2,941 件 ・ 関連度順
概要と使いどころ
Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.
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。
AI Automation Strategist: Decide what to automate: opportunity mapping, ROI, build vs buy, rollout and change management.
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。
Covers writing backend Trigger.dev tasks with @trigger.dev/sdk: defining task() and schemaTask(), the run function and its ctx, retries, waits, queues and concurrency, idempotency keys, run metadata, logging, triggering other tasks (and the Result shape), scheduled/cron tasks, and the essentials of trigger.config.ts. Load this whenever you are authoring or editing code inside a /trigger directory, defining a task, or writing backend code that triggers tasks. Realtime/React hooks and AI chat are covered by separate skills.
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。
Clerk Billing for subscription management - render Clerk's PricingTable and in-app checkout drawer, configure subscription plans, seat-limit plans for B2B, feature entitlements with has(), and billing webhooks. Use for SaaS monetization, plan gating, checkout flows, trials, invoicing, and subscription lifecycle management.
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。
Advanced and operational chat.agent capabilities for Trigger.dev, loaded on demand. Load this when working on the raw Sessions primitive (sessions / SessionHandle), a custom chat transport or the realtime wire protocol, durable sub-agents (AgentChat, chat.stream.writer), human-in-the-loop, steering, actions, background injection (chat.defer / chat.inject), fast starts (preload, Head Start via @trigger.dev/sdk/chat-server), context resilience (compaction, recovery boot, OOM, large payloads), chat.local run-scoped state, offline testing with mockChatAgent, or prerelease/version upgrades. For the everyday chat.agent({...}) definition and the useTriggerChatTransport happy path, use the trigger-authoring-chat-agent skill instead.
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。
Bootstrap Trigger.dev into an existing project from scratch: authenticate the CLI, install @trigger.dev/sdk and @trigger.dev/build, write trigger.config.ts with the project ref and task dirs, scaffold a /trigger directory with a first task, wire tsconfig and .gitignore, set TRIGGER_SECRET_KEY, and run the dev server. Load this when a project has no trigger.config.ts yet and the user asks to "add Trigger.dev", "set up Trigger.dev", "initialize Trigger.dev", or get a first task running, including in a monorepo. Once the project is set up and you are writing task code, switch to the trigger-authoring-tasks skill.
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。
Analyze Trigger.dev tasks, schedules, and runs for cost optimization opportunities. Use when asked to reduce spend, optimize costs, audit usage, right-size machines, or review task efficiency. Combines static source analysis with live run analysis via the Trigger.dev MCP tools (list_runs, get_run_details, get_current_worker).
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。
Clerk authentication router. Use when user asks about Clerk CLI operations, adding authentication, setting up Clerk, custom sign-in flows, Swift or native iOS auth, native Android auth, Next.js patterns, React patterns, Vue patterns, Nuxt patterns, Astro patterns, TanStack Start patterns, Expo patterns, React Router patterns, Chrome Extension patterns, organizations, billing, subscriptions, payments, pricing, plans, seat-based pricing, feature entitlements, syncing users, or testing. Automatically routes to the specific skill based on their task.
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 this skill when building, debugging, or answering questions about Liveblocks. Liveblocks gives you the building blocks and infrastructure to enable people and AI to work together inside your app, powering realtime collaboration. Liveblocks features include collaboration, rooms, organizations, workspaces, comments, composer, threads, notifications, multiplayer, conflict resolution, realtime presence, avatar stacks, AI collaborators, AI agents, text editors, Tiptap, BlockNote, Lexical, React Flow, Chat SDK. Common components include AiChat, Thread, InboxNotification, Composer, Toolbar (for Lexical Tiptap), FloatingToolbar, FloatingComposer, FloatingThreads, AnchoredThreads. Common hooks include useThreads, useStorage, useMutation, useOthers, useInboxNotifications, useAiChats. Common issues are related to authentication (ID tokens vs access tokens), permissions, room limits, connection errors, user info.
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。
Trigger.dev client/frontend surface: subscribe to runs in realtime (runs.subscribeToRun and the @trigger.dev/react-hooks hook useRealtimeRun), consume metadata and AI/text streams in React (useRealtimeStream), trigger tasks from the browser (useTaskTrigger, useRealtimeTaskTrigger), and mint scoped frontend credentials with auth.createPublicToken / auth.createTriggerPublicToken. Load when wiring a frontend (React/Next.js/Remix) or backend-for-frontend to show live run progress, status badges, token streams, trigger buttons, or wait-token approval UIs. NOT for writing the backend task itself (streams.define / metadata.set is trigger-authoring-tasks territory); this is the consumer side.
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。
Author and run a durable AI chat agent with chat.agent from @trigger.dev/sdk/ai: the per-turn run loop, why you MUST spread ...chat.toStreamTextOptions() first, returning a StreamTextResult vs calling chat.pipe(), the two server actions (chat.createStartSessionAction + auth.createPublicToken), and wiring useChat to useTriggerChatTransport. Load this when building, modifying, or debugging a chat backend (the agent task or its lifecycle hooks) or its React transport, when declaring typed tools or custom data parts, or when migrating a plain AI SDK streamText route to chat.agent.
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。
Clerk Organizations for B2B SaaS - create multi-tenant apps with org switching, role-based access, verified domains, and enterprise SSO. Use for team workspaces, RBAC, org-based routing, member management.
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。
Clerk Backend REST API explorer and executor. Browse tags, inspect endpoint schemas, and execute authenticated requests. Use when listing users, managing organizations, or calling any Clerk API endpoint.
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。
Operate the Clerk CLI (`clerk` binary) for authentication, user/org/session management, deploy verification, instance config, env keys, and any Clerk Backend or Platform API call. Use when the user mentions Clerk management tasks, "list clerk users", "create a clerk user", "update organization", "pull clerk config", "clerk env pull", "clerk doctor", "clerk deploy", "clerk deploy status", "clerk api", or any ad-hoc Clerk API request. Prefer the CLI over raw HTTP: it handles auth, key resolution, app/instance targeting, and formatting automatically.
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。
Guides and best practices for working with Neon Serverless Postgres. Covers setup, connection methods, branching, autoscaling, scale-to-zero, read replicas, connection pooling, Neon Auth, and the Neon CLI, MCP server, REST API, TypeScript SDK, and Python SDK. Use when users ask about "Neon setup", "connect to Neon", "Neon project", "DATABASE_URL", "serverless Postgres", "Neon CLI", "neon", "Neon MCP", "Neon Auth", "@neondatabase/serverless", "@neondatabase/neon-js", "scale to zero", "Neon autoscaling", "Neon read replica", or "Neon connection pooling".
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。
Add Clerk authentication to any project by following the official quickstart guides.
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。
Advanced Next.js patterns - middleware, Server Actions, caching with Clerk.
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。
Overview of the Neon platform for apps and agents, spanning Postgres, Auth, Data API, and the new services: Object Storage, Compute Functions, and AI Gateway. Use whenever "Neon" is mentioned for an overview of how to work with Neon and how to get started. Otherwise, the individual capabilities are the triggers: "object storage" or "S3-compatible storage", "serverless functions", "background jobs", or "run code near my database", "AI gateway", "LLM proxy", "model routing", or "call an LLM" → AI Gateway; "database", "Postgres", or "authentication" → Postgres and Auth.
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。
Custom authentication flows and component appearance - hooks (useSignIn, useSignUp), themes, colors, fonts, CSS. Use for custom sign-in/sign-up flows, appearance styling, visual customization, branding.
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。
Playwright browser automation. Navigates URLs, takes screenshots, checks accessibility tree, interacts with UI elements, and reports findings.
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。
SEO/GEO Agent Operations SOP v2 — Rebuilt from real-world operations (analook.com 0→launch, GSC incident, DataForSEO monitoring, gingiris.tools post-migration recovery). What's new in v2: • Step-by-step onboarding (Q1→Q6), multiple choice wherever possible — no big forms • Mandatory daily SEO log — first item is always GSC token status check • Data cross-validation rule: any external metric must come from ≥2 sources before use • Backlink progress tracking (6-week wait → check → alert if not indexed) • New vs. established site strategy matrix (new site <6mo: KD≤20; mature: KD up to 35+) Real incidents baked in: GSC token expired silently for 2 weeks (analook.com), P0 keywords dropped out of Top 100 after domain migration (gingiris.tools), traffic data off by 17× from single-source DataForSEO. Triggers: "SEO agent" | "SEO daily report" | "GSC monitoring" | "DataForSEO" | "GEO agent" | "backlink tracking" | "IndexNow" | "competitor comparison page" | "SEO SOP" | "autonomous SEO" | "GEO triple combo" 🇨🇳 SEO/GEO Agent 运营 SOP v2 — 基于真实运营经验重写（analook.com 从零建站 + GSC 断档 2 周 + DataForSEO 监控 + gingiris.tools 迁移权重恢复）。 对话式开局、强制日报（GSC token 是第一项）、数据交叉验证铁律、外链进度追踪、新老站区分策略。
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。
[DEPRECATED — merged into gingiris-seo-geo-agent] SEO/GEO agent-ops SOP: daily 4-phase audit automation, GSC pipeline, AI traffic tracking, schema validation, IndexNow. Use the gingiris-seo-geo-agent skill instead.
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。
AI Agent Workflow & Skill Architecture Guide — turn expert work into measurable, reusable agent systems. Covers workflow discovery, skill decomposition, harness design, evaluation, human escalation, observability, cost control, and multi-agent orchestration. Includes a measured marketing-delivery case: 15 people × 3–4 weeks reduced to one strategist + AI in 5 days. By Gingiris.
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。
Skill for developing AI agent engine components in internal/agent/. Covers the ReAct loop, swarm delegation, planning, verification, memory reflection, and cron automation.
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。