7,332 件 ・ 関連度順
概要と使いどころ
Drag and spring: production-level createDraggable, bounds, friction and spring. Use when implementing, reviewing or testing drag and spring for React, Vite, Next.js or Perfect_AI projects.
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。
Accessible motion: production-level reduced motion, seizure prevention, pause controls. Use when implementing, reviewing or testing accessible motion for React, Vite, Next.js or Perfect_AI projects.
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。
Animation instrumentation: production-level frame timing, scroll state and ownership conflicts. Use when implementing, reviewing or testing animation instrumentation for React, Vite, Next.js or Perfect_AI projects.
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。
Brand palette reasoning: production-level category, trust, culture, hierarchy. Use when implementing, reviewing or testing brand palette reasoning for React, Vite, Next.js or Perfect_AI projects.
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。
Color vision and contrast: production-level WCAG contrast on composited layers. Use when implementing, reviewing or testing color vision and contrast for React, Vite, Next.js or Perfect_AI projects.
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。
WAAPI and compositing: production-level GPU-friendly transform/opacity, offscreen pausing. Use when implementing, reviewing or testing waapi and compositing for React, Vite, Next.js or Perfect_AI projects.
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。
Animation storyboard: production-level frame states and scroll-beats production spec. Use when implementing, reviewing or testing animation storyboard for React, Vite, Next.js or Perfect_AI projects.
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。
Complex timelines: production-level relative offsets, labels, reversibility, orchestration. Use when implementing, reviewing or testing complex timelines for React, Vite, Next.js or Perfect_AI projects.
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。
Easing mathematics: production-level cubic bezier, damped spring, velocity continuity. Use when implementing, reviewing or testing easing mathematics for React, Vite, Next.js or Perfect_AI projects.
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。
Scroll-driven choreography: production-level sticky progress, sync, enter/leave, bidirectional timeline. Use when implementing, reviewing or testing scroll-driven choreography for React, Vite, Next.js or Perfect_AI projects.
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。
Layout changes: production-level FLIP layout, additive composition, measurement. Use when implementing, reviewing or testing layout changes for React, Vite, Next.js or Perfect_AI projects.
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。
Accessibility automation: production-level axe audits and manual keyboard checks. Use when implementing, reviewing or testing accessibility automation for React, Vite, Next.js or Perfect_AI projects.
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。
Anime.js v4 core animations: production-level target selection, property keyframes, duration, ease, loop, play/pause. Use when implementing, reviewing or testing anime.js v4 core animations for React, Vite, Next.js or Perfect_AI projects.
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。
Responsive scope: production-level createScope lifecycle, media query gating, cleanup. Use when implementing, reviewing or testing responsive scope for React, Vite, Next.js or Perfect_AI projects.
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。
Delegate independent research, implementation, or verification in parallel when it can save time after dispatch and review overhead, or when explicitly requested. Keep decisions and final integration in the main 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。
Implement User and Entity Behavior Analytics using Elasticsearch/OpenSearch to build behavioral baselines, calculate anomaly scores, perform peer group analysis, and detect insider threat indicators such as data exfiltration, privilege abuse, and unauthorized access patterns.
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。
Deploys deception-based honeytokens in Active Directory including fake privileged accounts with AdminCount=1, fake SPNs for Kerberoasting detection (honeyroasting), decoy GPOs with cpassword traps, and fake BloodHound paths. Monitors Windows Security Event IDs 4769, 4625, 4662, 5136 for honeytoken interaction. Use when implementing AD deception defenses for detecting lateral movement, credential theft, and reconnaissance.
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。
Deploys and configures osquery for real-time endpoint monitoring using SQL-based queries to inspect running processes, open ports, installed software, and system configuration. Use when building visibility into endpoint state, threat hunting across fleet, or implementing compliance monitoring. Activates for requests involving osquery deployment, endpoint visibility, fleet management, or SQL-based endpoint querying.
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。
Detects anomalous authentication patterns using UEBA analytics, statistical baselines, and machine learning models to identify impossible travel, credential stuffing, brute force, password spraying, and compromised account behaviors across authentication logs. Activates for requests involving authentication anomaly detection, login behavior analysis, UEBA implementation, or suspicious sign-in investigation.
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。
Executes containment strategies to stop active adversary operations and prevent lateral movement during a confirmed security breach. Implements short-term and long-term containment using network segmentation, endpoint isolation, credential revocation, and access control modifications. Activates for requests involving breach containment, lateral movement prevention, network isolation, active threat containment, or live incident response.
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。
Configure secure OAuth 2.0 authorization flows including Authorization Code with PKCE, Client Credentials, and Device Authorization Grant. This skill covers flow selection, PKCE implementation, token
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。
Implement Microsoft's Enhanced Security Admin Environment (ESAE) tiered administration model for Active Directory. Covers Tier 0/1/2 separation, privileged access workstations (PAWs), administrative f
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。
Implement a vulnerability aging dashboard and SLA tracking system to measure remediation performance against severity-based timelines and drive accountability.
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。
Designs and implements VLAN-based network segmentation on managed switches to isolate network zones, enforce access control between segments, and reduce the attack surface by limiting lateral movement paths in enterprise network 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。