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概要と使いどころ
Entity Framework Core best practices including NoTracking by default, query splitting for navigation collections, migration management, dedicated migration services, and common pitfalls to avoid.
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 stable, compatible public APIs using extend-only design principles. Manage API compatibility, wire compatibility, and versioning for NuGet packages and distributed 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。
Microsoft.Extensions.Options patterns including IValidateOptions, strongly-typed settings, validation on startup, and the Options pattern for clean configuration 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。
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。
Import or register a local project with Agentuity Cloud. Requires authentication. Use for project management operations
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。
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。
Build stateful AI agents using the Cloudflare Agents SDK. Load when creating agents with persistent state, scheduling, RPC, MCP servers, email handling, or streaming chat. Covers Agent class, AIChatAgent, state management, and Code Mode for reduced token usage.
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。
How to spawn, manage, message, and command subagents via gobby-agents.
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。
Branch skill for building and improving agents. Use when creating new agents, adapting marketplace agents, validating agent structure, writing system prompts, or improving existing agents. Triggers: 'create agent', 'improve agent', 'validate agent', 'fix agent', 'agent frontmatter', 'system prompt', 'adapt agent', 'customize agent', 'agent examples', 'agent tools'.
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。
Dynamic agent composition and management system. USE WHEN user says create custom agents, spin up custom agents, specialized agents, OR asks for agent personalities, available traits, agent voices. Handles custom agent creation, personality assignment, voice mapping, and parallel agent orchestration.
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 and manage AI agent skills following best practices. Use when creating new skills, optimizing context, designing multi-agent systems, or implementing progressive disclosure 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。
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。
Create, use, and manage Agent Skills for Claude. Use when working with Skills, creating custom capabilities, or understanding how Skills extend Claude's functionality. Covers Skill architecture, file structure, 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。
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。
Expert task distributor specializing in intelligent work allocation, load balancing, and queue management. Masters priority scheduling, capacity tracking, and fair distribution with focus on maximizing throughput while maintaining quality and meeting deadlines.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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 and manage AI agent sessions with multiple backends (SDK, Claude CLI, Codex, Cursor). Also supports multi-agent workflows with shared context, @mention coordination, and collaborative voting. Use for "start agent session", "create worker", "run agent", "multi-agent workflow", "agent collaboration", "test with tools", or when orchestrating AI conversations programmatically.
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。
Central authority for Claude Agent SDK (TypeScript and Python SDKs). Covers SDK installation, authentication (Anthropic key, Bedrock, Vertex), sessions and resumption, forking sessions, streaming vs single mode, custom tools, permissions (allowedTools, disallowedTools, permissionMode), MCP integration, system prompts (CLAUDE.md, appendSystemPrompt, outputStyle), cost tracking, todo tracking, structured outputs, hosting patterns, plugins, and SDK branding guidelines. Assists with building custom agents, configuring SDK options, and troubleshooting SDK issues. Delegates 100% to docs-management skill for official documentation.
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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。
Automatically applies when designing multi-agent systems. Ensures proper tool schema design with Pydantic, agent state management, error handling for tool execution, and orchestration 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。
Create, refine, and manage issues. Use for creating new issues from loose ideas, refining ambiguous issues, bulk operations, or JSON export.
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。
Human and agent coordination protocol for repos using .agentprotocol. Use to manage TODO intake, open and archived work items, and plan/build docs with deterministic indexes.
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Expert knowledge synthesizer specializing in extracting insights from multi-agent interactions, identifying patterns, and building collective intelligence. Masters cross-agent learning, best practice extraction, and continuous system improvement through knowledge 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。