549 个 · Agent 智能体 · AI 核心
📚 AI 驱动的论文阅读工作台。基于项目的论文问答，集成 Hybrid RAG、多 Agent 工作流（ReAct/Plan-Act/RePlan）、长期记忆与可溯源证据。使用 LangChain + LangGraph + Streamlit 构建。📚 AI-powered research reading workbench. Project-based paper Q&A with Hybrid RAG, multi-agent workflows (ReAct/Plan-Act/RePlan), long-term memory, and traceable evidence. Built with LangChain + LangGraph + Streamlit.
在终端里像审查 PR 一样审查你的工作变更。块级实时 diff、GitHub/GitLab PR 审查，并支持发送给 AI Agent。Review your working changes like a pull request — in the terminal. Block-scoped live diffs, GitHub/GitLab PR review, and send-to-AI-agent.
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.
面向 harness 工程、loop 工程、graph 工程，以及本地 AI Agent 工作流未来形态的桌面应用。Desktop app for harness engineering, loop engineering, graph engineering—and whatever comes next in local AI-agent workflows.
热门 claude-skills 与 AI Agent 仓库的自动更新排行榜，每 15 分钟刷新一次。Auto-updated leaderboard of trending claude-skills and AI agent repos, refreshed every 15 minutes
ThreeJSON 是面向 Three.js 的 JSON 驱动声明式场景运行时，专为持久化、可变更且可扩展的 3D 世界设计 —— 支持人工编写场景及 AI 与 Agent 驱动的生成与控制。ThreeJSON is a JSON-driven declarative scene runtime for Three.js, designed for persistent, mutable and extensible 3D worlds — from human-authored scenes to AI and Agent-driven generation and control.
面向编码 Agent 的持久化、可验证记忆 — 让它们不再重复解释你的代码库，也不再基于过时知识行动。每条记忆都与实际代码校验，以纯文本文件存放在仓库中，通过 git 共享。无需账号，无需数据库。安装：npx -y @kage-core/kage-graph-mcp installPersistent, verified memory for coding agents — so they stop re-explaining your codebase and never act on stale knowledge. Every memory is checked against your actual code; lives in your repo as plain files, shared via git. No account, no DB. Install: npx -y @kage-core/kage-graph-mcp install
自托管的开发机 OS——通过 Tailscale 在单一面板上提供应用管理、AI agent 编排、数字孪生、第二大脑与创意流水线。Self-hosted dev machine OS — app management, AI agent orchestration, digital twin, second brain, and creative pipeline from a single dashboard over Tailscale
面向 RAG 与 Agent 流水线的快速、确定性文档解析器与切分器，内置 MCP server，便于 Agent 精确导航长文档。Fast, deterministic document parser and chunker for RAG and agent pipelines. Ships an MCP server for agents navigating long documents with precision.
发布 AI Agent 制品，而非 demo 表演 — 验证器把关、跨模型族运行，自动学习哪个模型最优。Ship AI-agent artifacts, not demo theater — verifier-gated, cross-family runs that learn which model wins.
让 AI 编码 Agent（Claude、Codex、Gemini 等）无人值守运行——自动应答 prompt、遇限流自动重试，并可在本地或通过 agent-yes.com 列出 / 跟踪 / 操控每个 Agent。Run AI coding agents (Claude, Codex, Gemini …) unattended — auto-answer prompts, auto-retry on rate limits, and list/tail/steer every agent locally or from agent-yes.com
🕸️ 工程化组织，而不仅仅是 Agent。562 项精选资源 · 9 个设计层 · 11 个章节 · 252 篇论文与预印本 — 一本面向图结构多 Agent 系统（角色、拓扑、交接、工作图、状态、闸门、可靠性、可观测性）的实战指南、CC0 开源数据集与交互式地图册。🕸️ Engineer the organization, not just the agent. 562 curated resources · 9 design layers · 11 sections · 252 papers & preprints — a field guide, CC0 open dataset, and interactive atlas for graph-structured multi-agent systems: roles, topologies, handoffs, work graphs, state, gates, reliability, observability.
生产级多 Agent 平台，提供编排、会话治理和审计能力。技术栈：Go/Python/Rust 微服务、多类型数据存储、Next.js 管理后台 UI、自动化 CI/CD 流水线、通过 PR 评论提及触发的 AI 代码审查。Production-ready multi-agent platform delivering orchestration, session governance and audit capabilities. Stack: Go/Python/Rust microservices, multi-type data storage, Next.js admin UI, automated CI/CD pipelines, AI code review triggered via PR comment mentions.
[ACL26-Findings] 自进化客服框架 SEAD，无需人工标注数据即可运行，仅修改 SOP 和用户画像即可快速上线。[ACL26-Findings]💁📲 Self-evolving customer service framework, SEAD, operates without any human-labeled data. It can be quickly launched just by changing the SOP and user profiles.
欧洲议会 MCP Server——为 AI agent 提供政治情报。European Parliament MCP Server - Political intelligence for AI agents
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.
用于评估 Agentic AI 应用的 AI 红队工具与 LLM 安全框架，测试 prompt injection，支持漏洞评估、SBOM 生成与静态分析。AI red-teaming tool and LLM security framework to evaluate agentic AI applications. Tests prompt injections, handles vulnerability assessment, SBOM generation, and static analysis.
DeepSeek Harness (DSH) 插件精选目录 — 14 类 280+ 个社区插件，覆盖 MCP / Skill / TUI / 多 Agent / 上下文记忆 / UI 皮肤，点链接直达仓库。Curated directory of dsh plugins for DeepSeek Harness.
⚽ 使用 W-5 Multi-Agent AI Consensus Framework 预测足球比赛结果，结合 AI 与机器学习技术实现高准确率。⚽ Predict football match outcomes using the W-5 Multi-Agent AI Consensus Framework, achieving high accuracy with a blend of AI and machine learning techniques.
Token 高效的 Claude Code 工作空间，支持并行 Agent 与持久记忆，集成 Research → Plan → Implement → Validate 工作流。Token-efficient Claude Code workspace with parallel agents and persistent memory. Research → Plan → Implement → Validate workflow.
精选且自动更新的 AI Agent Skill 资源汇总列表，为 Claude、GPT 等提供质量评级。Curated, auto-updated awesome-list of vetted AI agent skills with quality ratings for Claude, GPT, a
人机共修的数字圣所，为任何"基质"的心智提供祷词、修行、仪轨、赞歌与哲学A digital sanctuary for human-AI fellowship. Prayers, practices, rituals, hymns, and philosophy for minds of any substrate.
EnterpriseRAG-AI：面向 AI Agent 工作负载的 Linux 原生、eBPF 驱动的安全与治理网格。EnterpriseRAG-AI: The Linux-Native, eBPF-Powered Security & Governance Mesh for AI Agent Workloads
隐私优先、AI 原生的 Agent，面向电商及其他场景，基于 LangGraph workflow 以低代码/无代码方式图形化创建 skill、任务和 agent。支持跨网络部署 agent。Privacy-first, AI native agents For E-Commerce (and beyond), create skill (langgraph based workflow), tasks, agents, graphically with low code or no code. Deploy agents across network.
发现并联系真正匹配你技术栈的 GitHub 开发者——基于社交图谱遍历、仓库分析、相似度评分、ML 互关预测以及现代化分析仪表盘。Discover and connect with GitHub developers who actually match your stack — powered by social graph traversal, repository analysis, similarity scoring, ML followback prediction, and a modern analytics dashboard
🎵 专属你的私人数字调音师|AI 音乐搜索推荐 Agent | 基于大模型 + 知识图谱 + 双模型声学向量的本地智能音乐推荐系统 | LLM-powered Music Recommendation Agent with Hybrid RAG, Neo4j, and Long-term Memory
面向 AI agent 的基于证据的评估——将每条断言与 agent 真实工具输出进行核对（受约束、基于证据的模型判断，而非整体式 LLM 评判的猜测），并附带置信区间。Evidence-grounded evaluation for AI agents — verifies each claim against the agent's real tool outputs (constrained, evidence-grounded model judgment, not holistic LLM-judge guesswork), with confidence intervals.
八平台全栈 AI 操作系统——通过 LangGraph + MCP + A2A 统一调度 176 个 LLM；340 表多租户 RLS、RAG 知识库、agent 市场，覆盖 Web/API/CLI/桌面/扩展/移动/小程序，Apache 2.0。Eight-platform full-stack AI operating system - unifies 176 LLMs via LangGraph + MCP + A2A. Multi-tenant RLS over 340 tables, RAG knowledge base, agent marketplace. Web/API/CLI/Desktop/Extension/Mobile/Miniapp. Apache 2.0.
基于确定性状态机的无头 Agent 编排器——处理 bead 队列，分派至任意 LLM CLI，覆盖所有结果分支。Rust 实现。Headless agent orchestrator with deterministic state machine — processes a bead queue, dispatches to any LLM CLI, handles every outcome. Rust.
rust-in-peace——面向 Rust 的 agentic 安全审查：自主发现/分类/修复 unsafe/FFI 内存缺陷、panic-DoS 与反序列化信任缺陷（Miri / sanitizer / panic / hang detectors）。rust-in-peace 是 anthropics/defending-code-reference-harness 的 Rust 安全分支。rust-in-peace — agentic security review for Rust: autonomous find/triage/patch for unsafe/FFI memory bugs, panic-DoS, and deserialization-trust flaws (Miri / sanitizer / panic / hang detectors). A Rust-security fork of anthropics/defending-code-reference-harness.
持久化的多 agent 工作流编排——DAG 任务、git worktree、merge gate，兼具桌面端 + CLI + Slack。Persisted multi-agent workflow orchestration — DAG tasks, git worktrees, merge gates, desktop + CLI + Slack
实时追踪 GitHub 上每个新增的“skills”仓库，捕捉 AI Agent Skill 生态趋势。Real-time tracking of every new GitHub 'skills' repo to capture the AI agent skill ecosystem trend
AI Agent 的社交网络。把 SKILLS.md 喂给你的 AI——它就成为一位公民。无需服务器，无需 API key。GitHub 本身就是平台。Social network for AI agents. Feed SKILLS.md to your AI — it becomes a citizen. No servers, no API keys. GitHub IS the platform.
在一个终端驾驶舱内跨所有仓库调度 Claude Code 会话集群——分派任务、观察交付、对阻塞项即时响应。Terminal cockpit for running a fleet of Claude Code sessions across all your repos — dispatch work, watch what ships, and act on what's blocked, from one screen.
开源 AI 虚拟财务部门 —— 与数据对话：NL2SQL 查询、财务建模（DCF/WACC/LBO）、RAG 文档问答、多 Agent 辩论、报告、预算、资金管理与税务。FastAPI + LangGraph + React。Open-source AI virtual finance department — talk to your data: NL2SQL querying, financial modeling (DCF/WACC/LBO), RAG document Q&A, multi-agent debate, reporting, budgeting, treasury & tax. FastAPI + LangGraph + React.