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概要と使いどころ
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
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。
Manage Alibaba Cloud DNS (Alidns) using the @alicloud/alidns20150109 TypeScript SDK. Use when working with DNS resolution on Alibaba Cloud, including domain management, DNS record CRUD (A, AAAA, CNAME, MX, TXT, SRV, CAA, etc.), DNS load balancing (DNSSLB), custom resolution lines, DNSSEC, domain groups, batch operations, Cloud GTM (Global Traffic Manager), DNS GTM, GTM Classic, recursive DNS, DNS cache, Public DNS (PDNS), DNS over HTTPS (DoH), ISP cache flush, domain statistics, and resource tagging. Covers all 234 APIs of the Alidns 20150109 version.
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。
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, 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。
This skill should be used when the user asks about "plugin settings", "store plugin configuration", "user-configurable plugin", ".local.md files", "plugin state files", "read YAML frontmatter", "per-project plugin settings", or wants to make plugin behavior configurable. Documents the .claude/plugin-name.local.md pattern for storing plugin-specific configuration with YAML frontmatter and markdown content.
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。
SwiftUI architecture patterns, state management with @Observable, view composition, navigation, performance optimization, and modern iOS/macOS UI best practices.
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。
Verification loop for Spring Boot projects: build, static analysis, tests with coverage, security scans, and diff review before release or PR.
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。
Kotlin Coroutines and Flow patterns for Android and KMP — structured concurrency, Flow operators, StateFlow, error handling, and testing.
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。
Verification loop for Laravel projects: env checks, linting, static analysis, tests with coverage, security scans, and deployment readiness.
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。
Frontend development patterns for React, Next.js, state management, performance optimization, and UI best practices.
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。
REST API design patterns including resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting for production APIs.
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。
Compose Multiplatform and Jetpack Compose patterns for KMP projects — state management, navigation, theming, performance, and platform-specific UI.
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 .NET types for performance. Seal classes, use readonly structs, prefer static pure functions, avoid premature enumeration, and choose the right collection types.
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。
[AUTO-INVOKE] MUST be invoked when debugging failed on-chain transactions. Covers transaction receipt analysis, gas diagnosis, calldata decoding, revert reason extraction, and state verification. Trigger: any task involving failed tx analysis, revert debugging, or on-chain transaction troubleshooting.
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。
Akka.Management for cluster bootstrapping, service discovery (Kubernetes, Azure, Config), health checks, and dynamic cluster formation without static seed nodes.
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。
Choosing the right concurrency abstraction in .NET - from async/await for I/O to Channels for producer/consumer to Akka.NET for stateful entity management. Avoid locks and manual synchronization unless absolutely necessary.
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。
Comprehensive AI/ML development guide for LangChain, LangGraph, and ML model integration in FastAPI. Use when building LLM applications, agents, RAG systems, sentiment analysis, aspect-based analysis, chain orchestration, prompt engineering, vector stores, embeddings, or integrating ML models with FastAPI endpoints. Covers LangChain patterns, LangGraph state machines, model deployment, API integration, streaming, error handling, and best practices.
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。
AgentHero AI - Hierarchical multi-agent orchestration system with PM coordination, file-based state management, and interactive menu interface. Use when managing complex multi-agent workflows, coordinating parallel sub-agents, or organizing large project tasks with multiple specialists. All created agents use aghero- prefix.
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。
Transition from static LLM chats to autonomous agents that execute multi-step tasks. Use this when you need to automate cross-platform reports (e.g., Snowflake to Google Docs), build self-service tools for non-technical teams, or create "anticipatory" engineering workflows that draft PRs based on Slack discussions.
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 functional software prototypes and MVPs without deep technical skills by using AI agents as "developers in your pocket." Use this skill when you need to validate a new product concept, build custom back-office tools (e.g., a real estate data manager), or create high-fidelity demos to unblock engineering roadmaps.
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 multi-agent AI workflows with orchestration, tool use, and state 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。
Optimize ElevenLabs conversational AI agents for real estate applications. Use when creating new agents, improving conversation quality, selecting voices, engineering system prompts, configuring agent parameters, or analyzing agent performance metrics. Includes voice selection, model tuning, prompt engineering, and A/B testing 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。
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
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。
Interactive code review for agent iterations. Captures comments, tracks resolution status, and integrates with git diffs.
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。
Designs multi-step agent workflows with tool usage, retry logic, state management, and budget controls. Provides orchestration diagrams, tool execution order, fallback strategies, and cost limits. Use for "AI agents", "agentic workflows", "multi-step AI", or "autonomous 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。