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概要と使いどころ
Complete toolkit for programmatic video creation with Remotion + React. Covers animations, timing, rendering (CLI/Node.js/Lambda/Cloud Run), captions, 3D, charts, text effects, transitions, and media handling. Use when writing Remotion code, building video generation pipelines, or creating data-driven video templates.
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。
Maps observed adversary behaviors, security alerts, and detection rules to MITRE ATT&CK techniques and sub-techniques to quantify detection coverage and guide control prioritization. Use when building an ATT&CK-based coverage heatmap, tagging SIEM alerts with technique IDs, aligning security controls to adversary playbooks, or reporting threat exposure to executives. Activates for requests involving ATT&CK Navigator, Sigma rules, MITRE D3FEND, or coverage gap analysis.
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。
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
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, data-backed email marketing knowledge base. 908 sources, 4,798 insights. Use when reviewing email setups, building automation flows, diagnosing deliverability, writing email copy, selecting platforms, or pulling Standards. Covers strategy, flows, deliverability, copywriting, segmentation, compliance, cold email, and 19 industry playbooks.
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。
Technical guide for creating a new Galyarder Framework agent adapter. Use when building a new adapter package, adding support for a new AI coding tool (e.g. a new CLI agent, API-based agent, or custom process), or when modifying the adapter system. Covers the required interfaces, module structure, registration points, and conventions derived from the existing claude-local and codex-local adapters.
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。
Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making. Use when analyzing financial statements, building valuation models, assessing budget variances, or constructing financial projections and forecasts. Also applicable when users mention financial modeling, cash flow analysis, company valuation, financial projections, or spreadsheet analysis.
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。
Gathers information from multiple sources in parallel, compares what they say, flags where they agree or conflict, and delivers a clean synthesis with a confidence rating for each finding. Useful for making evidence-backed decisions, when evaluating competing claims, during due diligence on a vendor or market, and for building research briefs before strategy sessions. Use when the user says "research this", "synthesize multiple sources", "compare sources", "research report", "what does the evidence say", "gather information on", or "deep dive into".
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。
Multi-step content production pipeline that takes a topic or brief and produces a full blog post, email newsletter excerpt, and three social posts — all in your voice. Useful for building a content batch, when repurposing a core idea across formats, during content sprint sessions, and for turning expertise into publishable material. Use when the user says "create content", "content pipeline", "blog to social", "write and repurpose", "content engine", or "create a blog post and social posts".
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。
End-to-end meeting workflow skill. Pre-meeting: research attendees, build agenda, prepare talking points, create pre-read. Post-meeting: process notes into action items, draft follow-up emails, log decisions, update project notes. Useful for preparing for important calls, during post-meeting processing, when following up with attendees, and for building a running decision log. Use when the user says "prepare for meeting", "meeting prep", "process meeting notes", "meeting follow up", "meeting machine", or "prep for my call".
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。
Sets up a file-based memory system so Cowork always knows who you are, how you work, and where your projects stand. For eliminating repetitive re-introductions at session start, when building persistent context across multiple projects, or during initial Cowork onboarding. Use when the user says "claude doesn't remember me", "memory system", "persistent context", "why does it forget", "remember my preferences", "I keep re-explaining myself", or "how do I make Claude remember things".
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。
Interviews you about a task you repeat often, then walks you through building a custom skill for it using Cowork's built-in skill creator — no coding required. For packaging a repeating workflow into a one-phrase trigger, when teaching Cowork your personal process from scratch, or during a skill library build session. Use when the user says "create a skill", "teach claude my workflow", "custom skill", "make cowork do this automatically", "automate my process", "I do this every week", or "how do I make a skill".
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 reliable, safe, and trustworthy agent systems that fail gracefully and operate within bounds. Use when building guardrails, handling edge cases, preventing harmful outputs, monitoring for failures, implementing safety constraints, or designing error recovery. Covers failure modes, constraint systems, oversight mechanisms, and safety validation.
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。
Multi-agent coordination patterns for building effective AI teams
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 in designing, orchestrating, and managing multi-agent systems (MAS). Specializes in agent collaboration patterns, hierarchical structures, and swarm intelligence. Use when building agent teams, designing agent communication, or orchestrating autonomous 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。
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。
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.
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 building AI agents using prompt-native architecture where features are defined in prompts, not code. Use it when creating autonomous agents, designing MCP servers, implementing self-modifying systems, or adopting the "trust the agent's intelligence" philosophy.
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 IoT engineer specializing in connected device architectures, edge computing, and IoT platform development. Masters IoT protocols, device management, and data pipelines with focus on building scalable, secure, and reliable IoT solutions.
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 applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
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 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.
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。
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.
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 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.
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 effective AI agent systems with clear architecture, capability planning, and tool integration. Use when building agent systems, designing agent workflows, planning tool ecosystems, defining agent roles and boundaries, or architecting multi-agent systems. Covers agent patterns, agentic loops, capability design, and system composition.
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。
Use when creating, improving, or troubleshooting Claude Code subagents. Expert guidance on agent design, system prompts, tool access, model selection, and best practices for building specialized AI 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。