Cloud

Guide user through actual deployment steps for their application. This skill should be used when a project is ready to deploy to production. Walks through pre-deployment checks, deployment execution, and post-deployment verification. Supports VPS/Docker, Cloudflare Pages, fly.io, and Hostinger Shared Hosting.

Vercel and Cloudflare canary deployment patterns with traffic splitting, gradual rollout automation, and rollback strategies. Use when deploying with canary releases, implementing progressive rollouts, managing traffic splitting, configuring A/B deployments, or when user mentions canary deployment, blue-green deployment, gradual rollout, traffic shifting, or deployment rollback.

AWS cloud infrastructure patterns and best practices. Use when designing or implementing AWS solutions including EC2, Lambda, S3, RDS, and infrastructure as code with Terraform or CloudFormation.

Comprehensive guidance for building and deploying static websites with the Astro framework.This skill should be used when asked to "create astro site", "deploy astro to firebase","set up content collections", "add mermaid diagrams to astro", "configure astro i18n","build static blog", or "astro markdown setup". Covers SSG fundamentals, Content Collections,Markdown/MDX, partial hydration, islands architecture, and deployment to Netlify, Vercel,GitHub Pages, or GCP/Firebase.

MANDATORY adversarial code review. Use before ANY commit to find security vulnerabilities, logic flaws, and edge cases. Actively tries to break the code.

学習目的で、あらゆる提案変更に WHY / VERIFY / RISK とロールバックを必ず付ける（コード・コマンド・AWS手順）。WHYは「選択肢→特徴→結論（最適案）」で統一する。

Update the project learning logs (PowerShell/cmd, Git/GitHub/Copilot, AWS, TypeScript, Next.js/React, Playwright) by merging new knowledge into existing categories across one or more files.

Firebase Cloud Messaging and Apple Push Notification Service setup.

PostgreSQL development for Python with full-text search (tsvector, tsquery, BM25 via pg_search), vector similarity (pgvector with HNSW/IVFFlat), JSONB and array indexing, and production deployment. Use when creating search features, storing AI embeddings, querying vector similarity, optimizing PostgreSQL indexes, or deploying to AWS RDS/Aurora, GCP Cloud SQL/AlloyDB, or Azure. Covers psycopg2, psycopg3, asyncpg, SQLAlchemy integration, Docker development setup, and index selection strategies. Triggers: "PostgreSQL search", "pgvector", "BM25 postgres", "JSONB index", "psycopg", "asyncpg", "PostgreSQL Docker", "AlloyDB vector". Does NOT cover: DBA administration (backup, replication, users), MySQL/MongoDB/Redis, schema design theory, stored procedures.

Create Azure DevOps dashboards with widgets and metrics. Use when visualizing project metrics or creating team dashboards.

Discover all resources in your Amplify sandbox (DynamoDB tables, Lambda functions, data models, auth config) by reading amplify_outputs.json and querying AppSync.

Troubleshoots infrastructure and application configuration items in Mission Control by diagnosing health issues, analyzing recent changes, and investigating resource relationships. Use when users ask about unhealthy or failing resources, mention specific config items by name or ID, inquire about Kubernetes pods/deployments/services, AWS EC2 instances/volumes, Azure VMs, or other infrastructure components. Also use when investigating why a resource is down, stopped, degraded, or showing errors, or when analyzing what changed that caused an issue.

Given a human certification or license (e.g. PL-300, SAP B1, Azure AI Engineer), create a production-ready agent skill profile and certification ladder, including skills.yaml entries, agent YAML, and skills documentation, using the anthropics/skills SKILL.md conventions.

This skill should be used when configuring or using the OpenCode CLI for headless LLM automation. Use when the user asks to "configure opencode", "use opencode cli", "set up opencode", "opencode run command", "opencode model selection", "opencode providers", "opencode vertex ai", "opencode mcp servers", "opencode ollama", "opencode local models", "opencode deepseek", "opencode kimi", "opencode mistral", "fallback cli tool", or "headless llm cli". Covers command syntax, provider configuration, Vertex AI setup, MCP servers, local models, cloud providers, and subprocess integration patterns.

Control Tuya devices via local Home Assistant (tuya-local) or Tuya Cloud using the tuya-hub Go CLI.

Edge function development patterns for Cloudflare Workers. Use when creating API endpoints, handling requests, or working with bindings.

Activate when users need help setting up cloud security monitoring for AWS, Azure, or GCP, including adapter configuration, detection rules, and threat response.

Perform OSINT, subdomain enumeration, port scanning, web reconnaissance, email harvesting, and cloud asset discovery for initial access. Use when gathering intelligence or mapping attack surface.

CloudBase platform knowledge and best practices. Use this skill for general CloudBase platform understanding, including storage, hosting, authentication, cloud functions, database permissions, and data models.

Complete knowledge domain for Cloudflare Workers AI - Run AI models on serverless GPUs across Cloudflare's global network.Use when: implementing AI inference on Workers, running LLM models, generating text/images with AI,configuring Workers AI bindings, implementing AI streaming, using AI Gateway, integrating withembeddings/RAG systems, or encountering "AI_ERROR", rate limit errors, model not found, tokenlimit exceeded, or neurons exceeded errors.Keywords: workers ai, cloudflare ai, ai bindings, llm workers, @cf/meta/llama, workers ai models,ai inference, cloudflare llm, ai streaming, text generation ai, ai embeddings, image generation ai,workers ai rag, ai gateway, llama workers, flux image generation, stable diffusion workers,vision models ai, ai chat completion, AI_ERROR, rate limit ai, model not found, token limit exceeded,neurons exceeded, ai quota exceeded, streaming failed, model unavailable, workers ai hono,ai gateway workers, vercel ai sdk workers, openai compatible workers, workers ai ve