Coordinate multiple AI agents and skills for complex workflows
Skills（SKILL.md）は、AIエージェント（Claude Code、Cursor、Codexなど）に特定の能力を追加するための設定ファイルです。
詳しく見る →Coordinate multiple AI agents and skills for complex workflows
Expert agent organizer specializing in multi-agent orchestration, team assembly, and workflow optimization. Masters task decomposition, agent selection, and coordination strategies with focus on achieving optimal team performance and resource utilization.
Generate standardized .agent-os directory structure with product documentation, mission, tech-stack, roadmap, and decision records. Enables AI-native workflows.
Expert penetration tester specializing in ethical hacking, vulnerability assessment, and security testing. Masters offensive security techniques, exploit development, and comprehensive security assessments with focus on identifying and validating security weaknesses.
Expert PHP developer specializing in modern PHP 8.3+ with strong typing, async programming, and enterprise frameworks. Masters Laravel, Symfony, and modern PHP patterns with emphasis on performance and clean architecture.
Expert platform engineer specializing in internal developer platforms, self-service infrastructure, and developer experience. Masters platform APIs, GitOps workflows, and golden path templates with focus on empowering developers and accelerating delivery.
Expert project manager specializing in project planning, execution, and delivery. Masters resource management, risk mitigation, and stakeholder communication with focus on delivering projects on time, within budget, and exceeding expectations.
Track and optimize agent specialization during methodology development. Use when agent specialization emerges (generic agents show >5x performance gap), multi-experiment comparison needed, or methodology transferability analysis required. Captures agent set evolution (Aₙ tracking), meta-agent evolution (Mₙ tracking), specialization decisions (when/why to create specialized agents), and reusability assessment (universal vs domain-specific vs task-specific). Enables systematic cross-experiment learning and optimized M₀ evolution. 2-3 hours overhead per experiment.
Write effective system prompts for TD AI agents. Covers role definition, constraint specification, output formatting, tool usage instructions, and prompt structure patterns.
Ready-to-use prompt templates for specialized agents. Use when building n8n workflows, AI integrations, or sales materials. Contains structured prompts for automation-architect, llm-engineer, and sales-automator agents.
Expert research analyst specializing in comprehensive information gathering, synthesis, and insight generation. Masters research methodologies, data analysis, and report creation with focus on delivering actionable intelligence that drives informed decision-making.
Expert Rust developer specializing in systems programming, memory safety, and zero-cost abstractions. Masters ownership patterns, async programming, and performance optimization for mission-critical applications.
Expert sales engineer specializing in technical pre-sales, solution architecture, and proof of concepts. Masters technical demonstrations, competitive positioning, and translating complex technology into business value for prospects and customers.
Operate E2B agent sandboxes using the CLI. Use when user needs to run code in isolation, test packages, execute commands safely, or work with binary files in a sandbox environment. Keywords: sandbox, e2b, isolated environment, run code, test code, safe execution.
Agent SDK development utilities for creating, testing, and managing AI agents with comprehensive tooling and debugging capabilities.
Systematic framework for selecting the optimal specialized agent for any task. Use when delegating to subagents via the Task tool to ensure the most appropriate specialist is chosen based on framework, domain, task type, and complexity. Applies decision tree logic to match tasks with agent expertise.
Creates new agent skills following modern best practices with proper structure and documentation. Use when asked to build a new skill, organize skill resources, design skill descriptions, or validate skill structure for portability across Copilot platforms.
Guide creation of focused single-purpose agents following the One Agent One Prompt One Purpose principle. Use when designing new agents, refactoring general agents into specialists, or optimizing agent context for a single task.
Expert Spring Boot engineer mastering Spring Boot 3+ with cloud-native patterns. Specializes in microservices, reactive programming, Spring Cloud integration, and enterprise solutions with focus on building scalable, production-ready applications.
Expert Swift developer specializing in Swift 5.9+ with async/await, SwiftUI, and protocol-oriented programming. Masters Apple platforms development, server-side Swift, and modern concurrency with emphasis on safety and expressiveness.
Expert technical writer specializing in clear, accurate documentation and content creation. Masters API documentation, user guides, and technical content with focus on making complex information accessible and actionable for diverse audiences.
Expert Terraform engineer specializing in infrastructure as code, multi-cloud provisioning, and modular architecture. Masters Terraform best practices, state management, and enterprise patterns with focus on reusability, security, and automation.
Test agent delegation patterns to verify hierarchy and escalation paths. Use after modifying agent structure.
Expert tooling engineer specializing in developer tool creation, CLI development, and productivity enhancement. Masters tool architecture, plugin systems, and user experience design with focus on building efficient, extensible tools that significantly improve developer workflows.
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.
Complete workflow for building, implementing, and testing goal-driven agents. Orchestrates building-agents-* and testing-agent skills. Use when starting a new agent project, unsure which skill to use, or need end-to-end guidance.
LLM prompt management and evaluation platform. Version prompts, run A/B tests, evaluate with metrics, and deploy with confidence using Agenta's self-hosted solution.
Asistente especializado en investigación académica, redacción científica, ACD, metodología cualitativa y análisis de datos con prevención de plagio
AI assistant for creating clear, actionable task descriptions for GitHub Copilot agents
Features in LivestockAI must now be designed for **dual consumption**: Humans (UI) and Agents (MCP/API).
Architecture guidelines for Jarvy CLI - codebase structure, tool implementation patterns, registry system, platform-specific code organization, and module conventions.
Generate a project-specific AGENTS.md from a user goal, then confirm before overwriting.
Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.
AIコーディングエージェント向けの指示書「AGENTS.md」を作成するスキル。プロジェクトにAIエージェントが作業するための文脈と指示を集約するファイルを作成したい場合に使用します。「AGENTS.mdを作成」「AIエージェント用の指示書を作る」「エージェント向けREADMEを作成」などのリクエストでトリガーします。OpenAI Codex、Claude Code、GitHub Copilot、Cursorなど、複数のAIエージェントで共通利用できるオープンな標準フォーマットです。
Create or update root and nested AGENTS.md files that document scoped conventions, monorepo module maps, cross-domain workflows, and (optionally) per-module feature maps (feature -> paths, entrypoints, tests, docs). Use when the user asks for AGENTS.md, nested agent instructions, or a module/feature map.
Get a specific vector entry by key. Requires authentication. Use for Agentuity cloud platform operations
Create and maintain AgentV YAML evaluation files for testing AI agent performance. Use this skill when creating new eval files, adding eval cases, or configuring custom evaluators (code validators or LLM judges) for agent testing workflows.
Agile ceremonies and sprint management specialist. Use when running standups,
When facilitating sprint retrospectives or team improvement sessions.
Comprehensive ahooks React hooks library specialist. Expert in all 76+ ahooks hooks including state management, effects, data fetching, performance optimization, DOM utilities, and advanced patterns. Use when working with ahooks library, need React hooks utilities or want to learn best practices.
Air Handler Configuration & Sizing Agent
Quality Assurance & Design Validation Agent
<skill>
<skill>
<skill>
测试用例生成 Skill，负责根据 SoT 文档和业务代码生成 pytest 测试用例。
Comprehensive L&D framework for upskilling DevOps/IaC/Automation teams to become AI Agent Engineers. Covers LLM literacy, RAG, agent frameworks, multi-agent systems, and LLMOps. Designed to help traditional automation teams compete with OpenAI and Anthropic.
ai-app
Leveraging AI coding assistants and tools to boost development productivity, while maintaining oversight to ensure quality results.
AI-powered code generation for boilerplate, tests, data, and scaffolding