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概要と使いどころ
API reference: Core Animation (QuartzCore). Query for CALayer, CAAnimation, CABasicAnimation, CAKeyframeAnimation, CASpringAnimation, CATransaction, CAShapeLayer, CAGradientLayer, CAEmitterLayer, CATransform3D, CADisplayLink.
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 writing a literature review article (narrative, scoping PRISMA-ScR or systematic). Scaffolds a 7-part skeleton with a scope and non-overlap statement, summary-table stubs and reporting-guideline wiring, without inventing citations. Original research is /write-paper.
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 choosing the model for a medical-imaging study. Picks a paper-grounded architecture family (CNN/ViT, U-Net/nnU-Net, detection, SAM/foundation, GNN), then vets the concrete repo or checkpoint for licence, version pin, weight provenance and benchmark overlap.
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 DreamerV2 2.2.0 for TensorFlow world-model reinforcement-learning training, custom Gym integration, typed experiment configuration, replay/checkpoint management, and JSONL/TensorBoard evaluation.
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 EasyR1 for multimodal LLM RL post-training, dataset/reward preparation, core API debugging, and checkpoint export 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。
Use Dexbotic to prepare DexData, train and serve vision-language-action policies, evaluate checkpoints, and integrate explicitly external RL or robot backends.
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。
Routes DI-engine users to the right workflow for CLI/config launches, serial and framework-based RL pipelines, and environment integration.
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 DreamerV3 for world-model reinforcement learning training, embodied environment dataflow, JAX model internals, result operations, and troubleshooting.
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。
Route DeepLabCut markerless pose-estimation workflows, project setup, PyTorch training/inference, maDLC tracking, Model Zoo, post-processing, 3D, and export 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。
Use AReaL for large-scale asynchronous LLM reinforcement learning, agentic RL, distributed post-training, inference/agent services, backend planning, and customization 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。
Guides Any4LeRobot dataset conversions, LeRobot-to-RLDS export, and LeRobot v1.6-v3.0 format migrations with schema validation, version-aware environments, and safe publication boundaries.
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 someone has a business problem, strategic question, or founder challenge they need to think through clearly. Triggers on "I'm stuck on", "should I", "what's wrong with my", "diagnose", "strategy problem", "business problem", "founder problem", "help me think through". Runs structured consulting-style diagnostic lenses to produce a comprehensive 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。
Use when a completed Shell scenario planning exercise needs to be converted into a TikTok script. Triggers when user says "make a tiktok", "tiktok script", "generate tiktok", or "content from scenario". Requires a completed scenario with narratives, findings, and worldview integration.
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。
External recon and OSINT pipeline - subdomain enum, live host discovery, URL crawl, JS analysis, nuclei scan. Outputs to Attack-surface.md and scope/. Queries wiki before each phase. Use when starting recon on any target.
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ICS/SCADA/OT exploitation - Modbus (502), S7comm (102), EtherNet/IP (44818), DNP3, OpenPLC, Node-RED SCADA, PLC/HMI/coil/holding-register attacks. Use when a target exposes industrial protocols or the goal is to drive a plant to a dangerous state (over-pressure/over-speed/disable interlock) and read the flag the HMI/CCTV reveals.
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。
Wiki-first "what do I use" lookup - pick the automated TOOL (wiki/tools/), then the PAYLOAD/technique (wiki/payloads/ + wiki/cheatsheets/), for a surface/service/vuln-class BEFORE hand-rolling or working from memory. Use for "tool for <service>", "automated tools for web/<service>", "what should I run on <surface>", "which tool for <X>", "payloads for <X>", "payload arsenal", "cheatsheet for <X>", "how do I exploit <tech/class>", "exploit/attack chain for <X>", "arsenal", any SSRF/XSS/SQLi/SSTI/LFI/JWT/XXE/IDOR/NoSQL/deserialization/CSRF/CORS/CRLF/GraphQL/smuggling/web-cache/OAuth/SAML/MFA/crypto/LDAP/XPath/WebAuthn/file-upload/IMDS/prompt-injection/Modbus ask, plus "privesc arsenal", "CVE arsenal", "default creds", "nuclei templates", "sqlmap/hydra/nmap/bloodhound", "password attacks".
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。
Capture a Burp Suite Repeater request/response as a PoC image (targets/<eng>/poc/) by driving the Burp MCP + the Kali GUI. Replays a request in a Repeater tab, sends it, and grabs the request+response panes - a Burp-native PoC (client report / CTF writeup). Use when you want the evidence to come from Burp rather than a curl/terminal card, or whenever you drive a target through Burp and need the images. Pairs with hunt-burp.
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。
Photorealistic AAA art direction for Blender including photogrammetry cleanup, real-world scale, high-poly workflows, PBR accuracy, and scan optimization. Use for cinematic and AAA game realism.
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。
Architectural visualization in Blender for interiors/exteriors with real-world scale, camera composition, PBR materials, and still/animation delivery via MCP.
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。
Art direction for RPG, JRPG, CRPG, ARPG, and MMORPG worlds in Blender including loot rarity reads and region identity.
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。
Biome and setting art direction for Blender covering underwater, desert, arctic, jungle, underground, and floating-island environments.
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 polishing, diagnosing, tailoring, or exporting resumes for LLM, RAG, Agent, Agentic RL, post-training, pretraining, AIGC, search/ranking, multimodal, AI backend, or LLM algorithm internships from raw resume text, a materials folder, and/or a target job description. Audits evidence, maps JD fit, enforces truth boundaries, writes polished and targeted resumes, generates interviewer-style grilling questions, answer cards, evidence-upgrade plans, and optional open-source project recommendations without fabricating experience.
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。
Research and advise on the best way to approach a software project, including architecture, tech stack, implementation strategy, pricing/operating-cost tradeoffs, benchmark research, and comparisons with similar real-world projects. Use before building, mid-build, or after completion when the user asks for project strategy, optimal approach, research comparables, similar projects, stack selection, vendor/service choice, repo analysis, architecture critique, implementation feedback, or a prioritized improvement plan. Avoid for narrow single-bug debugging or isolated file edits unless the user asks for broader project direction.
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 user asks to "research", "fact-check", "check the history", "is this accurate", "research notes", "sources", "historical accuracy", "technical accuracy", "how would this really work", "verify a detail", "interview an expert", "plan a site visit", "expert review", or needs to investigate and record the real-world facts a story relies on and the chapters that use them.
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。