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Hand off a task with only the context needed to continue in a fresh session. Use for "handoff", "引き継ぎ", "別セッションへ渡す", or "別マシンで続ける". The orca subcommand launches an independent Orca workspace or terminal tab; without it, produce a paste-ready prompt backed by a verified remote branch or PR. Do not launch sessions for capability questions or design requests.
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Plan and execute a comprehensive red team engagement covering reconnaissance through post-exploitation using MITRE ATT&CK-aligned TTPs to evaluate an organization's detection and response capabilities.
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Simulates man-in-the-middle attacks using Ettercap, mitmproxy, and Bettercap in authorized environments to intercept, analyze, and modify network traffic for testing encryption enforcement, certificate validation, and detection capabilities.
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Build comprehensive threat actor profiles using open-source intelligence (OSINT) techniques to document adversary motivations, capabilities, infrastructure, and TTPs for proactive defense.
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12 regulatory & QM agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. ISO 13485 QMS, MDR 2017/745, FDA 510(k)/PMA, ISO 27001 ISMS, GDPR/DSGVO, risk management (ISO 14971), CAPA, document control, auditing. Python tools (stdlib-only).
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Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
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Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Trigger only when the user explicitly asks to threat model a codebase or path, enumerate threats/abuse paths, or perform AppSec threat modeling. Do not trigger for general architecture summaries, code review, or non-security design work.
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Use when the user explicitly asks for a desktop or system screenshot (full screen, specific app or window, or a pixel region), or when tool-specific capture capabilities are unavailable and an OS-level capture is needed.
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Compress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance, transferring GPT-4 capabilities to open-source models, or reducing inference costs. Covers temperature scaling, soft targets, reverse KLD, logit distillation, and MiniLLM training strategies.
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Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. Use when training large-scale models with limited compute (5× cost reduction vs dense models), implementing sparse architectures like Mixtral 8x7B or DeepSeek-V3, or scaling model capacity without proportional compute increase. Covers MoE architectures, routing mechanisms, load balancing, expert parallelism, and inference optimization.
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Create new scientific tools for ToolUniverse framework with proper structure, validation, and testing. Use when users need to add tools to ToolUniverse, implement new API integrations, create tool wrappers for scientific databases/services, expand ToolUniverse capabilities, or follow ToolUniverse contribution guidelines. Supports creating tool classes, JSON configurations, validation, error handling, and test examples.
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Video and audio processing capabilities for Flutter applications
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Write model cards documenting AI capabilities. TRIGGERS - Use when user needs help with ai-model-card-writer related tasks.
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Design planning capabilities for AI agents. TRIGGERS - Use when user needs help with ai-agent-planning related tasks.
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Gets a custom map into CARLA on UE 5.8 — the four distinct routes and which one to pick — via Util/Tools/Import.py for FBX+OpenDRIVE assets into a source build, CARLA_MAPS_TO_COOK to ship a map inside a package, or client.generate_opendrive_world() for an OpenDRIVE-only map at runtime with no build at all. Covers where imported assets land, why an imported map cannot be loaded from a package by name, and the four capabilities the UE4 skill has that ue58 lacks — standalone asset packages, their installer, semantic-material tagging, and a pedestrian navmesh that is generated but silently skipped. Use when the user asks to "import a map", "add a custom map", "load my .xodr", "package my own town", or "create a standalone map package".
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App Store Connect API 4.5.1 (REST) アプリ配布リファレンス。JWT 認証、API キー作成・失効、 Apps, Builds, Bundle IDs, Bundle ID Capabilities, Certificates, Devices, Provisioning Profiles, Users, User Invitations, Merchant IDs, Pass Type IDs、TestFlight (Beta Groups / Testers)、 Sandbox Testers、App Review, Review Submissions, Customer Reviews, Custom Product Pages, Phased Release、In-App Purchases, Subscriptions, Subscription Groups, App Price Points, Promotional Offers, Win-back Offers, Sales Reports、App Asset Library (screenshots / app previews)、 Webhooks / Webhook Events / Deliveries、Xcode Cloud (Workflows, Build Runs, Artifacts)、 Alternative Distribution (EU マーケットプレイス / Web Distribution)、 Game Center (Achievements, Leaderboards, Challenges)、Analytics / 診断レポート。
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Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
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Capture screenshots on registered computers, record on macOS or HarmonyOS, and manage saved captures. Probe capabilities before recording.
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Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
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Installs 425 bioinformatics skills covering sequence analysis, RNA-seq, single-cell, variant calling, metagenomics, structural biology, and 56 more categories. Use when setting up bioinformatics capabilities or when a bioinformatics task requires specialized skills not yet installed.
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Build search applications with vector, hybrid, and semantic search capabilities.
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Azure Fabric Management SDK for Python. Use for managing Microsoft Fabric capacities and resources.
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Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability.
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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
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