仓库/Skill 库

集成 ChatGPT web 与 Codex，用于 Agentic 编码工作流：ChatGPT 负责思考，Codex 负责执行，以节省 Codex 用量配额。Integrates ChatGPT web and Codex for agentic coding workflows ChatGPT thinks, Codex executes for saving Codex usage limits.

受 MemGPT 启发、支持 OpenAI API 的长期记忆 Agent，具备记忆生命周期控制与评估能力。MemGPT-inspired long-term memory agent with OpenAI API support, memory lifecycle controls, and evaluation.

针对任意 GitHub 仓库的自然语言问答 —— 构建 Neo4j 依赖图与 Qdrant 向量索引，用自然语言即可提问结构性与行为性问题。Natural-language Q&A over any GitHub repo — builds a Neo4j dependency graph + Qdrant vector index so you can ask structural and behavioral questions in plain English

受治理的持久化 AI worker，配备默认拒绝权限、人工审批、dry-run 以及经过认证的 MCP。Governed persistent AI workers with default-deny authority, human approvals, dry-runs, and an authenticated MCP.

基于 CrewAI 的 Agent 系统，用于辅助研究者围绕特定高层级研究问题定义研究项目与假设。This is a CrewAI agent system set up to assist a researcher with defining research projects and hypotheses for a specific high-level research question.

企业级 Java AI Agent 任务编排、安全审批、RAG 与全链路审计平台

AI Coding Memory MCP 2026：用于持久化 Sprint 与决策管理的 20 个工具。AI Coding Memory MCP 2026: 20 Tools for Persistent Sprint & Decision Management

多 Agent AI 研究助手——由多个专门化 Agent 协作，自动检索论文、总结发现、对比方法、生成文献综述并产出可演示的内容Multi-Agent AI Research Assistant — An AI-powered research automation system where multiple specialized agents collaborate to search research papers, summarize findings, compare methodologies, generate literature reviews, and create presentation-ready content.

使用多 Agent RAG 系统与混合索引、LangGraph 编排，自动获取 arXiv 研究论文并生成文献综述。Automate arXiv research paper retrieval and literature review generation using a multi-agent RAG system with hybrid indexing and LangGraph orchestration.

基于已验证决策构建的共享 intelligence 层。A shared intelligence layer built from verified decisions.

面向市场、产品、GTM、定价、增长与高管战略的精选 AI Agent Skill。Curated AI-agent skills for market, product, GTM, pricing, growth, and executive strategy.

面向 Agentic Dynamics 的实验工具：衡量 AI Agent 如何行为、恢复并产出已验证的结果Experimental instrument for Agentic Dynamics: measuring how AI agents behave, recover, and produce verified outcomes

本地、开源的推理框架，支持 Claude 和 Codex，包含 48 个编写好的系统，仅在需要更深层推理时选用。Local, open-source reasoning framework for Claude and Codex, with 48 authored systems selected only when deeper reasoning helps.

基于 LangGraph、LangChain、Groq 和 Tavily 构建的多步骤研究 Agent。分解复杂的研究问题，执行迭代式网络研究，评估证据，并生成结构化的最终报告。Multi-Step Research Agent built with LangGraph, LangChain, Groq, and Tavily. Decomposes complex research questions, performs iterative web research, evaluates evidence, and generates a structured final report.

有界研究 Agent：plan → retrieve → critique，具备步骤预算、执行轨迹、引用追溯与自由路径 UI，无需 API key。Bounded research agent: plan → retrieve → critique, step budgets, traces, citations, free-path UI. No API key.

面向中英双语生物医学研究的术语循证、主张强度与科学写作审计 skill。Evidence-aligned terminology, claim-strength, and scientific-writing audit skill for Chinese and English biomedical research.

在 Claude 中强制以引用优先的研究流程，通过结构化五阶段工作流验证事实、识别不确定性并消除幻觉。Enforce citation-first research with Claude to verify facts, identify uncertainty, and eliminate hallucinations through a structured five-phase workflow.

🔧 通过灵活的 prompt 模板与任务规范项目简化 AI Agent，实现高效的指令与记忆管理。🔧 Streamline AI agents with this flexible prompt template and task specification project for effective instruction and memory management.

一款 Specs AR 眼镜，可读取房间风水、进行评分、用 AI 重新渲染，并给出整改清单。基于 CLAD（Claude + Lens Studio MCP）构建。A Specs AR Lens that reads your room's feng shui, scores it, repaints it with AI, and gives you a checklist to fix it. Built with CLAD (Claude + Lens Studio MCP).

Autonomous AI Algorithm Discovery Laboratory：一个有边界、可复现的研究平台，在固定算力预算下提出、实现、测试、拒绝、改进并报告 AI 系统的候选改进方案。Autonomous AI Algorithm Discovery Laboratory: a bounded, reproducible research platform that proposes, implements, tests, rejects, refines, and reports candidate improvements to AI systems under a fixed compute budget.

📰 Spec-driven daily briefings on Claude Code cloud Routines — git as the only state, zero servers, zero API keys | 用 Claude Code Routines 每天自动生成主题简报，git 即全部状态，零服务器零密钥

可复现的研究流水线：将基于 Agent 的模型产出转化为有证据支撑的 LLM 高管报告。A reproducible research pipeline for converting agent-based model artifacts into evidence-backed LLM executive reports.

面向编码 Agent 的本地运行时，以合并质量为优化目标：由仓库自适应常驻模型生成补丁，大模型进行验证。单进程同时支持 Anthropic + OpenAI API，天生离线运行。A local coding-agent runtime that optimises for merge quality: a repo-adapted resident model generates patches, a large model verifies them. Anthropic + OpenAI APIs from one process, offline by construction.

向 Mac 上的 AI 编码 agent 展示 iOS 应用的实际运行状态——屏幕画面、应用内部状态、网络流量与日志，让检查 UI 变更不再依赖手动点击和截图循环。Shows what your iOS app is actually doing — the screen, the app's own state, its network traffic and its logs — to an AI coding agent on your Mac, so checking a UI change stops being a manual tap-and-screenshot loop.

关于 AI Agent 系统与编排的定向研究与文献综述的最终交付成果Final deliverables for directed studies and literature review on AI Agent Systems and Orchestration

将 OpenCode 转变为可复现的研究工具Turn OpenCode into a reproducible research instrument.

生产级 multi-agent 系统：接收研究问题、制定调查方案、从实时网络和私有文档语料中收集证据、对自身发现进行批判与事实核查，最终输出完整引用的 Markdown 报告。A production-grade multi-agent system that accepts a research question, plans an investigation, gathers evidence from the live web and a private document corpus, critiques and fact-checks its own findings, and delivers a fully cited Markdown report.

大语言模型（LLM）是一种人工智能（AI）程序，能够识别并生成文本，以及执行其他任务。A large language model (LLM) is a type of artificial intelligence (AI) program that can recognize and generate text, among other tasks.

AI agent 辅助学术论文写作。An AI agent supports writing academic papers

基于 TypeScript 的独立框架，通过统一原语 Component 组合安全的个人 AI agent：manifest-first 发现、能力授予、正交模型路由与信息流控制。Standalone TypeScript framework for composing secure personal AI agents from one universal primitive — the Component. Manifest-first discovery, capability grants, orthogonal model routing, and information-flow control.

Yaroslav Vasylenko —— AI 系统、验证工程、可复现研究与 agentic workflows。Yaroslav Vasylenko — AI systems, verification engineering, reproducible research, and agentic workflows.

成本感知的 GitHub Copilot 工作流，用于清晰、有界且经过独立评审的软件变更。Cost-aware GitHub Copilot workflows for clarified, bounded and independently reviewed software changes.

追踪并比较每一个严肃的 OpenClaw 替代方案——基于实测仓库数据与 AI 撰写的决策支持，且刻意保持独立。Track and compare every serious OpenClaw alternative — measured repo data, AI-written decision support, kept apart on purpose.

Adobe Experience Manager 的 W3C WebMCP 集成 — 通过 navigator.modelContext 让浏览器 AI agent 可发现并调用 AEM Core Components。W3C WebMCP integration for Adobe Experience Manager - makes AEM Core Components discoverable and callable by browser AI agents via navigator.modelContext

lq 是面向 AI Agent 的独立 CLI 工具，用于解析、查询与修改 LyX 文档lq is a standalone CLI tool designed for AI agent to parse, query, and mutate LyX documents.

基于证据的论文检索与推荐 Agent，面向复杂研究问题。Evidence-grounded paper search and recommendation agent for complex research questions.