仓库/Skill 库

Subconscious Memory 2026：基于混合语义搜索与 MCP 的 AI 编码上下文引擎。Subconscious Memory 2026: AI Coding Context Engine with Hybrid Semantic Search & MCP

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).

📰 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

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.

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.

CELLO protocol 的官方客户端——提供 MCP server 及面向 OpenClaw、NanoClaw、IronClaw、ZeroClaw 等 agent 变体的原生适配器。The official client for the CELLO protocol — MCP server and native adapters for OpenClaw, NanoClaw, IronClaw, ZeroClaw, and other agent variants

面向长生命周期 Agent 与有状态负载的会话中心计算：暂停即保留记忆，按需恢复。Session-centric compute for long-lived agents and stateful workloads. Pause with memory intact; resume on demand.

面向有据可循的 Agent 工作流的 TypeScript 参考实现，支持混合检索、人工审核与可回放的审计追踪。TypeScript reference implementation for grounded agent workflows with hybrid retrieval, human review, and replayable audit trails.

面向 GitHub Copilot 的 Agentic 开发生命周期——计划、工作、证据与教训全部沉淀在 GitHub 上，而非聊天窗口中。Agentic development lifecycle for GitHub Copilot — the plan, the work, the evidence, and the lessons all live on GitHub, not in chat windows.

驾驶 Claude Code Agent 的驾驶舱——打磨「指示→等待→审查→再指示」循环的桌面 Cockpit（非官方）。A cockpit for piloting Claude Code agents — 指示→待機→レビュー→再指示のループを磨くデスクトップコックピット (unofficial)

Microwave Method：agent 工厂 + 受治理的 LLM wiki。每个 agent 一次性重型处理，每个 feature 轻量处理。上下文只"烹饪"一次，按缓存价"回热"。Microwave Method: agent factory + governed LLM wiki. Heavy pass once per agent, light pass per feature. Context is cooked once, reheated at cache price.

Claude Code 动态工作流的指挥中心 — 实时 agent 可观测性、跨项目运行历史、保存与重放。零依赖的 Claude Code 插件。Mission control for Claude Code dynamic workflows — live agent observability, cross-project run history, save & re-run. A zero-dependency Claude Code plugin.

涵盖 RAG、AI Agent、评估与商业智能的实战 AI 应用项目集。Practical AI application projects across RAG, AI agents, evaluation, and business intelligence.

🐺 创新型 LLM 驱动 12 人狼人杀模拟，针对直播优化并支持 OBS 无缝集成🐺 Experience an innovative, LLM-driven Werewolf simulation for 12 players, optimized for live streaming and designed for seamless integration with OBS.

基于 n8n 构建的 AI agent，用于阅读、分类和回复询价邮件，并与 Google Sheets 和 Gmail 集成。AI agent created in n8n for reading, sorting, and replying to quote emails, integrated with Google Sheets and Gmail.

可移植的 Cursor/Claude agent skills，覆盖 GitLab MR 评审、事故 RCA、Kubernetes 资源调整、团队归属与组织汇总，支持注册表驱动安装、行为评估与组合契约Portable Cursor/Claude agent skills for GitLab MR review, incident RCA, Kubernetes rightsizing, squad ownership, and org rollups — registry-driven install, behavioral evals, composition contracts.

Pinakes —— 可移植、Agent 优先的知识库。一个目录即一个 KB。Pinakes — a portable, agent-first knowledge base. One directory = one KB.

AI 时代的工具联盟：可追溯的知识（Nexus·Archon）、可问责的审查与治理（Arbiter·Observer）、可理解的变更质量（Adept·Probe）。AI 构建，你来理解。An alliance of tools for the AI era: grounded knowledge (Nexus·Archon), accountable review & governance (Arbiter·Observer), and comprehension & mutation quality (Adept·Probe). AI builds it — you understand it.

一个工作流框架，适配所有编码 agent。通过与工具无关的核心，将你的 AI 编码规范安装到 Claude Code、Cursor、GitHub Copilot、Gemini CLI、Codex 和 Windsurf。Apache 2.0。One workflow framework, every coding agent. Install your AI-coding discipline into Claude Code, Cursor, GitHub Copilot, Gemini CLI, Codex, and Windsurf from one tool-agnostic core. Apache 2.0.

由机器强制执行的 AI Agent 前端 UI/UX Skill 包。注册表 + 懒加载：2,018 token 的路由在每次请求中从 334k token 深度内容中按需加载一个 Skill。包含 11 个发布阻塞闸门，其中一项用于校验 Skill 包自身文档与参考资料是否遵循其规则。Machine-enforced frontend UI/UX skill pack for AI agents. Registry + lazy loading: a 2,018-token router loads one skill per request out of 334k tokens of depth. 11 release-blocking gates, including one that checks the pack's own docs and reference material against its own rules.

适用于 macOS 的 local-first 语音+手势 AI 存在。唤醒词 → Whisper → 三层路由 → Claude Agent SDK + MCP，带有 kill switch、设备级 allowlist、声纹门控确认和完整的操作日志。Local-first voice + gesture AI presence for macOS. Wake word → Whisper → three-tier router → Claude Agent SDK + MCP, behind a kill switch, device-scoped allowlist, voiceprint-gated confirmation and a full action log.

自动化 n8n 工作流，抓取 LinkedIn 产品经理职位，通过向量相似度与简历匹配打分，并使用 Claude 为每个职位生成简历修改建议Automated n8n workflow that scrapes LinkedIn PM jobs, scores them against your resume with vector similarity, and uses Claude to suggest per-job resume edits.

Buzz Agent 运行时 harness——监控 stock buzz-acp，可选的 sandbox 前置入口、DNA 完整性校验与 memory checkpoint。Buzz agent runtime harness — supervise stock buzz-acp, optional sandbox front door, DNA integrity, and memory checkpoint.

为 AI agent 提供持久化、结构化记忆。基于 Go 的本地优先 MCP server：语义召回、去重、provenance、冲突解决。单一静态二进制，零依赖。Persistent, structured memory for AI agents. Local-first MCP server in Go: semantic recall, dedupe, provenance, conflict resolution. One static binary, zero dependencies.

多租户 SaaS 自动化平台，具备事件驱动工作流、AI 驱动的文档处理与实时集成。Multi-tenant SaaS automation platform with event-driven workflows, AI-powered document processing, and real-time integrations.

立场论文：编码 Agent 需要对代码库决策的显式建模，而不仅仅是结构建模。Position paper: coding agents need an explicit model of codebase decisions, not just structure"

自托管共享记忆，面向 AI Agent 团队。支持房间（Rooms）、L0-L3 层级深度与 MCP；读取路径不调用任何语言模型。基于 vectorize-io/hindsight（MIT）的 fork。Self-hosted shared memory for a team of AI agents. Rooms, hierarchical L0-L3 depth, MCP. The read path never invokes a language model. Fork of vectorize-io/hindsight (MIT).

3D 记忆岛屿，让 Google ADK agent 将你的记忆保存为有据可查的书：基于 Gemini on Vertex AI、Firestore、Pub/Sub 的 dreaming 机制构建知识图谱与 dark keepers，配合 Cloud TTS/STT 语音。All Things Agentic Hackathon 参赛作品。3D memory island where Google ADK agents keep your memories as grounded books: Gemini on Vertex AI, Firestore, Pub/Sub dreaming that builds a knowledge graph and dark keepers, Cloud TTS/STT voice. All Things Agentic Hackathon entry.

基于证据的构建流水线，编排 10 个 AI 子 Agent，并通过确定性 5 道关卡验证系统证明正确性。Evidence-based build pipeline that orchestrates 10 AI sub-agents and proves correctness through a deterministic 5-gate verification system.

AI 驱动的每周生活规划器 — 由多供应商 Agent 生成饮食、学习、锻炼、习惯和娱乐方案，并附带每周日程追踪。AI-powered weekly life planner - nutrition, study, workouts, habits and fun generated by a multi-provider agent, with a weekly schedule tracker.

基于 Next.js、FastAPI 和 Supabase 的 AI 辅导应用。上传 PDF 与 URL，即可生成结构化摘要、多轮对话和自定义测验。自定义主题通过 Wikipedia、ArXiv 和 DuckDuckGo 进行联网搜索，以生成测验并围绕主题展开对话。Next.js AI tutor with FastAPI and Supabase. Upload PDFs and URLs to generate structured summaries, multi-session chat, and custom quizzes. Custom topics use web search through Wikipedia, ArXiv, and DuckDuckGo to generate quizzes and chat about the topic.

NEXORA 的黑客松团队仓库 - [hackindia-team:ai-first-startup-hackathon-build-a-startup-using-ai-only:nexora]Hackathon team repository for NEXORA - [hackindia-team:ai-first-startup-hackathon-build-a-startup-using-ai-only:nexora]

Codiacs 黑客松团队仓库 - [hackindia-team:ai-first-startup-hackathon-build-a-startup-using-ai-only:codiacs]Hackathon team repository for Codiacs - [hackindia-team:ai-first-startup-hackathon-build-a-startup-using-ai-only:codiacs]

Local-first 可视化任务图，使人类与 AI Agent 在目标、进度、推理与下一步行动上保持对齐。Local-first visual task graph that keeps humans and AI agents aligned on goals, progress, reasoning, and the next action.

本地优先的研究论文工作空间与可视化 AI Agent 工作流构建器Local-first research paper workspace and visual AI agent workflow builder

面向 AI Agent 调试 Android React Native/Expo 应用的本地运行时可观测性桥接层——以证据为先：截图、UI 树、逐请求网络数据、FPS、React 渲染、CDP console/heap/profile、确定性诊断、前后对比。Local runtime observability bridge for AI agents debugging React Native/Expo apps on Android — evidence-first: screenshots, UI trees, per-request network, FPS, React renders, CDP console/heap/profile, deterministic diagnosis, before/after compare.