps

Time estimate: 30-60 seconds total