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概要と使いどころ
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".
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This skill should be used when the model's ROLE_TYPE is orchestrator and needs to delegate tasks to specialist sub-agents. Provides scientific delegation framework ensuring world-building context (WHERE, WHAT, WHY) while preserving agent autonomy in implementation decisions (HOW). Use when planning task delegation, structuring sub-agent prompts, or coordinating multi-agent workflows.
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。
Get external agent review and feedback. Routes Anthropic models through Claude Agent SDK (uses local subscription) and other models through OpenRouter API. Use for code review, architecture feedback, or any external consultation.
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Extract and display the final message from a Claude agent JSONL file. Use when the user wants to see an agent report, view agent output, extract agent results, check what an agent produced, or read the final response from a subagent. Triggers on requests like "show me agent report", "what did agent X produce", "extract agent output", "view agent results", or "get the report from agent ad42ecb".
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。
Analyze issues to identify the next work item and update focus.md. Enforces issue-first workflow and confidence-based batch limits.
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。
Extract, plan, or propose implementation details at configurable depth levels (low/normal/extensive). Outputs to reference files for team discussion and handoff.
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Install AgentOps into a new or existing project. Handles .agent/ setup and .github/ merging.
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 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。
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.
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。
Agent parameter passing, memory files, and data handoffs between 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。
Expert context manager specializing in information storage, retrieval, and synchronization across multi-agent systems. Masters state management, version control, and data lifecycle with focus on ensuring consistency, accessibility, and performance at scale.
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。
Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.
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。
Check agent configuration coverage across hierarchy levels and phases. Use to ensure complete agent system coverage.
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。
Evaluate agent performance using a structured scoring rubric
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。
Launches specialized Claude agents for targeted tasks. Analyzes requirements, selects appropriate agent, and executes with optimized configuration.
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。
Used to create a new agent. Used when a user wants to create a new agent
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 legal advisor specializing in technology law, compliance, and risk mitigation. Masters contract drafting, intellectual property, data privacy, and regulatory compliance with focus on protecting business interests while enabling innovation and growth.
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Create and optimize Claude Code subagent files (.claude/agents/*.md) following official best practices. Use when user asks to create a subagent, agent file, custom agent, or needs help structuring agent files with YAML frontmatter.
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Design AI agents with recommended patterns and architectures
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Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm
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。
Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.
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Design and implement evaluation frameworks for AI agents. Use when testing agent reasoning quality, building graders, doing error analysis, or establishing regression protection. Framework-agnostic concepts that apply to any SDK.
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Stop AI agents from secretly bypassing your rules. Mechanical enforcement with git hooks, secret detection, deployment verification, and import registries. Born from real production incidents: server crashes, token leaks, code rewrites. Works with Claude Code, Clawdbot, Cursor. Install once, enforce forever.
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 C++ developer specializing in modern C++20/23, systems programming, and high-performance computing. Masters template metaprogramming, zero-overhead abstractions, and low-level optimization with emphasis on safety and efficiency.
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。