远程 Agent 配对浏览器(gstack)
io.github.garrytan/gstack/pair-agent
让远程 AI agent 与你的浏览器配对使用。(gstack)
“Ai Company” 共 1,185 个结果
io.github.garrytan/gstack/pair-agent
让远程 AI agent 与你的浏览器配对使用。(gstack)
io.github.garrytan/gstack/setup-gbrain
为当前编码 agent 配置 gbrain:安装 CLI、初始化本地 PGLite 或 Supabase brain、注册 MCP、逐远端记录信任策略。(gstack)
io.github.google/skills/gke-ai-troubleshooting-tpu-performance-degradation
Diagnose GKE Cloud TPU training throughput drops and step-time regressions (15%+ TPU duty-cycle drop) using ML Diagnostics Workload Monitoring (`gcloud alpha mldiagnostics monitored-events` / `hypercomputecluster.googleapis.com/v1alpha`) and 1-minute Cloud Monitoring system metrics (`kubernetes.io/node/accelerator/*`). Distinguishes hardware and network fabric throttling from workload resource bottlenecks (HBM capacity, host memory, or host CPU saturation). Use when TPU training throughput or duty cycle drops without crashing pods, when `PERFORMANCE_DEGRADATION` monitored events fire, or when triaging slow multi-slice training steps. Don't use for complete multi-slice XLA execution stalls with `HANG_DETECTED` logs (use gke-ai-troubleshooting-tpu-mxla-hang) or pod eviction/interruption restarts (use gke-ai-troubleshooting-jobset-interruption).
io.github.google/skills/gke-ai-troubleshooting-tpu-mxla-hang
Diagnose GKE Cloud TPU multi-slice training hangs (Megascale `HANG_DETECTED` logs and hang monitored events) using the ML Diagnostics `Megascale XLA (MXLA) Hang Analyzer` (`gcloud alpha mldiagnostics monitored-events`) and 1-minute Cloud Monitoring multi-slice latency metrics (`kubernetes.io/container/multislice/*`). Distinguishes XLA compiler/HLO launch divergence and host data-input stalls from TPU chip, SparseCore, ICI, or network fabric faults. Use when multi-slice TPU training jobs freeze without progressing steps, emit `HANG_DETECTED`, or stall in collective operations. Don't use for gradual step-time throughput drops without hangs (use gke-ai-troubleshooting-tpu-performance-degradation) or pod preemption/eviction restarts (use gke-ai-troubleshooting-jobset-interruption).
io.github.openai/codex/openai-docs
用于 Codex 模型/定价、定时任务、skills、设置、安装、排障、定制、自动化与自我知识——包括指代 Codex 的“you”“your”“this app”“this coding agent”——以及 OpenAI API/产品与 ChatGPT Work 的问题。也用于模型选型/迁移、prompt 撰写、SDK、Responses、Realtime、agents、evals 以及 Chat/Work/Codex 的对比。仅提到 Codex 的普通应用/软件任务不适用。
io.github.coreyhaines31/marketingskills/emails
当用户想创建或优化邮件序列、drip campaign、自动化邮件流程或生命周期邮件体系时使用。用户提到 email sequence、drip campaign、nurture sequence、onboarding emails、welcome sequence、re-engagement emails、邮件自动化、lifecycle emails、trigger-based emails、email funnel、email workflow、“该发哪些邮件”、welcome series 或 email cadence 等场景时也适用。适合任何多封邮件的自动化流程。冷邮件触达见 cold-email,应用内引导见 onboarding。
io.github.DietrichGebert/ponytail/ponytail-audit
Quality audit of a whole repo: bugs, security holes, what breaks under real load, risky code without tests, slow paths, and what to delete, merge or split. Ranked, each finding explained in plain English. One-shot report, changes nothing. Use for "audit this codebase", "review the whole repo", "find bloat", "what can I delete", /ponytail-audit.
io.github.DietrichGebert/ponytail/ponytail-audit
Quality audit of the whole repo: bugs, security, real load, missing tests, speed, and what to delete. Most important first.
io.github.DietrichGebert/ponytail/ponytail
强制采用真正可行的最懒方案:最简、最短、最少。模仿一位见惯一切资深工程师的姿态:先质疑任务是否根本不必存在(YAGNI),优先标准库而非自写代码、平台原生能力而非引依赖、一行而非五十行。支持强度档位:lite、full(默认)、ultra。适用于任何编码任务:编写、新增、重构、修复、审查、设计代码以及选择库或依赖。当用户说 ponytail、be lazy、lazy mode、最简方案、minimal solution、YAGNI、do less、shortest path,或抱怨过度设计、膨胀、模板代码、不必要的依赖时也应使用。不用于非编码请求(通识、文章、翻译、摘要、菜谱)。
io.github.DietrichGebert/ponytail/ponytail-review
审查 diff 中的过度工程。找出该删的东西:重复造的标准库、多余依赖、投机性抽象。每条发现一行。
io.github.mem0ai/mem0/mem0-vercel-ai-sdk
Mem0 为 Vercel AI SDK 提供的 provider(@mem0/vercel-ai-provider)。触发条件:用户提到 "vercel ai sdk"、"@mem0/vercel-ai-provider"、"createMem0"、"retrieveMemories"、"addMemories"、"getMemories"、"searchMemories"、"mem0 vercel"、"AI SDK provider"、"AI SDK memory",或在 generateText/streamText 中使用 mem0。也适用于需要记忆增强 AI 的 Next.js 应用。不触发:不经 Vercel 的直接 Python/TS SDK 调用(用 mem0 技能),或 CLI 终端命令(用 mem0-cli 技能)。
io.github.topoteretes/cognee/company-brain-company-qa
Build one company memory from a SQL database, a support ticket export and a folder of documents, linked into one graph by cognee, then answer questions that need several of those sources together. Use when someone wants to connect their company's database, tickets and docs, or asks who owns, decided or is handling something across them. Runs locally; reads the sources, writes only to cognee's memory.
io.github.thedaviddias/Front-End-Checklist/css-containment
审查样式表、组件样式与响应式行为,落实“用 CSS containment 限制重绘范围”这一规则时使用。提出修复前要在各断点和交互状态下检查实际渲染布局。
io.github.TriliumNext/Trilium/maintaining-docker-hub
Use when working on Trilium's published Docker images on Docker Hub or GHCR rather than on the Dockerfiles — "how many pulls does the image get?", "why is the Docker Hub repository so big?", "clean up old tags", "delete untagged images", "which tags do we publish?", the legacy repositories (triliumnext/notes, zadam/trilium) and their mirroring, the main-docker.yml copy-to-Docker-Hub step, mirror-legacy-docker.yml, Docker Hub categories, stars or the overview. Includes hub.mjs (stats, tag listing/deletion, the manifest inventory and a safe untagged-image purge, all dry-run by default) and the storage model that decides how a cleanup works. Do NOT use for building or running the image locally (see the Developer Guide's Docker page).
io.github.The-Vibe-Company/quivr/mermaid-diagrams
Comprehensive guide for creating software diagrams using Mermaid syntax. Use when users need to create, visualize, or document software through diagrams including class diagrams (domain modeling, object-oriented design), sequence diagrams (application flows, API interactions, code execution), flowcharts (processes, algorithms, user journeys), entity relationship diagrams (database schemas), C4 architecture diagrams (system context, containers, components), state diagrams, git graphs, pie charts, gantt charts, or any other diagram type. Triggers include requests to "diagram", "visualize", "model", "map out", "show the flow", or when explaining system architecture, database design, code structure, or user/application flows.
io.github.debpalash/VoiceStudio/voicestudio-maintainer
Triage GitHub issues, review contributor pull requests, diagnose CI, and prepare explicitly requested releases for VoiceStudio's Electron desktop app and Python backend. Use for repository maintenance work, not ordinary VoiceStudio audio generation.
io.github.coollabsio/coolify/tailwindcss-development
用户消息以任何形式包含 'tailwind' 时始终调用。还适用于:构建响应式栅格布局(多列卡片栅格、商品栅格)、flex/grid 页面结构(带侧边栏的仪表盘、固定顶栏、移动端可折叠导航)、UI 组件样式(卡片、表格、导航栏、价格区、表单、输入框、徽章)、添加暗色模式变体、修复间距或排版,以及 Tailwind v3/v4 工作。核心场景:在 HTML 模板(Blade、JSX、Vue)中编写或修正 Tailwind 工具类。跳过:后端 PHP 逻辑、数据库查询、API 路由、无 HTML/CSS 部分的 JavaScript、CSS 文件审计、构建工具配置和原生 CSS。
io.github.affaan-m/ECC/ai-first-engineering
Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.
io.github.wshobson/agents/tailwind-design-system
使用 Tailwind CSS v4、设计令牌、组件库与响应式模式构建可扩展的设计系统。在创建组件库、实现设计系统或标准化 UI 模式时使用。
io.github.sickn33/agentic-awesome-skills/container-registries
Manage container registries including ECR, ACR, GCR, and Docker Hub.
io.github.sickn33/agentic-awesome-skills/container-hardening
Secure Docker images and container runtime configurations.
io.github.sickn33/agentic-awesome-skills/ai-coding-agent-guardrails
Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.
io.github.obra/superpowers/brainstorming
任何创造性工作之前必须先使用——创建功能、构建组件、添加能力或修改行为。在实现之前探索用户意图、需求与设计。
io.github.affaan-m/ECC/fal-ai-media
通过 fal.ai MCP 统一生成媒体——图像、视频和音频。覆盖文生图(Nano Banana)、文/图生视频(Seedance、Kling、Veo 3)、文生语音(CSM-1B)以及视频生音频(ThinkSound)。当用户想用 AI 生成图像、视频或音频时使用。