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概要と使いどころ
Find and set up Google Play Console service-account JSON credentials for gpc. Use when Android Play uploads need auth, GPC_SERVICE_ACCOUNT is unknown, or before ns-deploy-android-app/ns-android-beta.
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。
One-shot NowStack Mobile iOS deployment with asc App Store Connect CLI. Use when preparing TestFlight/App Store releases, uploading IPAs, syncing screenshots/metadata, validating review readiness, or submitting the iOS app without EAS Submit.
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。
Build a NowStack Mobile iOS app and upload it to TestFlight. Always check OS first: macOS uses local `eas build --local`; Windows/Linux must run ns-setup-expo and use EAS cloud.
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。
Web scraping, search, crawling, and browser automation via the Firecrawl CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, scrape a webpage, grab content from a URL, extract data from a website, crawl documentation, download a site, or interact with pages that need clicks or logins. Also use when they say "fetch this page", "pull the content from", "get the page at https://", or reference scraping external websites. This provides real-time web search with full page content extraction and cloud browser automation — capabilities beyond what Claude can do natively with built-in tools. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.
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。
Agent eXperience Interface (AXI) router — the main entry point for agent-ergonomic CLIs. Use whenever the agent needs GitHub, browser automation, human review, quota routing, Slack, Notion, AWS/Docker/K8s, databases, GitLab (glab-axi), Oracle DB (oracle-axi), tmux/herdr/WezTerm sessions (cyber-mux), or any AXI-catalog tool; when choosing AXI vs MCP vs raw CLI; when building or reviewing an agent-facing CLI; or when the user says axi, gh-axi, chrome-devtools-axi, TOON output, agent ergonomics, or "prefer AXI". When in doubt about which external tool interface to use, start here.
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。
Work with the @upstash/blob TypeScript/JavaScript SDK for S3-compatible object storage with direct browser uploads, presigned URLs, multipart, and signed reads. Use when storing files or blobs, uploading avatars, images, videos, attachments or user documents, letting a browser upload straight to storage without proxying bytes through a server, generating public or time-limited signed URLs, serving private files, streaming large files with pause and resume, setting cache headers on stored objects, or reaching an S3-compatible bucket from the AWS SDK.
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。
Work with the @upstash/box TypeScript/JavaScript SDK for sandboxed cloud containers with AI agents, shell, filesystem, git, cron schedules, snapshots, and a headless browser. Use when building with Upstash Box, creating a sandbox or isolated environment to run untrusted or agent-generated code, running AI coding agents in containers, giving an agent a cloud dev environment with a shell and repository, browser automation from a box, scheduling recurring jobs inside a box, saving and restoring snapshots, or orchestrating parallel boxes.
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。
Work with any Upstash product, SDK, or tool, including serverless Redis (caching, sessions, leaderboards, key-value storage), Ratelimit (rate limiting and throttling), QStash (message queue, cron schedules, background jobs), Workflow (durable long-running functions), Vector (vector database for embeddings, semantic search, and RAG), Search (full-text and semantic search), Box (sandboxed cloud containers for AI agents, TypeScript/JavaScript and Python), Blob (serverless S3-compatible file storage with direct browser uploads), the Upstash CLI, and no-signup scratch Redis for agents. Use when the user mentions Upstash or needs any of these capabilities in a serverless, edge, or Node.js app.
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。
Work with the @upstash/vector TypeScript/JavaScript SDK, a serverless vector database for embeddings, similarity search, semantic search, and RAG (retrieval-augmented generation). Use when upserting, querying, fetching, ranging, or deleting vectors, upserting raw text against an index with a built-in embedding model, choosing dense, sparse, or hybrid indexes, filtering by metadata, organizing data with namespaces, running resumable queries, or connecting Upstash Vector to an AI or LLM application. Also use when the user asks for a vector store, vector search, nearest-neighbor or kNN search, embeddings storage, semantic cache, recommendations or similarity features, or a hosted vector index that needs no infrastructure.
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。
Work with the upstash-box Python SDK for sandboxed cloud containers with AI agents, shell, filesystem, git, cron schedules, snapshots, and a headless browser. Use when building with Upstash Box in Python, creating a sandbox or isolated environment to run untrusted or agent-generated code, running AI coding agents in containers, giving an agent a cloud dev environment with a shell and repository, browser automation from a box, scheduling recurring jobs inside a box, saving and restoring snapshots, or orchestrating parallel boxes.
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。
Work with the @upstash/qstash TypeScript/JavaScript SDK, an HTTP-based message queue, task scheduler, and background job system for serverless and edge runtimes (Next.js, Vercel, Cloudflare Workers, Deno, Node.js). Use when publishing messages to HTTP endpoints or URL groups, running background jobs without a long-running worker process, scheduling with cron expressions, delaying messages, building FIFO queues with parallelism and flow control, configuring retries and callbacks, handling a dead letter queue (DLQ), deduplicating messages, fanning out to multiple endpoints, verifying QStash webhook signatures (Next.js App Router, Pages Router, and Edge Runtime), running a local QStash dev server, or migrating regions. Also use when the user asks for a serverless cron job, async task queue, job scheduler, delayed delivery, webhook delivery with retries, or event-driven messaging between services.
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。
Rate limiting for serverless and edge apps with the @upstash/ratelimit TypeScript/JavaScript SDK backed by Upstash Redis. Use when adding a rate limiter or throttling to an API route, Next.js middleware, Vercel Edge, Cloudflare Workers, or any HTTP endpoint; returning 429 Too Many Requests; choosing between fixed window, sliding window, and token bucket algorithms; limiting per user, IP, API key, or tenant with prefixes and custom keys; protecting login, signup, form, or AI endpoints from abuse, bots, and brute force; using deny lists, ephemeral caching, analytics, timeouts, and multi-region rate limits; or estimating the Redis command cost of rate limiting. Also use when the user says rate limit, rate-limiting, throttle, quota, request limits, or traffic protection.
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。
Design or review .NET solution architecture across modular monoliths, clean architecture, vertical slices, microservices, DDD, CQRS, and cloud-native boundaries without over-engineering.
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 the Microsoft.Extensions stack correctly across Generic Host, dependency injection, configuration, logging, options, HttpClientFactory, and other shared infrastructure patterns.
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。
本番に出る前の修正が積まれたrelease pull requestに、デプロイの前後に人間がやる事をまとめたコメントを投稿・更新する。 codepatrol skillが起動したsubagentが実行する。ユーザーが直接呼び出す事は想定していない。
Scaffold a new Tip in the ai-product-dev-tips repository following the existing directory/format conventions, and register its link in the root README.md. Use this whenever the user wants to add, create, or write a new Tip in this repo — e.g. "nlp_processing に〜の Tip を追加して", "新しい Tips を作って", "〜の解説 Tip を書いて", "this repo に〜のネタを追加". It picks the right category and next sequential number, matches the README format of nearby Tips, generates code scaffolding (Dockerfile / requirements.txt / *_cpu.sh / *_gpu.sh / *.py) only when the Tip needs runnable code, and inserts the link into the correct <details> section of the root README. Trigger this even if the user doesn't say the word "skill" — any request to add a new entry to this Tips collection should use it.
Azure OpenAI画像生成CLIツール (gpt-image-1.5 / gpt-5.1)。テキストから画像生成、画像のAI編集、画像の内容説明を行う。Use when the user wants to (1) generate images using Azure OpenAI, (2) edit existing images with AI, (3) explain image contents. Triggers on "画像を生成", "画像を編集", "画像の説明", "generate an image", "edit this image", "describe this image", "imgenで".
提出物の事前検証を実行する。Kaggle CSV / Kaggle Code Competition / 予測ファイル zip / Docker コンテナ / Simulation エージェントの5形式に対応。submission-validator agent を呼び出して機械的にチェックする。提出直前に必ず使う。
Run pre-submission validation. Handles 5 formats — Kaggle CSV / Kaggle Code Competition / prediction-file zip / Docker container / Simulation agent. Delegates to the submission-validator agent for mechanical checks. Use right before any submission.
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 cutting, debugging, or verifying a pythinker-code (TSC monorepo) release — changesets flow, the ci release-packages version PR, release.yml anatomy, npm Trusted Publishing OIDC, native assets, brew tap, CDN redeploy, and their failure modes. Invoked by /release.
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。
Build AI performance monitoring. TRIGGERS - Use when user needs help with ai-performance-monitor related tasks.
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 observability for AI systems. TRIGGERS - Use when user needs help with ai-observability-setup related tasks.
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。
Build AI monitoring systems with drift detection. TRIGGERS - Use when user needs help with ai-monitoring-system related tasks.
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。
Design model serving infrastructure for AI. TRIGGERS - Use when user needs help with ai-model-serving related tasks.
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。