SuperAPI AI Directory

微信读书Skill

Official AI assistant extension capability launched by WeRead

Open website

About this tool

What is WeRead Skill

WeRead Skill is an AI assistant extension capability officially launched by WeRead. After users authorize via API Key, the AI can access private data such as personal bookshelf, reading progress, notes and highlights, enabling intelligent book lookup, habit statistics, note export and personalized recommendations. The tool upgrades WeRead from a passive reading tool to a personalized AI reading partner through natural language interaction.

WeRead Skill

Main features of WeRead Skill

  • Browse bookshelf: The AI browses the user's personal bookshelf in real time, quickly locating books and reading status.
  • Book search: Searches any book within the bookstore, returning key metadata such as title, author and rating.
  • Reading statistics: Quantitatively analyzes reading duration, days, preferred genres and depth, generating visualized habit reports.
  • Book details: Retrieves the chapter directory, reading progress and content summary of a single book, keeping track of the reading journey.
  • Notes and highlights: Searches the user's historical highlights and thoughts, and supports batch export of note files in Markdown format.
  • Recommend good books: Based on personal reading preferences and bookshelf content, generates personalized book lists and similar book recommendations.

How to use WeRead Skill

  • Install Skill: Open the WeRead Skill official website https://weread.qq.com/r/weread-skills , copy the installation command 下载 https://cdn.weread.qq.com/skills/weread-skills.zip 安装 skill, paste it into WorkBuddy and other AI assistant dialog boxes that support Skill, and wait for automatic download and security review to complete.
  • Get API Key: On the WeRead Skill page, click "Log in to WeRead", scan the QR code to log in to your account, and the system will generate an exclusive API Key. Click "Copy Key" for later use.
  • Configure authorization: Send the API Key to the AI assistant, or execute the environment variable command export WEREAD_API_KEY=你的Key and source it to take effect, so that the AI gains permission to read personal reading data.
  • Start using: After authorization is complete, ask the AI assistant questions in natural language to verify whether the Skill is running properly.

Core advantages of WeRead Skill

  • Native data integration: Directly calls the official WeRead interface, with no need for manual export or synchronization, and reading data can be checked in real time.
  • Privacy and security controllable: The API Key is independently generated and managed by the user, data is used only for the current session, and the official gateway does not pass through third parties.
  • Lightweight zero-code deployment: Skill installation can be completed with one command, with no need to write code or configure complex environment variables.
  • Natural language interaction: Operations such as book lookup, statistics and export can be completed through dialogue, lowering the cognitive threshold of reading data management.
  • Note ecosystem compatibility: The export format is standard Markdown, which can be seamlessly integrated into mainstream knowledge management tools, connecting the workflow from reading to note-taking.

Comparison of WeRead Skill with similar competitors

Comparison dimension WeRead Skill Readwise Reader
Data source WeRead official account data Multi-platform aggregation (Kindle, Apple Books, web pages, etc.)
Deployment method AI Assistant Skill Instruction Installation Standalone App/Browser Extension
Interaction Mode Conversational Natural Language Query In-app Annotation and Review
Note Export Markdown Batch Export Official Sync to Notion, Roam, etc.
Recommendation Logic Based on WeChat Reading Bookshelf Preferences Based on Highlighted Content and Reading Frequency
Privacy Mechanism User-authorized API Key Cloud Account Sync Storage

Application Scenarios of WeChat Reading Skill

  • Personal Reading Review: At year-end or quarterly reviews, quickly generate quantitative statistical reports on reading duration, book genres, and progress.
  • Smart Bookshelf Management: When the collection is large, quickly search purchased but unread books and reading progress through natural language.
  • Reading Notes Archiving: Batch export historical highlights and thoughts to Obsidian/Notion to build a personal knowledge base.
  • Precise Booklist Recommendations: Based on existing reading preferences, let AI filter the massive content of the bookstore and generate highly matched to-read booklists.
  • Reading Community Operations: Content creators retrieve personal reading data to quickly organize book review materials and reading insights.