huashu-weread-advisor

Transform Weread shelves and notebooks into personalized reading advice.

134|7|Updated May 17, 2026

Search Tags:#advisor #knowledge-mapping #weread #book-recommendations #note-synthesis #reading-workflows #reading-planning

Ready to run

npx skills add https://github.com/alchaincyf/huashu-weread --skill huashu-weread-advisor

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: huashu-weread-advisor
Source: https://github.com/alchaincyf/huashu-weread/tree/main
Command: npx skills add https://github.com/alchaincyf/huashu-weread --skill huashu-weread-advisor

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

微信读书高阶顾问在底层 Weread skill 的原子 API 之上，提供四类工作流：advisor、path、alchemy、review。通过书架与笔记的交叉分析，识别“真读过”的书与主动归类的兴趣，输出个性化书单、系统学习路径、笔记提炼和复盘文章，帮助用户提升阅读效率与决策质量。

Core Features & Use Cases

Advisor: 基于已读和笔记，给出个性化书单和下一步阅读方向。
Path: 提供从入门到前沿的阶梯书单，帮助系统学习新领域。
Alchemy: 将划线与想法结构化，生成可复用的读书笔记。
Review: 产出可分享的季度/年度读书复盘，适合朋友圈/公众号。
Use Case: 当用户说“下一本读啥”“整理我的笔记”或“我今年读了什么”时，自动路由到对应工作流并给出可执行输出。

Quick Start

请告诉我你需要的输出，如“下一本读啥”或“规划一个领域的学习路径”，以触发相应的工作流。

Frequently Asked Questions about huashu-weread-advisor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I get personalized book recommendations from my Weread history?▼

Weread book recommendations are generated by cross-analyzing your bookshelves and notebooks to identify actively read books and categorized interests. The advisor workflow routes this data to output personalized book lists and next reading directions.

What is the best way to build a systematic learning path for a new domain using Weread?▼

Building a systematic learning path uses the path workflow to generate laddered book lists from introductory to frontier texts. It structures your domain learning progression by sequencing reading materials based on your Weread shelf data.

Can I synthesize my Weread highlights and notes into structured reading summaries?▼

Yes, you can synthesize Weread highlights into structured summaries using the alchemy workflow. It transforms your underlines and ideas into reusable reading notes by applying data-driven routing to ensure structured, actionable outputs.

How do I generate a quarterly or yearly reading retrospective from my Weread data?▼

Generating a reading retrospective uses the review workflow to process your Weread shelves and notebooks. It produces shareable quarterly or yearly review articles suitable for social media platforms or personal blogs.

Does the Weread reading advisor work without manually categorizing my bookshelves?▼

Yes, the Weread reading advisor works without manual categorization by cross-analyzing shelf and notebook data to automatically identify actively read books and active interests. It implements robust error handling to ensure safe, actionable outputs.