RecSys-Industrial-Book: 《推荐系统:工业架构与核心算法》开源书稿

by jhljx · Agent Tool · ★ 460

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 48/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentagent-skillsagentic-aiagentsaibookclaude-codegenerative-recommendationgenerative-recommendersgpt

Quick Facts

Stars460
Forks31
LanguagePython
CategoryAgent Tool
Quality Score48/100
Last Updated2026-10-18
Created2026-06-07
Platformsclaude-code, python
Est. Tokens~21k

About RecSys-Industrial-Book

RecSys-Industrial-Book 《推荐系统:工业架构与核心算法》开源书稿 AI Agent 使用入口:、 与 。仓库仅从已发布 PDF 在本地临时建立检索索引,不公开 LaTeX 或正文等价 Markdown。 🔖 定位:工业级推荐系统硬核专著,主打全链路系统化思维,拒绝碎片化知识点 🎯 受众:具备机器学习 / 推荐基础的研究生、算法 / 架构 / 策略工程师、技术研究者 ❗ 不适合纯零基础小白(建议先学习机器学习与深度学习入门知识) 💡 创作理念:随着AI的快速发展,写代码门槛已逐步降低。因此本书主要聚焦于系统认知、架构设计、模块协同、工业策略、业务权衡等方面,帮助大家建立一种系统化、模块化的思维。 📦 内容:全书上下册 PDF + 配套可运行代码、实验案例、补充资料(持续更新) 📄 授权:个人学习非商用,转载 / 引用请注明出处 AI Agent 使用...

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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