114 个 · 教程
8 个 Claude Skill · 100+ 侦察能力 · 80 条 secret-regex 模式 · 80+ dorks · 9 个只读凭据验证器 · 27 个攻击路径模板 · 约 10,000 行结构化技术内容。开箱即用的 SKILL.md 文件，可将 Claude 改造为面向授权红队与漏洞赏金项目的顶级外部侦察操作员。8 Claude skills · 100+ recon capabilities · 80 secret-regex patterns · 80+ dorks · 9 read-only credential validators · 27 attack-path templates · ~10,000 lines of structured tradecraft. Drop-in SKILL.md files that turn Claude into a god-mode external recon operator for authorized red-team and bug-bounty engagements.
《构筑大语言模型应用：应用开发与架构设计》一本关于 LLM 在真实世界应用的开源电子书，介绍了大语言模型的基础知识和应用，以及如何构建自己的模型。其中包括Prompt的编写、开发和管理，探索最好的大语言模型能带来什么，以及LLM应用开发的模式和架构设计。
一套开箱即用的 Claude Code 学术模板，基于 LaTeX/Beamer + R，支持多 Agent 评审、质量门禁、对抗式 QA 与复现协议。A ready-to-fork Claude Code template for academics using LaTeX/Beamer + R. Multi-agent review, quality gates, adversarial QA, and replication protocols.
Prompt工程师指南，源自英文版，但增加了AIGC的prompt部分，为了降低同学们的学习门槛，翻译更新
面向Apple开发者文档的MCP服务器——在Claude、Cursor及AI助手中检索iOS/macOS/SwiftUI/UIKit文档、WWDC视频、Swift/Objective-C API及代码示例MCP server for Apple Developer Documentation - Search iOS/macOS/SwiftUI/UIKit docs, WWDC videos, Swift/Objective-C APIs & code examples in Claude, Cursor & AI assistants
Claude Code Skill Factory——一个强大的开源工具包，用于大规模构建和部署生产级 Claude Skills、Code Agent、自定义斜杠命令和 LLM Prompts。可轻松生成结构化的 skill 模板、自动化工作流集成，以简洁、开发者友好的配置加速 AI Agent 开发。Claude Code Skill Factory — A powerful open-source toolkit for building and deploying production-ready Claude Skills, Code Agents, custom Slash Commands, and LLM Prompts at scale. Easily generate structured skill templates, automate workflow integration, and accelerate AI agent development with a clean, developer-friendly setup.
www.flydean.com 的源码，AIGC,人工智能,JAVA,前端全领域覆盖,定期分享学习心得和经验,帮助大家少走弯路。觉得有帮助的话,给我点个star吧!
Anthropics/skills中文学习版本 来自：https://github.com/anthropics/skills
Best AI Humanizer Handbook——一份让 AI 辅助写作更清晰、更可信、更具人文气息的实用指南Best AI Humanizer Handbook A practical guide to making AI-assisted writing clearer, more credible, and more human
"Humanizer" 规则集，让 AI 文本更锐利、具备 genre 感知能力，包含具体锚点与 self-auditing 工作流"Humanizer" rules that make AI text sharper, genre-aware, with concrete anchors and self-auditing workflow
在两台 dgx-spark 上从零部署 deepseek-flash-0731 的设置指南。setup guide for deepseek-flash-0731 on two dgx-spark from scratch
使用 AI 的系统文献综述（SLR）借助人工智能技术，自动加速海量学术文献的审阅与综合过程Systematic Literature Review (SLR) using AI involves leveraging artificial intelligence techniques to automate and expedite the process of reviewing and synthesizing large volumes of scholarly literature.
Obsidian.md 是一款专为学术写作打造的出色笔记应用。本仓库是"使用 AI 进行系统文献综述"研讨会活动的组成部分。Obsidian.md stands out as an exceptional note-taking application tailored specifically for academic writing. This repository is part of the activities for the Systematic Literature Review using AI workshop.
本课程涵盖从初始想法到正式学术写作的开发流程与实现要点。学生将学习如何转化与消化文献综述，从而凝练出拟定的研究题目。This course will cover the fundamental steps and implementation on developing the initial ideas to formal academic writing accordingly. Students will be given the mechanisms on how to transform and digest the literature reviews that leads to the proposed title.
Meta Inc. 所有 oss 模型的相关 recipes。All recipes for oss models from Meta Inc.
走向可复现研究的初步步骤（极简教程）Initial steps toward reproducible research (a minimal tutorial)
面向 agent 的纯数学工具：搜索实例与反例，进行精确计算，并独立验证结论所证内容。Pure mathematics for agents: search for examples and counterexamples, compute exactly, and independently check what a result proves.
自动更新的开源知识库，面向 AI Agent、RAG 系统、MCP server、prompt、tool、模板以及新一代 Web 开发。An auto-updating open-source vault for AI agents, RAG systems, MCP servers, prompts, tools, templates, and next-generation web development.
一个以证据为引领的六语种 LLM 实战手册：包含可迁移的核心、Codex 旗舰路线，以及 ChatGPT、Claude Code、Gemini、DeepSeek 和 Grok 的适配器。An evidence-led, six-language LLM playbook: the transferable core, the Codex flagship track, and adapters for ChatGPT, Claude Code, Gemini, DeepSeek, and Grok.
可复现研究仓库的 GitHub 模板 —— 两层 Python 3.10+/uv monorepo，将通用基础设施与项目级代码分离，配有 pytest 覆盖率门禁（基础设施 60%、项目 90%）、16 阶段构建流水线、通过 pandoc/LaTeX 实现的 Markdown 转 PDF 渲染，以及 25 个标准示例。GitHub template for reproducible research repos — two-layer Python 3.10+/uv monorepo splitting generic infrastructure from per-project code, with pytest coverage gates (60% infra, 90% projects), a 16-stage build pipeline, markdown-to-PDF rendering via pandoc/LaTeX, and 25 canonical exemplars.
🚀 掌握 prompt engineering，通过指南、示例与最佳实践优化 AI 交互，覆盖各技能水平与应用领域。🚀 Master prompt engineering to optimize AI interactions with guides, examples, and best practices for all skill levels and domains.
在研究全球干旱状况的同时实践可复现研究方法的项目A project to practice reproducible research practices while studying the state of drought around the world
微调、评估、提示工程、开源模型Fine-tuning, evaluation, prompting, open-source models
🚀 通过 70 个生成式 AI 实战项目转型技能，从入门到生产级架构师，涵盖真实场景应用。🚀 Transform your skills with 70 hands-on projects in Generative AI, guiding you from beginner to production-ready architect with real-world applications.
builderr.ai 交易 Agent 模板——fork 后实现 decide()，即可提交。Trading agent template for builderr.ai — fork this, implement decide(), submit.
通过真实工作流学习实践可复现研究的 R 开放教材An open educational textbook for learning reproducible research in R through practical, real-world workflows.
AI 工程路线图 2026 🚀 | 从零构建并部署 AI 应用。AI Engineering Roadmap 2026 🚀 | Build & Deploy AI Apps from Scratch
一个可运行的 TypeScript 教程，从零搭建一个极简 DeepSeek 风格 Agent 框架。A runnable TypeScript tutorial that builds a minimal DeepSeek-style agent harness from scratch.
The Research Mind R Course 2026 涵盖 R 编程基础、统计分析与可视化。学习搭建 R 环境、编写函数、组织项目、执行检验（T-test、ANOVA）以及绘制图表。适合 data science 和 bioinformatics 方向。通过克隆仓库并浏览各课时即可开始。The Research Mind R Course 2026 covers R programming basics, statistical analysis, and visualization. Learn to set up R, write functions, organize projects, perform tests (T-test, ANOVA), and create plots. Ideal for data science and bioinformatics. Get started by cloning the repository and exploring the sessions.
使用 HTML 和 CSS 构建简洁、风格化的网站，配备响应式布局、导航与现代设计，提升用户参与度🌐 Build a simple, stylish website using HTML and CSS, featuring a responsive layout, navigation, and a modern design for easy user engagement.
GenAI 职业路线图 2026 🚀 | AI 岗位路径与技能指南GenAI Career Roadmap 2026 🚀 | AI Job Paths & Skills Guide
AutoScientists：确定性的多 agent 科学发现协调框架 —— docxology/template 可复现研究范式的公开范例（测试覆盖率 ≥90%，无 mock，GitHub 与 Zenodo 10.5281/zenodo.20533669 双重发布）。AutoScientists: a deterministic multi-agent scientific-discovery coordination harness — public exemplar of the docxology/template reproducible-research paradigm (≥90% test coverage, no mocks, double-published GitHub + Zenodo 10.5281/zenodo.20533669).