「simulator」の検索結果

Packages an agent for CARLA Leaderboard submission — builds the docker image with make_docker.sh (plain or ROS variant), checks the four required roots and the egg layout it assumes, sets the agent/track/routes environment inside the image, and verifies the image can import the stack and load the agent before submission. Use when the user asks to "build the leaderboard docker image", "submit to the leaderboard", "package my agent", or make_docker.sh fails.

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。

Reads a specific actor's live telemetry from a running CARLA server — location and rotation, velocity and speed, acceleration, angular velocity, and for vehicles the control input (throttle/steer/brake), front-wheel steer angle and mass. All kinematics come from one world snapshot so they are frame-consistent. Use when the user asks "how fast is it going", "where/what heading is the car", "show the ego's telemetry", or "stream a vehicle's state". Resolve ambiguous targets with the world-data 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。

Spawns and attaches sensors on a running CARLA server — cameras (rgb/depth/semantic/instance/optical-flow/normals), lidar, radar, IMU, GNSS, collision/lane-invasion/obstacle — to the ego or any actor, with a mount transform and blueprint attributes (resolution, fov, sensor_tick, lidar range/points, …). Also sets up native ROS 2 publishing (--ros to enable_for_ros, --ros-name/--ros-frame-id topic and TF naming) and prints the topics the sensor will publish. Use when the user asks to "add a camera/lidar/sensor", "put a dashcam on the ego", "attach a depth camera", "mount a sensor", or "publish a sensor to ROS". Prints the sensor id; read its data with the read-sensor 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。

Lists and toggles a map's static environment objects via get_environment_objects / enable_environment_objects — hide or show buildings, vegetation, poles, fences, traffic signs and other baked assets by CityObjectLabel (and optional name filter). Use when the user asks to "hide/remove the buildings", "turn off the trees/vegetation", "show only the roads", "disable the fences", or "list the environment objects". Affects rendering and collision; resets on map reload.

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。

Directly drives a specific vehicle on a running CARLA server — raw VehicleControl (throttle/steer/brake/reverse/hand-brake), Ackermann speed control, vehicle lights, opening/closing doors, and physics-control tuning; ros-info reports the native ROS 2 command topics (vehicle_control_cmd, ackermann_control_cmd) for the hero. Targets the ego by default. Use when the user asks to "drive/steer the car", "accelerate/brake/reverse", "set a target speed", "turn on the headlights/blinkers/brake lights", "open a door", "drive the car from ROS", or "change the vehicle's mass/drag/physics". This is manual control (autopilot off) — for TM-driven traffic use control-traffic.

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 and interpret iOS Simulator ETTrace profiles. Use when profiling launch or runtime latency, comparing traces, or finding CPU-heavy stacks.

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。

Payoff Simulation reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.

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。

Run the root-level workflow runtime policy or rule-based rollouts and verify simulator success. Use for evaluation, checkpoints, or local controllers; do not use for replay or dataset annotation.

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。

Runs quantum computing workflows on AWS through Amazon Braket — discovering devices (QPUs and simulators) and their availability, building gate-model circuits and analog Hamiltonian programs, submitting quantum tasks, program sets and hybrid jobs, looking up prices, and capping spend with spending limits. Applies to any request about quantum computing, quantum hardware, quantum simulation, AHS, OpenQASM, or running a quantum algorithm on AWS.

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。

Evaluate Expo skills in this repo end-to-end - trigger accuracy, generated code quality, and runtime screenshots on iOS simulator and Android emulator via Expo Go (web optional). Use when the user wants to eval an Expo skill, test that a skill produces working code, benchmark a skill with device screenshots, or verify a skill's output renders correctly.

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 native-feeling, benchmark-quality mobile app screens (Expo / React Native). Use when designing or implementing any mobile UI — screens, flows, onboarding, paywalls, tab bars, sheets, settings, empty states — or when polishing motion, navigation, typography, dark mode, or perceived performance. Enforces Apple HIG fidelity, semantic colors, native controls, anti-slop discipline, navigation semantics (push vs replace, modal vs sheet vs overlay, the one-way doors where back must not exist), purposeful Reanimated motion, a full-motion simulator-verified iteration loop, and a study-real-apps-first workflow (pairs with the Appllama MCP). Trigger on "build a screen", "make this screen better", "design the onboarding", "wire up this flow", "polish the UI", "make it feel native", or any mobile design/implementation task.

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。

Simulate realistic coding interview 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。

Compare and implement eviction policies (LRU, LFU, FIFO, S3FIFO, ARC) for bounded-capacity caches. Use when choosing or implementing an eviction policy for a buffer pool, page cache, CDN edge, or LLM KV cache, or when writing a replay simulator that supports multiple policies. Clarifies recency vs frequency semantics, queue topology, saturating counters, ghost buffers, and the second-chance rule that distinguishes modern FIFO-family policies from classic LRU.

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 this skill when converting natural language flight commands into waypoints and timing for a drone simulator. Covers parsing commands like "Take off to X m height in Y seconds", "Hover at X m height for Y seconds", "Fly from (x,y,z) to (x',y',z') in T seconds", and "Land from X m height in Y seconds" into structured (4×n) waypoint arrays and segment mode lists.

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。

GitHub Actions workflow patterns for React Native iOS simulator and Android emulator cloud builds with downloadable artifacts. Use when setting up CI build pipelines or downloading GitHub Actions artifacts via gh CLI and GitHub API.

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。

Run automatic SPICE simulations on subcircuits detected from KiCad schematic analysis — validates filter frequencies, divider ratios, opamp gains, LC resonance, and crystal load capacitance. Supports ngspice, LTspice, and Xyce (auto-detected). Generates testbenches, runs batch mode, produces structured pass/warn/fail report. Use when the user asks to simulate, verify, or validate any analog subcircuit — RC filters, LC filters, voltage dividers, opamp circuits, crystal oscillators. Also for "simulate my circuit", "run spice", "verify with simulation", "check my filter cutoff", "does this divider give the right voltage", "what's the bandwidth of this opamp stage". Consider suggesting simulation during design reviews when the schematic analyzer reports simulatable subcircuits and a SPICE simulator is available.

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。

Run automatic SPICE simulations on subcircuits detected from KiCad schematic analysis — validates filter frequencies, divider ratios, opamp gains, LC resonance, and crystal load capacitance. Supports ngspice, LTspice, and Xyce (auto-detected). Generates testbenches, runs batch mode, produces structured pass/warn/fail report. Use when the user asks to simulate, verify, or validate any analog subcircuit — RC filters, LC filters, voltage dividers, opamp circuits, crystal oscillators. Also for "simulate my circuit", "run spice", "verify with simulation", "check my filter cutoff", "does this divider give the right voltage", "what's the bandwidth of this opamp stage". Consider suggesting simulation during design reviews when the schematic analyzer reports simulatable subcircuits and a SPICE simulator is available.

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 asking about Axiom skills or axbuild build/test capture, xclog console, xcsym .ips/MetricKit/.crash symbolication, xcui simulator UI/accessibility, or xcprof xctrace/CPU profiles.

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 ANY iOS or macOS build fails, a crash log needs diagnosing, a test run crashes, Xcode misbehaves, or an environment issue blocks work before code is the suspect. Covers build failures, dependency conflicts, simulator diagnostics.

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 capturing or analyzing ETTrace profiles for a focused iOS launch or runtime flow, including exact-build dSYM UUID matching, Simulator or device capture, processed per-thread flamegraph JSON, sampled inclusive/exclusive time, unresolved symbols, and comparable verification. Use debugging-instruments or swiftui-performance for generic profiling instead.

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 capturing or analyzing an iOS .memgraph, especially when the task mentions a memory leak, heap growth, persistent memory increase, ownership path, or matched-capture comparison with Apple CLI tools. Covers unambiguous Simulator capture, leaks/heap/vmmap/malloc_history evidence, raw artifact preservation, and same-flow verification. Use debugging-instruments for interactive Xcode Memory Graph, Instruments, generic retain-cycle inspection, or LLDB work.

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 CarPlay-enabled apps using the CarPlay framework. Use when creating navigation, audio, communication, EV charging, parking, or food ordering apps for the car display, working with CPTemplateApplicationScene, CPInterfaceController template hierarchies, CPListTemplate, CPMapTemplate, CPNowPlayingTemplate, configuring CarPlay entitlements, or integrating with CarPlay Simulator for testing.

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。

Set up and run wireless network simulations using the Wireless Network Toolbox. Use this skill when creating system-level simulations with wirelessNetworkSimulator, adding traffic sources (networkTrafficOnOff, networkTrafficFTP, networkTrafficVoIP, networkTrafficVideoConference), configuring node mobility, logging events or IQ samples, visualizing traffic, scheduling actions during simulation, running parametric sweeps, writing PCAP files with pcapWriter or technology-specific PCAP writers, registering event callbacks on wireless nodes, accessing event data fields, or combining multiple capture/visualization tools in a simulation.

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。

Orchestrate iOS screenshot automation with xcodebuild/simctl for build-run, AXe for UI actions, JSON settings and plan files, Koubou-based framing (`asc screenshots frame`), and screenshot upload (`asc screenshots upload`). Use when users ask for automated screenshot capture, AXe-driven simulator flows, frame composition, or screenshot-to-upload 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。