「systems」の検索結果

Model a Phase-Locked Loop (PLL) IC from its datasheet or system specs using Mixed-Signal Blockset. Without this skill, agents universally select the wrong solver and produce non-functional PLL models — 100% of unguided attempts fail. Covers Integer-N, Fractional-N, Dual Modulus architectures, loop filter design, lock time optimization, VCO phase noise configuration, and msbPllArchitectures/msbPllFoundation block assembly. Use when: PLL modeling, frequency synthesizer design, phase noise simulation, lock time analysis, charge pump design, loop filter tuning, datasheet-to-model, Mixed-Signal Blockset PLL, msbPllArchitectures.

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 machine vision inspection systems with MATLAB Visual Inspection Toolbox. Covers the full arc from problem selection through deployment: anomaly detection (Student-Teacher, PatchCore, FastFlow, FCDD), object detection (YOLOX), counting (CounTR, shape matching), gauging and measurement (caliper, fitcircle, fitangle), blob analysis (regionprops, calibrated measurement), shape matching for fixturing and localization, synthetic data generation for training augmentation, and deployment to standalone apps, embedded C/C++, NVIDIA GPUs (TensorRT), NPUs (ONNX), and Beckhoff PLCs. Routes to rule-based tools when problems are geometric and deterministic, AI-based tools when defect appearance varies, and hybrid pipelines combining both.

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。

Launch and control the MATLAB Radar Designer app programmatically via MCP. Use when designing radar systems, configuring parameters, comparing radar types, analyzing performance metrics, or managing radar design sessions.

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 RoadRunner HD Map entities in MATLAB — lanes, boundaries, markings, junctions, signs, signals, barriers, parking. Use when creating driving scenes from scratch, authoring road networks for simulation and testing automated driving systems, or assembling RRHD maps from Lanelet2 or other HD map sources.

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Perform aerospace unit conversions, time conversions, coordinate frame transformations, and rotation representations using Aerospace Toolbox. Use when converting units (length, velocity, angle, acceleration, angular velocity, force, mass, pressure, temperature, density), computing Julian dates or decimal years, transforming between coordinate frames (ECEF, ECI, LLA, flat Earth, geodetic/geocentric, NED, body, wind, stability), or working with rotation representations (Euler angles, DCM, quaternion, Rodrigues vector). Also use when the user asks about aerospace coordinate systems, reference frames, or rotation conventions.

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Scan systems and dependencies for CVEs and security vulnerabilities. Use tools like Nessus, OpenVAS, and Qualys to identify and prioritize vulnerabilities. Use when performing security assessments, compliance scanning, or vulnerability management.

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Conduct threat modeling using STRIDE methodology. Identify threats, assess risks, and design security controls. Use when designing secure systems or assessing application security.

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。

Administer Windows Server systems. Manage IIS, Active Directory, and PowerShell automation. Use when administering Windows infrastructure.

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。

Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.

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。

Apply CIS benchmarks and secure Linux servers. Configure SSH, manage users, implement firewall rules, and enable security features. Use when hardening Linux systems for production or meeting security compliance requirements.

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Secure Docker images and container runtime configurations. Implement non-root users, read-only filesystems, and security contexts. Use when building secure container images or hardening container deployments.

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。

Defend AI systems against prompt injection and indirect prompt attacks using input controls, tool permissions, output validation, and isolation boundaries.

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Harden AI/LLM deployments against prompt injection, data exfiltration, model theft, and supply chain attacks. Covers input validation, output filtering, access control, model API security, and compliance controls for production AI systems.

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。

Manage users, groups, and permissions on Linux systems. Configure sudo and access controls. Use when managing system access.

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 NFS servers and clients. Implement network file sharing for Linux systems. Use when setting up shared storage.

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System administration for Linux servers. Manage packages, services, and system configuration. Use when administering Linux systems.

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Set up alerting rules, configure on-call rotations, and manage incident response workflows. Integrate with PagerDuty, Opsgenie, or Grafana OnCall for alert routing and escalation. Use when implementing alerting strategies and on-call management for production systems.

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Orchestrate AI/ML pipelines for data ingestion, model training, batch inference, and RAG indexing using Prefect, Airflow, or Dagster. Build reliable, observable, and retriable workflows for production AI systems.

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Monitor and evaluate RAG systems with retrieval quality metrics, groundedness checks, hallucination detection, and continuous regression testing.

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Customer loyalty and rewards — points systems, VIP tiers, referral programs, app selection

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Deep research and discovery before building something new. Explores local projects for reusable code, researches competitors, reads forums and reviews, analyses plugin ecosystems, investigates technical options, and produces a comprehensive research brief. Three depths: focused (30 min), wide (1-2 hours), deep (3-6 hours). Triggers: 'research this', 'discovery', 'explore the space', 'what should I build', 'competitive analysis', 'before I start building', 'research before coding'. Not for cited fact-checking research reports (a separate harness does those); this is pre-build product discovery.

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。

Modern web design trends, principles, and implementation patterns for 2024-2025. Use this skill when designing websites, creating interactive experiences, implementing design systems, ensuring accessibility, or building performance-first interfaces. Triggers on tasks involving modern design trends, micro-interactions, scrollytelling, bold minimalism, cursor UX, glassmorphism, accessibility compliance, performance optimization, or design system architecture. References animation skills (GSAP, Framer Motion, React Spring), 3D skills (Three.js, R3F, Babylon.js), and component libraries for implementation guidance.

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。

Fast, lightweight 2D rendering engine for creating interactive graphics, particle effects, and canvas-based applications using WebGL/WebGPU. Use this skill when building 2D games, particle systems, interactive canvases, sprite animations, or UI overlays on 3D scenes. Triggers on tasks involving PixiJS, 2D rendering, sprite sheets, particle effects, filters, or high-performance canvas graphics. Alternative to Canvas2D with WebGL acceleration for rendering thousands of sprites at 60 FPS.

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。

Lightweight WebGL/WebGPU game engine with entity-component architecture and visual editor integration. Use this skill when building browser-based games, interactive 3D applications, or performance-critical web experiences. Triggers on tasks involving PlayCanvas, entity-component systems, game engine development, WebGL games, 3D browser applications, editor-first workflows, or real-time 3D rendering. Alternative to Three.js with game-specific features and integrated development environment.

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。