「agent」の検索結果

Adds a new topic to CARLA's native ROS 2 interface — a publisher (BasePublisher + PublisherImpl, topic suffix, QoS, registration in ROS2::GetOrCreateSensor, a ProcessDataFrom* entry point and its call site in the UE4 plugin) or a subscriber that lets ROS drive an actor. Also covers adding a middleware (RMW) behind IPublisherMiddleware. Use when the user asks to "publish X to ROS from CARLA", "add a ROS topic/publisher/subscriber", "make the obstacle/lane-invasion sensor publish", "add odometry to ROS", or "add another RMW".

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。

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。

Answers "can CARLA do X here, and is there a vetted procedure for it" before you promise anything, and detects client/server/tree version skew — a support matrix over the whole collection (covered by a skill / works but undocumented / present but untested / broken or removed), an index of the features that are verified BROKEN on 0.10.0 (gbuffers crash the server, map layers do nothing, Landmark.waypoint is None, standalone asset packages are gone), and a probe that reports what this machine's build flags and running server actually offer. Use when the user asks whether CARLA supports something, when a feature has no skill, when a UE4 tutorial's steps do not exist, or before improvising a procedure.

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。

Reads and sets the weather on a running CARLA server via get_weather/set_weather, and turns natural-language weather requests ("heavy rain at sunset", "light fog at night", "clear noon", "dust storm") into exact WeatherParameters — cloudiness, precipitation, puddles, wind, fog, sun position, wetness, dust. Use when the user asks to "set/change the weather", "make it rainy/foggy/sunny/night", "apply a weather preset", or describes any sky/lighting condition.

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 and summarises ScenarioRunner output — the criteria pass/fail tables from --output/--file, the machine-readable --json and --junit result files, and the criteria JSON written alongside a --record recording — and runs the metrics module (metrics_manager.py) to compute custom measurements over a recorded run offline, without the simulator. Use when the user asks "did the scenario pass", "why did it fail", "summarise these results", "compare these runs", or wants distance/speed/lane metrics from a recording.

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。

Loads, reloads, and reshapes the map on a running CARLA server via the Python API — get_available_maps, load_world and reload_world (with or without resetting world settings), generate a world from an OpenDRIVE .xodr, and load/unload map layers. Use when the user asks to "load a map", "change the town", "reload the world", "list available maps", "load an xodr/opendrive map", or "load/unload map layers", and when settings (sync mode, fixed delta) must survive the switch.

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。

Creates and edits CARLA Leaderboard route files — placing waypoints and scenario trigger points interactively from the spectator camera (route_creator, scenario_creator), visualising an existing route in the simulator (route_displayer), summarising it as a table (route_summarizer), capturing the current weather in route format (weather_creator), sorting scenarios by route position (scenario_orderer) and converting 1.0-format routes to 2.x (route_bridge). Use when the user asks to "make a new route", "add a scenario to a route", "visualise/debug a route", "see what's in this route file", or "convert old leaderboard routes".

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。

Create a pull request from the current branch with structured summary

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。

QA + bugfix cycle until it passes

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。

Full pipeline: evaluation -> spec -> implementation -> review -> QA

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。

Discipline skill — TDD red-green-refactor cycle. Use when implementing any feature or bugfix, before writing implementation code.

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。

Discipline skill — systematic debugging process. Use when encountering any bug, debug issue, test failure, broken function, or unexpected behavior, before proposing fixes.

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, review, or audit this repository's technical documentation, including README.md, CONTRIBUTING.md, root and scoped AGENTS.md files, docs pages, and documentation drift. Use for source-backed documentation authoring, behavior verification, and cross-surface consistency. Do not use for code review, deslop diff cleanup, or whole-page rewrites, splits, or reorganizations handled by docs-refactor.

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。

Conventional Commits 形式で GitHub PR を作成する。OWASP Top 10 のセキュリティチェック必須で、問題があれば PR 作成を中止。Summary/Test plan/Design を含む body を生成。「PR 作って」「プルリク」「`gh pr create`」などで使用。別リポジトリ (upstream) への貢献は contribute-skill。

Conventional Commits 形式で git コミットを作成する。staged 差分から type/scope を推定し、breaking change やシークレット混入 (.env 等) を検出。pre-commit フックを必ず通す (`--no-verify` 不可)。「コミットして」「git commit」「変更を記録して」などで使用。

既存の GitHub Issue ツリーを棚卸し・更新するスキル。「ツリーを棚卸しして」「イシューツリーを更新して」「トラッキング issue を整理して」で使用。 ルートのトラッキング issue 番号を受け取り、sub_issues API でツリー全体を再帰取得 → closed 親下の残置 open issue 付け替え・孤児の再配置・新 Phase 親の新設・phase ラベル同期 → ルート issue 本文は既存本文を保持し、Phase 別表・棚卸し履歴の管理ブロックのみ更新する。 ツリー新規作成は create-issue-tree、実装消化は implement-issue-tree を参照。

GitHub Project v2 を新規作成し、Status/Priority/Size の標準フィールドを設定してリポジトリにリンクする。Auto-add/Auto-archive/Auto-close 等のビルトインワークフロー設定 URL もガイド (CLI 不可・Web UI のみ)。「プロジェクト作って」「Project v2 セットアップ」「カンバン作成」などで使用。

Phase 分割された GitHub Issue ツリーを新規作成するスキル。「イシューツリー作って」「タスクを Phase 別に Issue 化」「Issue ツリーを起票して」で使用。 要件・タスク一覧を受け取り、タスク分解（既定 2h 粒度・--granularity で変更可）→ Phase 分割 → ルート（トラッキング）issue → Phase 親 issue → 子 issue の階層を sub_issues API で紐付け。 phase ラベル付与・ルート issue 本文の Phase 別表生成まで自動化。任意の phase 指定で部分起票にも対応。 ツリーの棚卸し・更新は update-issue-tree、実装消化は implement-issue-tree を参照。

Theatre.js アニメーションツールキットリファレンス。 @theatre/core / @theatre/studio / @theatre/r3f / @theatre/dataverse。 getProject, Sheet, Sequence, Object, val, onChange, prop-types（number / rgba / compound / image）。 studio initialize / extend / transaction / scrub / createPane。 SheetProvider, editable, useCurrentSheet, useVal, usePrism, useAtom。 keyframe アニメーション、audio sync、state JSON、React Three Fiber 統合。