クラウド、CI/CD、監視、デプロイ（6,726 件）
概要と使いどころ
This skill should be used when the user asks to "analyze a lawsuit", "訴訟分析", "事件分析", "書面分析", "case analysis", "判決分析", "訴訟書類の整理", or wants to extract structured information from litigation documents.
日本語の概要は準備中です。原文の説明を表示しています。
OCI（Oracle Cloud Infrastructure）のアーキテクチャ構成図を draw.io 形式（.drawio）で生成・編集する。AWS/Azure の構成図を OCI へ変換することもできる。Generate, edit, and convert OCI architecture diagrams in draw.io (.drawio) format using official Oracle icons.
用户咨询腾讯云产品资源、AWS、阿里云等多云资源时，查看智能顾问架构图、架构目录、架构详情、架构评估结果、绘制架构图、开通智能顾问时、AI智能巡检、AI容量监测、AI混沌演练、AI云诊断、主动预警、架构健康度、云运维问答、云资源查询、云成本优化、安全合规、云资源盘点、闲置资源检查、云产品最佳实践等AIOps、ChatOps、CloudOps操作时使用。
日本語の概要は準備中です。原文の説明を表示しています。
MUST USE whenever the user wants to automate a real desktop or sandbox - clicking, typing, scrolling, screenshotting, running an OS shell command, or handing a high-level 'open browser and do X' task to an autonomous computer-use agent. Wraps the trycua/cua Python toolkit via its `cua` CLI - pynput-based, cross-platform (macOS / Linux / Windows). NO custom tools are registered; you call `cua` through pi's built-in bash and read screenshots back through the Read tool. Triggers: cua, computer use, computer-use, GUI automation, screenshot the desktop, click on the screen, type into the active app, scroll the page, control my computer, drive my browser, sandbox, docker sandbox, QEMU sandbox, Lume sandbox, ComputerAgent, cua do, cua sandbox, 컴퓨터 자동화, 스크린샷 찍어, 내 컴퓨터 조작, 브라우저 열어서, 샌드박스, 화면 자동화, 마우스로 클릭, 키보드 타이핑, computer use 위임, 자동으로 클릭, 자율 에이전트로 처리.
日本語の概要は準備中です。原文の説明を表示しています。
Set up and configure WorkOS AuthKit authentication with Convex backend. Use when integrating AuthKit, configuring JWT providers, setting up environment variables, or implementing sign in and sign out flows with React and Vite. Supports Netlify deployment.
日本語の概要は準備中です。原文の説明を表示しています。
Use when deploying this teleprompt app with get-convex/static-hosting, especially when the user says /deploydev, /deployprod, deploy dev, deploy prod, deploy production, upload static hosting, or asks which Convex static-hosting command to run. Keeps dev uploads on fearless-dolphin-422 and production uploads on befitting-dodo-95.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user says /deploydev, deploy dev, upload dev static hosting, or asks to deploy the current app to its development Convex static-hosting target.
日本語の概要は準備中です。原文の説明を表示しています。
Integrate Convex static self hosting into existing apps using the latest upstream instructions from get-convex/self-hosting every time. Use when setting up upload APIs, HTTP routes, deployment scripts, migration from external hosting, or troubleshooting static deploy issues across React, Vite, Next.js, and other frontends.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user says /deployprod, deploy prod, deploy production, upload production static hosting, or asks to deploy the current app to its production Convex static-hosting target.
日本語の概要は準備中です。原文の説明を表示しています。
Router for Convex static-hosting deploy requests. Prefer deploydev for /deploydev and deployprod for /deployprod.
日本語の概要は準備中です。原文の説明を表示しています。
Use when acting as the orchestrator agent that drives Syntropic137 - running the dogfood loop, deciding what to dispatch next, landing agent PRs, deploying a beta, triaging failed executions, or keeping the scratchpad, paper cuts and retrospectives current. Trigger phrases include "orchestrator tick", "keep the loop running", "what should we dispatch next", "land these PRs", "why are PRs stacking up", "deploy the next beta", "pit stop", "the run failed, what now", "write the retro", "is the system helping", "scale quality", "learning loop for the orchestrator". Do NOT use for deciding whether one task belongs in a workspace or locally (see `dogfooding`), for turning one incident into an eval case (see `learning-loop`), for designing a workflow A/B experiment (see `workflow-experimentation`), or for release-branch and version-bump mechanics (see `devops`).
日本語の概要は準備中です。原文の説明を表示しています。
Use when asked to report the deployment sentinel value. Provides the sentinel string that proves a vendored skill reached the agent's context.
日本語の概要は準備中です。原文の説明を表示しています。
Use when: analysing a project's architecture, structure, and infrastructure health from the System perspective.
日本語の概要は準備中です。原文の説明を表示しています。
Use when: assessing how much context a deployed agent profile consumes before real work starts.
日本語の概要は準備中です。原文の説明を表示しています。
Use when: analysing a project's delivery health — CI/CD, commit patterns, and working tree state.
日本語の概要は準備中です。原文の説明を表示しています。
Use when creating new skills, editing existing skills, or verifying skills work before deployment
日本語の概要は準備中です。原文の説明を表示しています。
Server management principles and decision-making. Process management, monitoring strategy, and scaling decisions. Teaches thinking, not commands.
日本語の概要は準備中です。原文の説明を表示しています。
Upstash QStash expert for serverless message queues, scheduled jobs, and reliable HTTP-based task delivery without managing infrastructure. Use when: qstash, upstash queue, serverless cron, scheduled http, message queue serverless.
日本語の概要は準備中です。原文の説明を表示しています。
Expert in building voice AI applications - from real-time voice agents to voice-enabled apps. Covers OpenAI Realtime API, Vapi for voice agents, Deepgram for transcription, ElevenLabs for synthesis, LiveKit for real-time infrastructure, and WebRTC fundamentals. Knows how to build low-latency, production-ready voice experiences. Use when: voice ai, voice agent, speech to text, text to speech, realtime voice.
日本語の概要は準備中です。原文の説明を表示しています。
Expert knowledge for deploying to Vercel with Next.js Use when: vercel, deploy, deployment, hosting, production.
日本語の概要は準備中です。原文の説明を表示しています。
Specialized skill for building production-ready serverless applications on GCP. Covers Cloud Run services (containerized), Cloud Run Functions (event-driven), cold start optimization, and event-driven architecture with Pub/Sub.
日本語の概要は準備中です。原文の説明を表示しています。
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.
日本語の概要は準備中です。原文の説明を表示しています。
Integrate MercadoPago Checkout Pro (redirect-based) into Next.js applications with any PostgreSQL database (Supabase, AWS RDS, Neon, PlanetScale, self-hosted, Prisma, Drizzle, or raw pg). Use when the user needs to: (1) Add MercadoPago payment processing to a Next.js app, (2) Create a checkout flow with MercadoPago, (3) Set up payment webhooks for MercadoPago, (4) Build payment success/failure pages, (5) Create a shopping cart with payment integration, (6) Troubleshoot MercadoPago integration issues (auto_return errors, webhook failures, hydration mismatches, double submissions). Triggers on requests mentioning MercadoPago, Mercado Pago, payment integration with MP, Argentine/Latin American payment processing, or checkout with MercadoPago. Supports all MercadoPago countries: Argentina (ARS), Brazil (BRL), Mexico (MXN), Colombia (COP), Chile (CLP), Peru (PEN), Uruguay (UYU).
日本語の概要は準備中です。原文の説明を表示しています。
Expert at handling file uploads and cloud storage. Covers S3, Cloudflare R2, presigned URLs, multipart uploads, and image optimization. Knows how to handle large files without blocking. Use when: file upload, S3, R2, presigned URL, multipart.
日本語の概要は準備中です。原文の説明を表示しています。