Coding standards, frameworks, refactoring, and code review (16.7K skills)
List static objects built into a CARLA map and hide or restore them by category or asset name. Adjust buildings, vegetation, fences, and other scenery, preview affected objects, and change both their visibility and collision behavior.
Check whether a CARLA feature is usable in the current environment and has a verified procedure. Review known failures, inspect build settings, and identify differences between client, server, and source versions before planning work.
Builds CARLA's ue4-dev branch on Linux, producing the Unreal Engine 4.26 editor, server modules, and an installed Python client package. Fetches required content, optionally compiles native ROS 2 support, and verifies the build against a source-built server.
Import a four-wheel FBX vehicle into a CARLA source build, configure its physics, wheels, and animation, and register it for the Python API. Verify that the resulting vehicle can spawn, drive, and steer.
Import RoadRunner geometry and road data into a CARLA source build, then verify the map loads and supports driving. Handle tiled maps and generate and inspect pedestrian navigation areas for standard maps.
Draws points, lines, arrows, boxes, and text over a running CARLA world to visually check positions, paths, and objects. Sets colors and display lifetimes for temporary debugging overlays, without creating persistent actors or output files.
Places cameras, lidar, and other sensors in a running CARLA world, attached to vehicles or fixed in place. Configures mounting positions and sensor attributes, enables supported ROS 2 data publishing, and reports sensor IDs for later data reading.
Adjust how autopilot vehicles behave in CARLA, including speed, following distance, traffic light responses, and lane changes. Apply settings across traffic or to individual vehicles, and configure seeds and synchronization for repeatable traffic runs.
Install Scenic, a language for describing scenarios with randomized conditions, into the Python environment used by CARLA. Check command-line tools and version compatibility, optionally download example scenarios and map assets, and save the installation paths.
Install the CARLA Python client into a chosen Python environment using bundled packages or PyPI. The skill checks existing installations, selects a suitable package, and verifies imports and version compatibility with a reachable simulator.
Import an FBX character into a CARLA source build as a pedestrian available through the Python API. Check its GEN3 skeleton, create assets and a walker blueprint, register it, and verify spawning, ground placement, and movement.
Drives a CARLA vehicle to a specific destination using navigation agents that plan routes, avoid obstacles, and obey traffic lights. Can also plan and draw a route between two points without moving the vehicle.
Extend CARLA’s native ROS 2 interface to publish sensor data or receive vehicle commands. Covers topic implementation, registration, data connections, and verification, plus adding middleware, the communication layer used to exchange messages.
Add a message type to CARLA's native ROS 2 interface. Create its C++ data structure, serialization code for transmission, type identity hash, registration, and tests, with Docker-based hash calculation and build checks.
Read and change a running CARLA server’s timing, physics substeps, and rendering settings. Switch between client-controlled steps and automatic progression, keep Traffic Manager synchronization aligned, and read back the settings to verify each change.
Organize React and TypeScript frontend code using consistent rules for feature folders, shared components, types, API access, and tests. Use it to guide new code, focused refactoring, and reviews of existing changes.
Structure TypeScript backend features with clear module boundaries, shared definitions, and focused tests. It guides implementation and reviews while keeping request handling in routes and business logic in services.
Extend and audit TVM's T.ptx instruction table for GPU code generation. It guides instruction definitions, checks generated assembly with CUDA tools, and aligns comments and supported forms with a chosen PTX specification version.
Launch and troubleshoot the actual AO desktop app to inspect interface changes with local data. Supports reviewing combined pull request branches and diagnosing lingering Electron processes, port conflicts, and mismatches in the app’s preload bridge.
Calculates added and deleted lines for a pull request and maintains a three-line summary for implementation, tests, and other files. Preserves existing description text and checks the published counts against the current diff.
Coordinate AO Cloud work sessions through the ao command line. Create and monitor workers, exchange messages, attach pull requests, start reviews, and operate the visible browser using the commands available to each session’s role.
Build, test, and format CubeSandbox components using make targets and a Docker builder. Also covers the web dashboard’s development workflow, API type synchronization, and troubleshooting for missing services, outdated build tools, and environment requirements.
Set up portless to give local development servers stable, named URLs instead of changing port numbers. It covers multiple apps, separate Git worktree URLs, HTTPS setup, and checks for proxy, domain resolution, and certificate problems.
Configure OAuth, the authorization flow used for provider sign-in, with portless development URLs. It guides callback registration and authentication library settings, helping diagnose rejected domains, redirect URL mismatches, and callbacks that point to the wrong address.