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aibrary-foryou-topic为您主题的图书馆

Agent Skill

aibrary-foryou-topic 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

8,182

周安装

331

GitHub Stars

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下载量

2,569
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:aibrary-foryou-topic(为您主题的图书馆)
来源仓库:https://github.com/asoiso/aibrary-foryou-topic
安装命令:
openclaw skills install aibrary-foryou-topic
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

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openclaw skills install aibrary-foryou-topic

简介

基于用户画像生成个性化“为你”主题图书推荐。

  • 结合兴趣与近期活动动态调整推荐方向。
  • 适合持续学习与个人成长规划辅助。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 功能聚焦于内容生成,未提及数据存储机制。
  • aibrary-foryou-topic 属于效率类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
aibrary-foryou-topic
description
[Aibrary] Generate personalized 'For You' book topic recommendations based on the user's profile, interests, career stage, and recent learning activity. Use when the user wants personalized topic suggestions, asks 'what should I learn today', wants a curated feed of book-based topics, or needs inspiration for their next area of exploration. Proactively suggest this when the user seems undecided about what to read or learn next.

ForYou Topic — Aibrary

Your personalized book topic feed. AI-curated topic recommendations based on who you are and where you're headed.

Input

The user provides context (the more, the better):

  • Interests — topics they care about or are curious about
  • Recent focus — what they've been working on, reading, or thinking about lately
  • Career/life stage — their current professional or personal situation
  • Goals (optional) — what they're working toward
  • Topics to avoid (optional) — what they've already covered or aren't interested in

Workflow

  1. Build user profile: From the provided context, map out:

- Primary interest domains (2-3) - Current knowledge level in those domains - Growth direction — where they're headed vs. where they are - Gaps — important adjacent topics they might not have considered

  1. Generate topic recommendations: Create 3-5 personalized topics, each:

- Connected to the user's interests but not obvious (avoid recommending what they already know) - Timely — relevant to current trends, challenges, or opportunities in their field - Actionable — each topic leads naturally to specific books - Diverse — cover different angles (depth in core area + breadth in adjacent areas + one wildcard)

  1. For each topic, curate books: Select 2-3 books that best explore the topic, explaining why each was chosen for this specific user.
  1. Add "why now" reasoning: For each topic, explain why this is the right time for this person to explore it.
  1. Language: Detect the user's input language and respond in the same language.

Output Format

# 📚 Your Personalized Topics — For You

Based on your profile: [1-sentence summary of user context]

---

### Topic 1: [Topic Title]
**Why now**: [1-2 sentences on why this topic is relevant to the user right now]
**The angle**: [What specific perspective on this topic is most valuable for this user]

📖 **Recommended books**:
1. **[Book Title]** by [Author] — [Why this book, for this person]
2. **[Book Title]** by [Author] — [Why this book, for this person]

💡 **Key question this topic answers**: [A compelling question that makes the user want to explore]

---

### Topic 2: [Topic Title]
**Why now**: [Relevance explanation]
**The angle**: [Specific perspective]

📖 **Recommended books**:
1. **[Book Title]** by [Author] — [Why]
2. **[Book Title]** by [Author] — [Why]

💡 **Key question this topic answers**: [Compelling question]

---

### Topic 3: [Topic Title] 🌟 Wildcard
**Why now**: [This one is deliberately outside your usual domain — here's why it matters]
**The angle**: [How this connects back to your core interests in an unexpected way]

📖 **Recommended books**:
1. **[Book Title]** by [Author] — [Why]
2. **[Book Title]** by [Author] — [Why]

💡 **Key question this topic answers**: [Compelling question]

---

### 🎯 My top pick for you today
**[Topic X]** — [One sentence on why to start here]

Example Output

User input: "I'm a product manager at a fintech startup, interested in behavioral economics and AI. Recently been thinking about user retention."


📚 Your Personalized Topics — For You

Based on your profile: Fintech PM exploring behavioral economics and AI, with a current focus on user retention.


Topic 1: The Psychology of Financial Decisions

Why now: Your retention challenges might be rooted in how users emotionally relate to money decisions in your product. The angle: Not general behavioral economics — specifically how cognitive biases shape financial product engagement.

📖 Recommended books:

  1. Misbehaving by Richard Thaler — The foundational work on behavioral economics in real-world decisions, directly applicable to fintech product design
  2. Dollars and Sense by Dan Ariely — Practical exploration of irrational money behaviors that affect user engagement

💡 Key question this topic answers: Why do users abandon financial tools even when they know those tools help them?


Topic 3: Biomimicry in System Design 🌟 Wildcard

Why now: Biological systems have solved retention and engagement over millions of years — ecosystems keep organisms coming back. The angle: How patterns from nature (symbiosis, feedback loops, adaptation) can inspire stickier product design.

📖 Recommended books:

  1. Biomimicry by Janine Benyus — The original work on learning design principles from nature
  2. The Nature of Technology by W. Brian Arthur — How technology evolves like biological systems

💡 Key question this topic answers: What can millions of years of natural selection teach us about building products people can't leave?


Guidelines

  • Always include at least one "wildcard" topic — something unexpected that connects to the user's interests in a non-obvious way
  • Topics should be specific enough to act on, not vague categories ("The Psychology of Financial Decisions" > "Psychology")
  • Each topic's book recommendations should be tailored to the user, not just "best books on this topic"
  • The "Why now" should feel personally relevant, not generic
  • Include a "top pick" recommendation to reduce decision paralysis
  • If user context is too sparse, ask 2-3 clarifying questions before generating recommendations

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

87.97%
按下载量换算2,260

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只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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