「production-ready」の検索結果

Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start optimization. Use when ", aws, lambda, serverless, api-gateway, dynamodb" mentioned.

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。

Master AI-powered game asset pipelines using ComfyUI, Stable Diffusion, FLUX, ControlNet, and IP-Adapter. Creates production-ready sprites, textures, UI, and environments with consistency, proper licensing, and game engine integration. Use when "AI game art, generate game assets, ComfyUI game, stable diffusion sprites, AI texture generation, character consistency AI, procedural art generation, SDXL game assets, FLUX textures, train LoRA game, AI tileable texture, spritesheet generation, " mentioned.

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。

Creates production-ready MCP servers using FastMCP v2. Use when building MCP servers, optimizing tool descriptions for context efficiency, implementing progressive disclosure for multiple capabilities, or packaging servers for distribution.

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 and implement distinctive, production-ready frontend interfaces with strong aesthetic direction. Use when asked to create or restyle web pages, components, or applications (HTML/CSS/JS, React, Vue, etc.).

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。

Plan new YouTube videos with optimized titles, thumbnails, and hooks. Use when planning a video, writing or reviewing opening hooks, generating title and thumbnail concepts, or creating a production-ready video plan backed by research.

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。

Generate accurate, runnable quantitative strategy code for the JoinQuant (聚宽) platform. Use this skill when the user asks to write a stock/ETF/futures backtest, paper-trading, or live-trading strategy on JoinQuant — the skill provides progressive-disclosure access to the complete JoinQuant API knowledge base (14 categories, 294KB official docs), 5 production-ready strategy templates (single-stock MA, multi-factor, ETF rotation, momentum, mean-reversion), and a lint tool that catches hallucinated APIs, future-function violations, and unset price-mode/slippage/commission. Chinese-friendly. Code generated by this skill should paste directly into the JoinQuant online editor without modification.

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 production-ready prompt package — system prompt, few-shot examples, output format, edge case handling, eval criteria. Use when asked to "prompt engineering", "build a prompt", "write a system prompt", or "improve this prompt".

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 guide for converting UI screenshots, mockups, Figma frames, and whiteboard sketches into production-ready frontend code using vision-capable frontier models (Gemini 4 Pro, Claude 5.5, GPT Astra 6) — multi-pass visual extraction, component decomposition, responsive generation, and design token mapping / Panduan ahli konversi screenshot UI, mockup, frame Figma, dan sketsa whiteboard menjadi kode frontend siap produksi menggunakan model frontier berkemampuan vision — ekstraksi visual multi-pass, dekomposisi komponen, generasi responsif, dan pemetaan design token.

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。

Master orchestrator to build an application from scratch to a production-ready release, enforcing strict step-by-step progression and continuous documentation / Orkestrator utama untuk membangun aplikasi dari nol hingga rilis siap produksi dengan dokumentasi bertahap.

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。

Ultimate production readiness skill that orchestrates all relevant skills (frontend, backend, security, performance, SEO, testing, DevOps) to harden applications before deployment / Skill kesiapan produksi utama yang mengorkestrasi semua skill relevan (frontend, backend, keamanan, performa, SEO, testing, DevOps) untuk mengeraskan aplikasi sebelum 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 a ChatGPT/Codex Plugin needs a production-ready visual identity and SVG logo system that clearly expresses the Plugin's job across light and dark surfaces.

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 production-ready AI agents with Microsoft Foundry and Agent Framework. Use when creating AI agents, selecting LLM models, implementing agent orchestration, adding tracing/observability, or evaluating agent quality. Covers agent architecture, model selection, multi-agent workflows, and production 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。

Amplication is an open source developer platform for generating production-ready backend services and scaffolding from a visual workflow. This skill fits agents that need to help with service generation, codebase setup, schema-driven backend work, or self-hosted Amplication environments.

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。

Bridges asset requirements from motion design specs to production-ready assets. Parses specs for required assets, recommends free/paid sources, provides format conversion guidance, generates validated import code, and offers asset preparation checklists. Use when preparing assets for Remotion projects or when asked "where to get assets", "how to prepare assets", "asset formats for Remotion".

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。

Master orchestrator that chains all Remotion video creation skills together in a single automated pipeline. Takes a creative brief and produces a complete, production-ready Remotion video project. Use when starting a new video from scratch, when asked to "create a video", "make a video", "build a complete video", or "video from idea to code".

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。

Converts a Stitch screen, a local HTML file, or a URL into production-ready Next.js 15 App Router components — Server vs Client split, dark mode via CSS variables, TypeScript strict, ARIA, and responsive mobile-first layout. Only the Stitch route needs an API key.

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 custom AI agents in Claude Code from a user's problem statement. This skill analyzes the user's use case, asks smart clarifying questions, researches the internet for similar agents (GitHub repos, blogs, Claude Code community patterns), and then architects and builds production-ready Claude Code agents — including subagents, skills, hooks, slash commands, MCP integrations, and CLAUDE.md configuration. Use this skill whenever the user wants to create an agent, build an automation workflow, set up a Claude Code subagent, design a multi-agent system, or says things like 'build me an agent for...', 'automate this with Claude Code', 'I want a subagent that...', 'help me create a workflow', 'set up an agent pipeline', or any variation of wanting Claude Code to do something specialized. Also trigger when the user mentions agent architecture, agent SDK, agentic workflows, or task delegation in Claude Code — even if they don't use the word 'agent' explicitly.

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。

Create production-ready Kubernetes manifests for Deployments, Services, ConfigMaps, and Secrets following best practices and security standards. Use when generating Kubernetes YAML manifests, creating K8s resources, or implementing production-grade Kubernetes configurations.

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。

Rules for Drizzle ORM schema design, query patterns, migration workflows, and relational query usage. Ensures type-safe, production-ready database interactions.

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。

Convert Figma designs into production-ready code using MCP server tools. Use this skill when users provide Figma URLs, request design-to-code conversion, ask to implement Figma mockups, or need to extract design tokens and system values from Figma files. Works with frames, components, and entire design files to generate HTML, CSS, React, or other frontend code.

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。

Generate production-ready React/Next.js code from Figma designs. Instructs proper Figma MCP tool usage, component reuse strategies, and variant mapping. **CRITICAL: ALWAYS use this skill when user provides a Figma link or mentions implementing/redesigning from Figma design.** Never attempt manual implementation without invoking this skill first.

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。

Create production-ready Grafana dashboards with reusable panels, template variables, annotations, and provisioning for version-controlled dashboard deployment. Use when creating visual representations of Prometheus, Loki, or other data source metrics, building operational dashboards for SRE teams, migrating from manual dashboard creation to version-controlled provisioning, or establishing executive-level SLO compliance reporting.

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 whenever the user wants to use AI agents to work with Penpot design files via the Penpot MCP Server. Triggers include: using Penpot through an AI agent, design files, design systems, design tokens, Penpot MCP, design-to-code, generating UI from design, auditing a design system, creating components/variants, renaming layers, exporting assets from Penpot, adding flows, interactions, animations, overlays, or prototyping in Penpot, or prompting an AI agent to read/modify a Penpot file. Also triggers when the user wants to set up Penpot MCP, connect any MCP-compatible AI agent or IDE to Penpot, or produce production-ready HTML/CSS/React from a Penpot design. Use this skill for Penpot-agent workflows — design, code, audit, prototyping, or setup.

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 robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.

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。