仓库/Skill 库

Bartosz Milewski《Category Theory for Programmers》非官方 PDF 和 LaTeX 源码Bartosz Milewski's 'Category Theory for Programmers' unofficial PDF and LaTeX source

MLNLP社区用来帮助大家避免论文投稿小错误的整理仓库。 Paper Writing Tips

使用 LaTeX 撰写研究论文的技巧Tips for Writing a Research Paper using LaTeX

使用 LaTeX 撰写科学论文的最佳实践与技巧，图形由 Python 或 Matlab 生成Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.

帮助初学者轻松上手 LaTeX 的简明入门指南。📜 Brief Intro to LaTeX for beginners that helps you use LaTeX with ease.

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

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

"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

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.

走向可复现研究的初步步骤（极简教程）Initial steps toward reproducible research (a minimal tutorial)

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.

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

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.

学习时记录的笔记素材。Materi yang dicatatkan saat belajar

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.

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).

配套仓库：指数族模型主动感知文献综述Companion repository to a literature review on active sensing with exponential family models

本仓库用于存放系统综述 "Colour, Congruence, and Customisation: A Systematic Review of Purchase Intention in Online Fashion Retail" 的全部补充材料This repository is responsible for holding all the additional materials related to the systematic literature review titled: "Colour, Congruence, and Customisation: A Systematic Review of Purchase Intention in Online Fashion Retail"

《从原始数据到完稿论文：构建可复现研究流水线》演讲幻灯片，用于 WHU - Otto Beisheim School of Management 博士迎新周。Slides for 'From Raw Data to Finished Paper: Building a Reproducible Research Pipeline', a Doctoral Orientation Week session at WHU - Otto Beisheim School of Management.

通过系统综述和患者病例场景分析识别潜在药物不良反应（ADR），包括对症状、用药史、剂量及时间线的评估，以确定可疑药物并判断所报告反应是否可能与药物相关。项目展示了基础的 Pharmacovigilance 能力identifying potential Adverse Drug Reactions through systematic review and analysis of patient case scenarios. It includes evaluation of symptoms, medication history, dosage, and timelines to determine the suspected drug and assess whether the reported reaction is potentially drug-related. The project demonstrates basic Pharmacovigilance

本仓库最初是我毕设项目的 PyTorch Lightning 模板，后来演进为包含完整项目实现本身。研究问题是地理定位如何影响遥感视觉-语言模型的训练与推理。注：仓库名称与描述可能变化。This repo originally was a PyTorch Lightning template for my thesis project. It has since evolved to contain the full project implementation itself. The research question is how geolocation influences the training and inference of vision-language models for remote sensing. Note: The repository name and description may change

简介：使用机器学习与数据挖掘技术预测学业表现。技术栈：Python、机器学习、数据科学 AI 研究实验室。教育数据挖掘文献综述、数据集采集与预处理、分类算法实现、模型性能对比、学业成功影响因素分析Description: Predict academic performance using machine learning and data mining techniques Technology: Python, Machine Learning, Data Science AI Research Lab Literature review on educational data mining Dataset collection and preprocessing Implement classification algorithms Compare model performance Analyze factors affecting student success

硕士研究项目中用于统计分析与数据可视化的 R 脚本R scripts used for statistical analysis and data visualisation in my MSc research project.

关于可复现 pipelines 的 capstone workshop：项目结构、环境、Make、containers 与多步 SLURM workflows。Capstone workshop on reproducible pipelines: project structure, environments, Make, containers and multi-step SLURM workflows.

Python 包，通过 MCP、REST 与直接 Python 调用等方式，按 OHDSI 问题模板结构化研究问题。A Python package providing tools (MCP, REST, direct Python calls) for structuring research questions according to the OHDSI question templates.

Markdown 学术写作工作流：一篇以 Markdown 纯文本示例论文阐述写作流程，同时作为学习与脚手架项目。Markdown Academic Writing Workflow, an example paper talking about the writing workflow with Markdown plain text file, served as a learning and a scaffolding project at the same time.

多阶段现代控制项目：非等温 CSTR 反应器的建模、分析与控制Multi-phase modern control project: modelling, analysis, and control of a non-isothermal CSTR reactor.

本文件夹包含一系列研究问题及用于回答这些问题的 Python 实验。This folder contains a series of research questions and Python experiments designed to answer those questions.