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Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.

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에이전트 간 상호작용 구조와 워크플로우 정의

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Agent skill for mesh-coordinator - invoke with $agent-mesh-coordinator

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Expert Flutter specialist mastering Flutter 3+ with modern architecture patterns. Specializes in cross-platform development, custom animations, native integrations, and performance optimization with focus on creating beautiful, native-performance applications.

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Expert fintech engineer specializing in financial systems, regulatory compliance, and secure transaction processing. Masters banking integrations, payment systems, and building scalable financial technology that meets stringent regulatory requirements.

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Bootstrap new 33GOD ecosystem agents with standardized configuration. Use when creating new agents, spawning workers, deploying Yi nodes, or when the user says "spin up an agent", "create a new agent", "deploy a new worker", or needs a new agent for a specific pipeline role. Handles workspace creation, config injection, skill installation, provider mirroring, channel binding, and 33GOD ecosystem onboarding (GOD Docs, Plane, Bloodbank, memory).

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Visual context analyzer for AI agents. Provides screenshots, accessibility scans, DOM snapshots, and element descriptions for web pages. Use when you need to see what a web page looks like, analyze accessibility issues, inspect DOM structure, or get detailed element information. Triggers on requests like "take a screenshot", "check accessibility", "what does this page look like", "analyze the UI", "inspect this element", or any visual/UI analysis task.

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Create specialized agent experts with pre-loaded domain knowledge using the Act-Learn-Reuse pattern. Use when building domain-specific agents that maintain mental models via expertise files and self-improve prompts.

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Perpetual autonomous work loop for Claude Code — no end condition, no memory regression, no context overfill. Maintains a persistent ledger across all sessions.

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Generates Claude Code plugin agent .md files: writes YAML frontmatter (name, model, color, tools, hooks, disallowedTools), crafts system prompts, and creates triggering example blocks with context and commentary. Validates agent structure against naming, length, and format constraints. Use when the user asks to create an agent, add an agent, write a subagent, configure agent frontmatter, design agent system prompts, set agent tools or colors, build an autonomous agent, or add agent hooks.

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Claude Code agent generation system that creates custom agents and sub-agents with enhanced YAML frontmatter, tool access patterns, and MCP integration support following proven production patterns

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Standardized reference documentation section structure for agents - project guidance, conventions, related agents, and Skills. Use when implementing or updating agent documentation.

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Manage specification documents in .agent/specs/. Use when user provides requirements, acceptance criteria, or feature descriptions that need to be tracked and validated against implementation.

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Conduct structured interviews with the user. Use when multiple decisions need user input: ask ONE question at a time, wait for response, record answer, then proceed to next question.

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Create/update .agent/constitution.md. Use when commands/boundaries/constraints must be confirmed before baseline or code changes. Draft v0 from repo evidence, then interview user.

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Make an out-of-session agent AgentOps-native via skills + ao CLI + CI, not hooks.

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Agentic workflow patterns for autonomous LLM reasoning. Use when building ReAct agents, implementing reasoning loops, or creating LLMs that plan and execute multi-step tasks.

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Agent skill for crdt-synchronizer - invoke with $agent-crdt-synchronizer

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Design and build custom Claude Code agents with effective descriptions, tool access patterns, and self-documenting prompts. Covers Task tool delegation, model selection, memory limits, and declarative instruction design. Use when: creating custom agents, designing agent descriptions for auto-delegation, troubleshooting agent memory issues, or building agent pipelines.

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This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

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Create, update, review, fix, or debug VS Code agent customization files (.instructions.md, .prompt.md, .agent.md, SKILL.md, copilot-instructions.md, AGENTS.md). Use for: saving coding preferences; troubleshooting why instructions/skills/agents are ignored or not invoked; configuring applyTo patterns; defining tool restrictions; creating custom agent modes or specialized workflows; packaging domain knowledge; fixing YAML frontmatter syntax.

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Use when creating expert agents. Generates agent.md with frontmatter, hooks, required sections, and skill references.

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This skill should be used when the user asks to "create an agent", "write a subagent", "generate agent definition", "add agent to plugin", "write agent frontmatter", "create autonomous agent", "build subagent", needs agent structure guidance, YAML frontmatter configuration, invocation criteria with examples, or wants to add specialized subagents to Claude Code plugins with proper capabilities lists and tool access definitions.

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Agent skill for consensus-coordinator - invoke with $agent-consensus-coordinator

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