仓库/Skill 库

系统综述与论文清单：探索面向代码的 LLM 中数据与代码质量问题的映射、检测与治理。Systematic review and paper list exploring the mapping, detection, and governance of data and code quality issues in Large Language Models for Code.

自主 AI 平台，提供端到端的学术研究辅助——从论文发现到生成结构化文献综述，以及识别研究空白。An autonomous AI platform that performs end-to-end academic research assistance — from discovering papers to generating structured literature reviews and identifying research gaps.

基于 Zotero 的文献综述助手，支持基于原文的 PDF 抽取、声明验证、内容综合及 Semantic Scholar 检索Zotero-based literature review assistant for grounded PDF extraction, claim verification, synthesis, and Semantic Scholar search.

利用 LLM 提示词、证据链接笔记、Excel 跟踪与跨论文综合，从 PDF 自动生成博士文献综述Automate PhD literature reviews from PDFs with LLM prompts, evidence-linked notes, Excel tracking, and cross-paper synthesis.

自托管语义代码搜索。将代码仓库和知识源索引至本地向量数据库，然后通过 CLI 或任何 MCP 兼容 Agent 进行自然语言搜索。Self-hosted semantic code search. Index repos and knowledge sources into a local vector DB, then search by natural language from CLI or any MCP-compatible agent.

后端无关的 C# 库，用于构建有状态 AI 实体，具备按角色记忆、工具调用、情绪系统和自主 Agent 行为。Backend-agnostic C# library for building stateful AI entities with per-persona memory, tool access, mood systems, and autonomous agent behavior.

自动化并规模化 "LLMs as a participant"，将 LLM 作为研究参与者Automates and scales "LLMs as a participant."

自托管 AI 知识 Agent —— TypeScript、Bun、MCP。掌控你的数据，运行你自己的大脑。Self-hosted AI knowledge agent — TypeScript, Bun, MCP. Own your data, run your own brain.

Dust：一款受 React/Vue 启发的现代化、组件化 Dart Web 框架，基于 WebAssembly（WASM）构建，具有高性能与流畅的开发体验，可使用 Dart 构建健壮、类型安全的 Web 应用。Dust: A modern, component-based Dart web framework inspired by React/Vue. Built with WebAssembly (WASM) for high performance and a seamless developer experience. Create robust, type-safe web applications with the power of Dart.

AI 编码 Agent 的自动驾驶仪，支持 OpenCode、Claude Code、pi.dev、Cursor 等多种工具。Autopilot for AI Coding Agents, supports OpenCode, Claude Code, pi.dev, Cursor, and many more

面向 AI 编码 Agent 的 IDE 智能，集成 LSP 语义、tree-sitter 索引、项目记忆和并发安全编辑。IDE intelligence for AI coding agents, with LSP semantics, tree-sitter indexing, project memory, and concurrency-safe edits.

原生 LaTeX 的修订追踪，面向人类与 AI 辅助审阅。LaTeX-native track changes for human and AI-assisted review

面向 Model Context Protocol 服务器的 OWASP MCP Top 10 安全扫描器OWASP MCP Top 10 security scanner for Model Context Protocol servers

可自托管且功能丰富的视频库Self-hostable and feature-rich video library

为你的 AI 编程助手打造的持久记忆。它会记住你告诉它的内容，并在恰当时机把对应的笔记交还。本地机器全量运行。A memory for your AI coding assistant. It keeps what you tell it and hands the right note back at the moment it matters. Runs entirely on your own machine.

为 AI 编码 Agent 提供的本地文档镜像——自动同步，与索引器无关。Local docs mirror for AI coding agents — auto-synced, indexer-agnostic.

🤖 CareerForge AI 自动化求职：生成简历、分析职位描述、提供面试辅导，助力职业成功🤖 Automate your job search with CareerForge AI, building resumes, analyzing job descriptions, and providing interview coaching for career success.

大语言模型元数据的开放注册表——以单一机器可读的 models.json 提供身份、作者、模态、上下文/输出限制、能力与生命周期日期，并通过 JSON Schema 校验。CC BY 4.0Open registry of large-language-model metadata — identity, authorship, modalities, context/output limits, capabilities & lifecycle dates as one machine-readable models.json validated by JSON Schema. CC BY 4.0.

MendCode：可定制的 CLI，面向 agent、团队、记忆、评审与 TUI。MendCode: Customizable CLI for agents, teams, memory, reviews, and TUI.

面向多 Agent 工作流的 MCP 协调原语。LLM 无关、CLI 无关、可自托管。TypeScript + SQLite。MCP coordination primitive for multi-agent workflows. LLM-agnostic, CLI-agnostic, self-hostable. TypeScript + SQLite.

确定性的 MCP 安全架构。以 FrozenNamespace 作为 Model Context Protocol 工具验证的可信根（Root of Trust）。Deterministic MCP Security Architecture. FrozenNamespace as Root of Trust for Model Context Protocol tool verification

用于评估检索增强视觉语言模型在循证医学视觉问答中表现的研究框架Research framework evaluating retrieval-augmented vision-language models for evidence-grounded medical visual question answering.

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.

🛠️ 使用 Sherlock AI Plugin 将研究论文转化为可执行代码，是你高效进行文献综述与实现工作的必备工具。🛠️ Transform research papers into executable code with Sherlock AI Plugin, your essential tool for efficient literature review and implementation.

A field-adaptive academic writing Skill for Chinese and English research papers. | 面向中英文学术论文的领域自适应写作 Skill。

支持从多源智能检索、筛选与总结科学论文，提升研究与报告生成效率Enable intelligent retrieval, filtering, and summarization of scientific papers from multiple sources for efficient research and report generation.

🐙 通过 Python 与 PyTorch 实战代码深入理解 LLM 内部机制，掌握 LLM 架构、训练及核心原理。🐙 Explore the inner workings of large language models with hands-on Python and PyTorch code. Master LLM architecture, training, and mechanisms for AI systems.

实时更新的向量数据库项目、集成和基准评测全景图——每……刷新。Live-updating landscape of vector database projects, integrations, and benchmarks — refreshed every

GitHub 上 MCP server 的自动更新索引，每 15 分钟刷新一次。Auto-updated index of MCP servers shipping on GitHub, refreshed every 15 minutes

GitHub 上最新 Agent 框架的实时索引，按发布时间而非 star 数排序。Live index of the newest agent frameworks shipping on GitHub, sorted by recency not stars

在 LIBERO 与 RoboTwin2.0 上，基于状态融合解码与冻结视频骨干网络训练面向机器人操作的轻量级世界动作模型。Train lightweight world action models for robot manipulation using state-fusion decoding and frozen video backbones on LIBERO and RoboTwin2.0.

自托管、多用户转录平台：录制或上传音频。支持说话人标记、带时间戳的转录、跨录音识别说话人、摘要、提取行动项，并可使用自有 OpenAI 兼容 LLM 与转录内容对话。你的音频、你的服务器、你的模型。已在笔记本 RTX4070、台式机 RTX3090 与 RTX5090 上测试。Self-hosted, multi-user transcription platform: record or upload audio. Speaker-labeled, timestamped transcripts, Recognize speakers across recordings, Summarize, extract action items and chat over your transcripts with your own OpenAI-compatible LLM. Your Audio, your Server, your Model. Tested on Laptop RTX4070, Desktop RTX3090 and RTX5090

通过用于获取 arXiv 论文、提取技术细节与跟踪引用的研究 Skill，为 Agent 工作流自动化文献综述。Automate literature reviews with research skills for fetching arXiv papers, extracting technical details, and tracking citations for agent workflows.

自动化科研 AI 系统的精选枢纽：覆盖文献综述、调研综合、实验设计与执行、论文写作、AI 科学家与自主研究 AgentA curated hub for AI systems that automate scientific research: literature review, survey synthesis, experiment design and execution, paper writing, AI scientists, and autonomous research agents.

通过 MCP 让任意 AI agent 在你真实已登录的 Chrome 中拥有"眼睛"和"双手"。零依赖。Give any AI agent eyes and hands in your real, logged-in Chrome — via MCP. Zero dependencies.