「agentic ai」の検索結果

Adds a new ROS 2 message type to CARLA's native ROS 2 interface — the hand-written POD struct under LibCarla/source/carla/ros2/types/msg, its Fast-CDR serialize/deserialize pair, the RIHS01 type hash computed in Docker, the CdrTopicInfo registration and the type-hash test. Use when the user asks to "add a ROS message type", "support sensor_msgs/X in CARLA", "add a carla_msgs type", "why is my type hash warning appearing", or needs a message CARLA does not publish yet. There is no IDL codegen — every step is manual.

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。

Queries the live CARLA world and resolves an entity description into a concrete actor id — find actors by type, role, or colour, or the single one nearest a point/actor; read the world snapshot; get static level bounding boxes by label; cast rays for semantic points; project a point to the ground; or (ros-topics) list the native ROS 2 topics each actor should be publishing and why any is silent. Identifies by stable attributes, not by any rank/order. Use when the user asks "what actors are here", "find the red prius", "the vehicle nearest the ego", "list the pedestrians", or needs a specific actor id for another 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。

Replays a CARLA .log recorded by the recorder — the whole run or a time window, at any speed, following a chosen actor, optionally regenerating sensors and restoring weather. Use when the user asks to "replay the recording", "play back the run", "watch it again in slow motion / at 2x", "follow vehicle N during replay", or "replay onto a different map".

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 CARLA Leaderboard results.json — per-route driving score, route completion, infraction penalty and the infraction lists — explains how the score was computed for that leaderboard version, and rescores an existing result under the other version's rules (2.0 multiplicative vs 2.1 additive) without re-running anything. Also diffs two runs and merges sharded result files. Use when the user asks "what did I score", "why is my score low", "did my agent pass", "why don't my scores match the leaderboard", or hands over a results.json.

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。

Writes an autonomous agent for the CARLA Leaderboard — an AutonomousAgent subclass with setup/sensors/run_step/destroy, a sensor suite inside the track's budget, and the right constructor signature for the leaderboard version (1.0 and 2.x differ). Generates a working skeleton, validates the sensor configuration against the real per-track limits offline, and covers the ROS1/ROS2 agent base classes. Use when the user asks to "write a leaderboard agent", "make my agent work with the leaderboard", "add sensors to my agent", "port my agent to 2.1", or hits SensorConfigurationInvalid.

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 Scenic, the probabilistic scenario description language, for the CARLA in use — pip installing it into the same interpreter that holds the CARLA client, optionally cloning the upstream repo for the example scenarios the wheel does not ship, and verifying that the `scenic` CLI, the client and Scenic's version-keyed blueprint table all agree. Use when the user asks to "install Scenic", "set up Scenic", "download Scenic", "pip install scenic", wants to run `.scenic` files, or has a Scenic whose model import or blueprint lookup 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。

Builds CARLA (branch ue4-dev, Unreal Engine 4.26) from source on Linux end-to-end — UE4 fork, the Carla server (editor C++ modules), the LibCarla Python client wheel, and content — then verifies them against a from-source server. Optionally builds the native ROS 2 interface in (ROS2=1 → --ros2, Fast-DDS/CycloneDDS/Zenoh), which is compile-time only and cannot be enabled later. Use when the user asks to "build CARLA from source", "compile CARLA ue4-dev", "set up CARLA on Ubuntu (incl. 24.04)", "build CARLA with ROS2 support", or "produce a CARLA server + client wheel". Cooking a distributable Dist/ package is a separate skill (package-carla-ue4); running the build is run-carla-server.

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 CARLA's ScenarioRunner (the official scenario engine) and picks the branch that matches the CARLA in use — master for 0.9.14-0.9.16 (UE4), ue5-master for 0.10.0 (UE5), leaderboard-1.0/2.0/2.1 when driving the Leaderboard. Clones or checks out the branch, installs requirements, wires PYTHONPATH (including the `agents` package the carla wheel does not ship), and verifies the import. Use when the user asks to "install scenario runner", "set up SR", "run CARLA scenarios", "use OpenSCENARIO", or has a scenario_runner that fails to import.

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 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。

Cooks and packages CarlaUE4 into distributable tarballs under Dist/ — either the full simulator or a standalone asset package of selected maps and props for later import. ROS2=1 keeps the native ROS 2 interface in the cooked package (a plain cook silently drops it). Use when the user asks to "package CARLA", "make a Dist build", "cook the project", "export a map as a package", "package CARLA with ROS2", or needs a build with working camera and lidar sensors.

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。

Writes a new Scenic scenario (.scenic) from a natural-language description — "a car cuts in from the right lane", "a pedestrian crosses in front of the ego", "negotiate an unsignalized four-way" — by turning the request into a spec, generating the file from idioms proven on this build, and validating it by compiling and sampling before any simulator is involved. Use when the user asks to "write a Scenic scenario", "create a .scenic file", "turn this description into Scenic", "generate a scenario from text", or wants a Scenic scenario authored or repaired.

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。

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。

Inspects and visualises a ROS-2-enabled CARLA server from Docker containers, with no local ROS 2 install — list/echo/rate-check topics (the "are the topics actually on the wire" check), run the bundled map-and-lidar demo stack (hero vehicle with camera/lidar/GNSS/IMU on autopilot), and open RViz2 with the lane-network preset. Use when the user asks to "check the ROS topics", "echo /carla/map", "is CARLA publishing to ROS", "visualise the lidar in RViz", "open rviz", or "run the ROS 2 demo".

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。

Write copy following Sentry brand guidelines. Use when writing UI text, error messages, empty states, onboarding flows, 404 pages, documentation, marketing copy, or any user-facing content. Covers both Plain Speech (default) and Sentry Voice tones.

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。

Turn a one-line objective into a step-by-step construction plan any coding agent can execute cold. Each step has a self-contained context brief — a fresh agent in a new session can pick up any step without reading prior steps.

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 "model agent mental states", "implement BDI architecture", "create belief-desire-intention models", "transform RDF to beliefs", "build cognitive agent", or mentions BDI ontology, mental state modeling, rational agency, or neuro-symbolic AI 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。

Validates animation durations, enforces typography scale, checks component accessibility, and prevents layout anti-patterns in Tailwind CSS projects. Use when building UI components, reviewing CSS utilities, styling React views, or enforcing design consistency.

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 before creative or constructive work (features, architecture, behavior). Transforms vague ideas into validated designs through disciplined reasoning and collaboration.

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。

Azure Blob Storage SDK for Python. Use for uploading, downloading, listing blobs, managing containers, and blob lifecycle.

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。

Azure Blob Storage JavaScript/TypeScript SDK (@azure/storage-blob) for blob operations. Use for uploading, downloading, listing, and managing blobs and containers.

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。

Azure Blob Storage SDK for Rust. Use for uploading, downloading, and managing blobs and containers.

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。