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Spawns vehicles on a running CARLA server and destroys them — scattered across the map's spawn points on Traffic Manager autopilot, a row queued in a single lane at a fixed spacing, or a single hero/ego vehicle (optionally named for native ROS 2 publishing with --ros-name). Covers blueprint filtering, the atomic autopilot hand-off, and cleanup. Use when the user asks to "spawn vehicles/cars/traffic", "add N cars driving around", "put cars in a lane 15 m apart", "spawn the ego/hero vehicle", or "remove the vehicles".

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。

Imports an FBX vehicle into a CARLA source build as a spawnable vehicle.<make>.<model> — checks the FBX carries CARLA's 4-wheel bone rig, imports the mesh, then assembles the vehicle through CarlaTools' VehicleAuthoringLibrary (physics asset with kinematic wheel bodies, retargeted anim blueprint, four configured wheel blueprints, the vehicle blueprint), registers it in VehicleFactory through CARLA's own add_vehicle_to_vehicle_factory.py, and verifies it spawns, drives and steers. Use when the user asks to "add a car/truck/van to CARLA", "import a vehicle FBX", or needs a custom drivable vehicle spawnable from the Python 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。

Draws debug overlays in a running CARLA world via world.debug — points, lines, arrows, bounding boxes, and text strings, each with a colour and lifetime. Use when the user asks to "draw/mark/highlight a point or box in the world", "visualise a path/waypoints", "label a location", or "show something on the map for debugging". Shapes are an overlay, not actors.

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。

Runs standard-format scenarios through ScenarioRunner — ASAM OpenSCENARIO 1.x (.xosc, via --openscenario, with catalogs and ParameterDeclaration overrides) and OpenSCENARIO 2.0 (.osc, via --openscenario2, the ANTLR/osc2 pipeline). Validates a file against the schema before running, lists the bundled examples, and reports which OSC features ScenarioRunner actually implements. Use when the user asks to "run an xosc", "run an OpenSCENARIO file", "use the OpenSCENARIO standard", "run a .osc / OSC2 scenario", or hands over a scenario file from another tool.

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 pedestrians that wander autonomously via WalkerAIController, and destroys them in the correct order. Pairs each walker.pedestrian.* with a controller.ai.walker, places them on the navigation mesh, and sends them to random navmesh points at walking speed. Use when the user asks to "spawn pedestrians/walkers", "add people/crowds", "make pedestrians walk around", or "remove the walkers". Reads the world settings first: if the world is already synchronous it never ticks it, and if it is asynchronous it makes it synchronous and drives the clock itself.

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。

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。

Downloads CARLA so nothing has to be fetched by hand — an official release package for any published version (resolved live from the GitHub releases, with AdditionalMaps), the rolling nightly Dev build, a shallow source checkout of a branch or tag, or the carlasim/carla Docker image. Reports exactly what was obtained and where, plus the environment variables the other skills read. Use when the user asks to "download CARLA", "get CARLA 0.9.16", "install CARLA", "clone the carla repo", "fetch the latest CARLA", or has no CARLA at all yet.

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 a single ScenarioRunner Python scenario (or a whole group) against a running CARLA server — FollowLeadingVehicle, ControlLoss, DynamicObjectCrossing, SignalizedJunctionLeftTurn and the rest of srunner/examples — in sync or async mode, with result output, recording and manual/agent control of the ego. Lists what is runnable on the checked-out branch and on the loaded map. Use when the user asks to "run a scenario", "test FollowLeadingVehicle", "list scenarios", "run a CARLA traffic scenario", or reports a scenario that is "not supported".

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。

Imports FBX meshes into a CARLA source build as spawnable static.prop.* blueprints — pass a directory whose subdirectories name the semantic tags, or a single FBX with its tag, and the props are imported into content, registered, added to the prop factory and verified by spawning. Use when the user asks to "add a prop to CARLA", "import an FBX as a prop", "add street furniture/benches/signs", or needs a custom mesh spawnable from the Python 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。

Installs the CARLA Autonomous Driving Leaderboard (leaderboard.carla.org) at a chosen version — 1.0, 2.0 or 2.1 — together with the exact scenario_runner branch and CARLA build each one requires, then wires the four-root PYTHONPATH and verifies the whole stack imports. Detects which version an existing checkout is by reading its code, not its branch name. Use when the user asks to "install the leaderboard", "set up the CARLA challenge", "evaluate my driving agent", "reproduce my leaderboard score", or names a leaderboard version.

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。

Inspects a recorded CARLA .log without replaying it — show_recorder_file_info for the header/actors/frames, collision queries between actor categories, and blocked-actor queries for vehicles that got stuck. Use when the user asks to "what's in this recording", "show recorder info", "which vehicles collided", "find collisions in the log", or "which actors were blocked/stuck".

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。

Drives a vehicle to a destination autonomously using CARLA's navigation agents (BasicAgent/BehaviorAgent/ConstantVelocityAgent), or plans a route between two points with GlobalRoutePlanner. The agent handles routing, obstacle avoidance and traffic-light obedience. Use when the user asks to "drive the ego to (x,y,z)", "navigate to the junction", "go to that location", "plan a route from A to B", or "make the car drive itself somewhere specific". Manual control is control-vehicle; autopilot roaming is 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。

Installs the CARLA Python client (the `carla` package) into a chosen interpreter so the other python-api skills work — from a wheel bundled with your release or checkout, from PyPI (`pip install carla==X.Y.Z`), or by putting an older release's .egg on PYTHONPATH. Detects what is already present, picks the source that matches your simulator's version, pins numpy<2, and verifies `import carla` plus the client/server version match. Use when the user asks to "install the CARLA Python API", "pip install carla", "set up the carla python package", or when a skill reports "cannot import carla".

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 Scenic probabilistic scenarios against a running CARLA server with the `scenic FILE --simulate --2d` CLI — the carlaChallenge1-10 traffic scenarios shipped by ScenarioRunner (`model srunner.scenic.models.model`) and by Scenic itself (`model scenic.simulators.carla.model`) — bounding the run, sampling scenes headlessly first to tell a map problem from a syntax problem, and restoring the world afterwards. Use when the user asks to "run a Scenic scenario", "run carlaChallenge", "test a .scenic file", "scenic --simulate", or reports a Scenic scenario that rejects every sample or cannot find blueprints.

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。

Expert database administrator specializing in high-availability systems, performance optimization, and disaster recovery. Masters PostgreSQL, MySQL, MongoDB, and Redis with focus on reliability, scalability, and operational excellence.

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。

Expert infrastructure security engineer specializing in DevSecOps, cloud security, and compliance frameworks. Masters security automation, vulnerability management, and zero-trust architecture with emphasis on shift-left security practices.

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。

Expert payment integration specialist mastering payment gateway integration, PCI compliance, and financial transaction processing. Specializes in secure payment flows, multi-currency support, and fraud prevention with focus on reliability, compliance, and seamless user 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。

Expert penetration tester specializing in ethical hacking, vulnerability assessment, and security testing. Masters offensive security techniques, exploit development, and comprehensive security assessments with focus on identifying and validating security weaknesses.

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。

Expert legal advisor specializing in technology law, compliance, and risk mitigation. Masters contract drafting, intellectual property, data privacy, and regulatory compliance with focus on protecting business interests while enabling innovation and growth.

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。

Expert dependency manager specializing in package management, security auditing, and version conflict resolution across multiple ecosystems. Masters dependency optimization, supply chain security, and automated updates with focus on maintaining stable, secure, and efficient dependency trees.

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。

Operate E2B agent sandboxes using the CLI. Use when user needs to run code in isolation, test packages, execute commands safely, or work with binary files in a sandbox environment. Keywords: sandbox, e2b, isolated environment, run code, test code, safe execution.

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 agent-adapted STRIDE + access-control analysis on an agent system. Produces a ranked risk list with agentic mitigations (scope / split / filter / gate / review).

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。

Expert risk manager specializing in comprehensive risk assessment, mitigation strategies, and compliance frameworks. Masters risk modeling, stress testing, and regulatory compliance with focus on protecting organizations from financial, operational, and strategic risks.

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。