'server' 검색 결과

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".

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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.

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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".

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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.

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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.

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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.

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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.

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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".

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Controls the traffic-light actors on a running CARLA server — set a light green/red/yellow/off, freeze all lights (optionally all-green), set phase timing (green/yellow/red durations), and reset to the normal cycle. Target all lights, one by id, all in a junction, or the nearest. Use when the user asks to "make the light red", "freeze all lights green", "change the light timing", "turn the traffic lights off", or "reset the lights". This is the light actors, not the Traffic Manager (that's control-traffic).

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Windows アプリ開発 (Windows App SDK / WinRT) のファイル・設定・データ保存リファレンス。 Windows.Storage の StorageFile, StorageFolder, IStorageItem, FileIO, PathIO, CachedFileManager, DataReader, DataWriter, BasicProperties。ApplicationData, ApplicationDataContainer, ApplicationDataCompositeValue のローカル・ローミング設定。 FileOpenPicker, FileSavePicker, FolderPicker, KnownFolders, StorageApplicationPermissions (FutureAccessList / MostRecentlyUsedList)。 JsonObject, JsonArray, XmlDocument, SQLite, EF Core, Microsoft.Data.SqlClient (SQL Server), Cosmos DB, MySQL, MongoDB 接続。

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OpenAI Codex (CLI / IDE / cloud / ChatGPT desktop app) リファレンス。 GPT-6 系, Fast / Ultrafast mode, codex exec, スラッシュコマンド, prompting, AGENTS.md, rules, subagents, approvals, auto-review, sandbox, permission profiles, profiles, config.toml, 環境変数, roles, MCP 設定, GitHub Action, Codex SDK, App Server (JSON-RPC), Agents SDK 連携, Codex skills (.agents/skills), plugins, scheduled tasks, Browser, Computer Use, cloud / local / worktree 環境, git worktrees, Record & Replay, cloud 委譲, GitHub / GitLab / Linear / Slack 連携, administration, provisioning, analytics API, compliance API, LLM gateway, Codex Security 脆弱性スキャン (SARIF), deep scan, triage, findings, threat model, security hardening。

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OpenAI API (developers.openai.com) の Responses API リファレンス。 text generation, embeddings, gpt-6-astra / gpt-6.1-sol / gpt-6-luna, structured outputs, streaming, function calling, programmatic / async tool calling, conversation state, prompt caching, prompt cache diagnostics, reasoning (configuration_update), background mode, compaction, multi-agent, WebSocket mode (mid-turn steering, stream_id), webhooks, error codes, rate limits, Realtime server controls, 公式 SDK (Python / JS / .NET / Java / Go / Ruby), openai CLI, Chat Completions / Assistants 移行, deprecations。

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Storybook (UI カタログ) リファレンス。story, CSF (Component Story Format), CSF Next (CSF Factories), args, argTypes, decorators, play function, interaction tests, autodocs, main.ts / preview.ts, アドオン (a11y, controls, viewport, themes), Vitest addon, test-runner, Storybook MCP server, components manifest, アドオン作成, upgrade / migration。

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Figma REST API / Plugin API / Widget API / Code Connect / MCP Server / Dev Mode リファレンス OAuth / PAT / Plan Access Token, files, folders, variables, VariableComposedColor, webhooks, SCIM, Dev Resources, activity-logs, library-analytics FrameNode, TextNode, ComponentNode, figma.variables, figma.codegen, figma.ui, textWrapStyle, variable fonts Widget useSyncedState, useSyncedMap, usePropertyMenu, AutoLayout Code Connect template files (.figma.ts) / legacy parser / custom parsers / register / Storybook (React / SwiftUI / Compose / HTML) MCP Code to Canvas, Write to Canvas, html_to_figma, generate_image, get_motion_context, generative plugins / shaders, Figma Weave

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OpenAI API (developers.openai.com) の音声 API リファレンス。 GPT-Live (gpt-live-1, full-duplex, delegation, /v1/live/sessions), Realtime API (WebRTC / WARP / WebSocket / SIP, sessions / events, client secrets, VAD (server_vad / semantic_vad), tools/MCP), speech-to-speech voice agents, speech-to-text (gpt-transcribe / gpt-live-transcribe), text-to-speech, custom voices, translation。

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Inngest イベント駆動 Durable Execution リファレンス。バックグラウンドジョブ、長時間ワークフロー。 createFunction, step.run, step.sleep, step.waitForEvent, step.waitForSignal, step.invoke, step.sendEvent, step.sleepUntil, step.fetch, step.ai.infer, step.ai.wrap, step.metadata, inngest.send, serve, connect, checkpointing, Inngest CLI。 concurrency, throttle, debounce, rate-limit, batching, priority, idempotency, singleton, multi-tenancy フロー制御。 Realtime（channels, topics, publish, subscribe, subscription tokens, useRealtime）、 Agent Evals（scoring, group.experiment）、MCP（Dev Server / Cloud）。 デプロイ先 Next.js, Express, Hono, Cloudflare Workers, Vercel, Netlify, DigitalOcean, Render。

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Rust 製フロントエンドフレームワーク fandhe-frontend のリファレンス。 SSR / SPA / SSG / View Transitions、hydration、Document builder(SSR 組み込み)、CSP meta、単一実行ファイル配布、Vercel、既定エスケープ。 クレート core / app / interactive / server(generate_pages) / headless-ui(Primitives, AutocompleteToken, passkey) / pre-styled-ui(Themes, motion) / wireframe-ui(Wireframes) / animation(data-* 属性) / wasm-full。 Blocks(Hero / Pricing / Cart 等セクション例 335 件)。CLI fw。

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React Hook Form v7 (RHF、非制御フォームライブラリ) リファレンス。別名 rhf / React-Hook-Form。 useForm, register, handleSubmit, watch, setValue, getValues, getErrors, reset、 Controller, useFieldArray / FieldArray, formState / FormState, ErrorMessage、 resolver (Zod / Yup / Joi)、バリデーション、Server Actions / useActionState、 DevTools (@hookform/devtools)、TypeScript 型。

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Drizzle ORM (TypeScript ORM, drizzle-orm / drizzle-kit) の API リファレンス。 pgTable / mysqlTable / sqliteTable, `drizzle()`, `$inferSelect` / `$inferInsert`, RQB (Relational Queries) / `db.query`, `defineRelations`, magic `sql` operator, `drizzle-kit generate` / `push`, `drizzle.config.ts`, drizzle-zod, drizzle-seed, Drizzle Studio。SQL Server の低レベルドライバーは別スキル mssql。

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Claude Agent SDK (code.claude.com/docs/en/agent-sdk) の TypeScript / Python リファレンス。 query(), ClaudeAgentOptions / Options, fallbackModel, maxTurns, maxBudgetUsd, custom tools (in-process MCP), createSdkMcpServer, hooks, permissions (canUseTool), subagents, sessions (resume / fork), streaming, structured outputs, Agent Skills (SKILL.md), slash commands (/compact, /clear), tool search, hosting / observability。

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Claude Code (code.claude.com) デプロイ・CI/CD リファレンス。 Amazon Bedrock / Google Cloud Agent Platform (Vertex AI) / Microsoft Foundry / Claude Platform on AWS、 Claude apps gateway、LLM gateway (protocol / rollout)、 GitHub Actions (claude-code-action) / GitLab CI/CD / GitHub Enterprise Server (GHES)、 Code Review (REVIEW.md・review level・@claude review always・コスト・トラブルシュート)、 ローカル /code-review、ultrareview (claude ultrareview)、 Slack (Claude Tag、旧 Claude Code in Slack、Pro/Max)、 headless mode、cloud environments、devcontainer、 self-hosted environments（runner 構成・identity 検証・本番デプロイ）。

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Apple データ永続化・データフロー・ネットワーク・ユーティリティリファレンス。SwiftData / Core Data / Foundation / Combine。 @Model, ModelContainer, ModelContext, @Query, Predicate, FetchDescriptor, SectionedResults, ResultsObserver, NSManagedObject, NSFetchRequest, NSFetchedResultsController, NSPersistentContainer, NSPersistentCloudKitContainer, NSStagedMigrationManager, URLSession, JSONDecoder, JSONEncoder, Publisher, sink, Future, AsyncPublisher, @Published, AnyCancellable

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Blender Python API リファレンス。bpy / bmesh / mathutils / gpu / bpy_extras モジュール、 bpy.data / bpy.context / bpy.ops / bpy.types / bpy.props / bpy.msgbus / bpy.path コア API。 Mesh / Modifier / Geometry Nodes / Armature / Keyframe / Driver / Shape Key / NLA、 Cycles / EEVEE / Shader Nodes / Rigid Body / Cloth / Fluid / Compositor Nodes / AOV、 headless CLI レンダリング、add-on 開発、Extensions システム、MCP Server (Model Context Protocol)。

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Generate Skills from HTTP MCP servers with async job patterns (submit/status/result). Use when converting MCP specifications (.mcp.json) into reusable Skills using mcp_tool_catalog.yaml. Supports --lazy mode for context-saving generation. Also use for calling async MCP tools via JSON-RPC 2.0 with session-based polling.

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