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概要と使いどころ
After making code changes, start the dev server, open the app in Cursor's built-in browser, and verify everything works — check rendering, console errors, and network health. Use proactively after any UI or API change.
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 PostHog error tracking suppression rules to drop high-volume, low-value errors at ingestion. Use when the user asks "stop capturing this error", "drop browser extension errors", "ignore ResizeObserver loops", "suppress bot-driven errors", or wants to reduce ingestion cost from noisy unactionable errors. Identifies suppression candidates, scopes the filter tightly, decides between full suppression and sampling, and confirms the rule before creating it. Suppressed errors are dropped permanently — this skill defaults to caution.
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。
Check out two branches in separate worktrees, start both dev servers on different ports, screenshot the same pages, and produce a visual diff.
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。
Start the dev server, discover API routes from the codebase, hit every endpoint, and report which ones return errors.
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 AI scientist systems with the ToolUniverse Python SDK for scientific research. Covers the 3 calling patterns (`tu.run` portable dict API, `tu.tools.X` function API, direct class instantiation), tool loading, batch execution, MCP server integration, and embedding-based tool search. Use for SDK programming, custom tool composition, benchmarking pipelines, and integrating ToolUniverse into research workflows.
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。
Analyze Chronote product adoption with PostHog and Langfuse, including active users, meetings, feature usage, AI telemetry, and privacy-safe resolution of active Discord guild IDs to live server names.
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。
Stellar standards, ecosystem, and reference. Covers SEPs (Stellar Ecosystem Proposals), CAPs (Core Advancement Proposals), and a quick map for picking the right standard for wallets, anchors, payments, deposits/withdrawals, federation, deep links, and KYC. Also bundles ecosystem references (DeFi protocols, dev tools, wallets, infra, community projects), curated documentation links, and MCP servers (live tools such as Raven). Use when you need to know which SEP applies, or want a starting point for ecosystem integrations, official docs, or live MCP tooling.
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。
VenTu is a static export on GitHub Pages — no Node runtime at request time. Use when adding routes, auth, alerts, forms, API endpoints, or anything that could depend on a 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。
Implement BUI contracts, server validation, localized client windows, lifecycle cleanup, and state refresh.
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。
Change persistent models and SQLite/PostgreSQL migrations without breaking existing servers.
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。
Place contracts and behavior across authority, prediction, presentation, localization, and assembly boundaries.
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。
Validate UI, command, text, numeric, entity, and configuration input with localized feedback and server authority.
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。
Keep responsive shared interactions deterministic and free of duplicated side effects while server authority wins.
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。
Implement EUI sessions, shared state and messages, server lifecycle, and client presentation.
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。
Implement server APIs, authentication, and application data access. Schema modeling and query tuning use oma-db.
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 CARLA on UE 5.8 as spawnable props — drives the editor headlessly to import the mesh, derives the prop size from its measured bounds, and registers it in PropParameters.json so it appears in the blueprint library as static.prop.<name>. Handles the FBX unit-scale problem, verifies the result against a running server, and can revert cleanly. Use when the user asks to "import a prop", "add a custom mesh/object to CARLA", "make my model spawnable", or a prop imports but never shows up in the blueprint library.
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。
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 changes a running CARLA server's WorldSettings via apply_settings — synchronous vs asynchronous mode, fixed_delta_seconds (fps), physics substepping, and no_rendering_mode — and keeps the Traffic Manager's sync state matched automatically. Use when the user asks to "enable/disable sync mode", "set synchronous mode", "run at a fixed fps/step", "turn off rendering", "make the sim deterministic", or "restore async mode", and as the prerequisite for keeping settings across a map load.
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。
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。
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。
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).
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。