agentleFS
robium-airobium-ai/robium/skills/gazebo/SKILL.md

gazebo

Skill93 starsChanged 3 months agoMITView on GitHub

Build and debug modern Gazebo simulations and their ROS 2 boundary.

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

8 rules. About 0 are common, 6 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈6

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Treat a Gazebo simulation as a contract between world, robot, sensors, transport, and time.

    line 8
  2. Distinctive:

    When consuming an upstream simulator repository, select and pin an explicit branch or ref compatible with that ROS distro.

    line 20
  3. Very specific:

    Use modern Gazebo (gz). Gazebo Classic and libgazebo_ros_* tutorials are a different, end-of-life stack.

    line 23
  4. Distinctive:

    Keep upstream compatibility tables and SDF specifications as the authority for release-sensitive package names, tags, and plugin APIs.

    line 25
  5. Very specific:

    Bridge: prefer reviewable YAML for a static bridge set.

    line 36
  6. Distinctive:

    Do not infer simulation correctness from a running process or visible GUI.

    line 42
  7. Distinctive:

    Use the bundled SDF and bridge YAML together only as a starting pair.

    line 55
  8. Distinctive:

    Every required Gazebo topic has a matching, correctly directed ROS interface.

    line 66

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Gazebo

Treat a Gazebo simulation as a contract between world, robot, sensors, transport, and time. Find the first contract that is not producing believable evidence.

Start from the actual stack

  • For a new robotics app or first demo, read architect before creating worlds, launchers, or containers. Reuse its compatible reference-app selection if already made. Existing-world edits, simulator debugging, and explanations stay here.
  • Confirm the installed gz release, ROS distro, ros_gz pairing, render backend, and whether the run is graphical or headless.
  • When consuming an upstream simulator repository, select and pin an explicit branch or ref compatible with that ROS distro; default HEAD is not compatibility evidence.
  • Use modern Gazebo (gz). Gazebo Classic and libgazebo_ros_* tutorials are a different, end-of-life stack.
  • Keep upstream compatibility tables and SDF specifications as the authority for release-sensitive package names, tags, and plugin APIs.

Trace the simulation boundary

  • World: the selected world loads and the expected systems are present.
  • Robot: links, joints, frames, and drive plugins agree with the physical model and downstream interfaces.
  • Sensors: rates, fields of view, ranges, noise, frames, and timestamps model the intended hardware rather than tutorial defaults.
  • Transport: prove the Gazebo topic exists before debugging its ROS bridge.
  • Bridge: prefer reviewable YAML for a static bridge set. Use Python or XML launch-based parameter_bridge nodes when substitutions, grouping, or vendor conventions require them; reserve ad-hoc commands for diagnosis.
  • ROS: confirm /clock, commands, odometry, transforms, and sensor messages arrive with the expected direction and QoS.

Do not infer simulation correctness from a running process or visible GUI. A render-backed sensor may be silent even while physics continues.

Go deeper only when needed

  • For SDF worlds, models, drive plugins, spawning, and headless server mode, read worlds and models.
  • For lidar, camera, IMU, contact, noise, and rendering, read sensors.
  • For ros_gz_bridge, topic direction, types, QoS, /clock, and frame overrides, read the ROS 2 bridge guide.
  • For a silent world, sensor, bridge, or remote launch, read failures.
  • Use the bundled SDF and bridge YAML together only as a starting pair; keep their topic and frame names synchronized and verify syntax upstream.

Move to navigation only after the robot pose, sensor, map, and velocity interfaces are valid. Move to ros2 when Gazebo is publishing correctly and the fault is in the ROS graph. Use environments for container GPU/display setup and simulation only when the simulator itself has not been chosen.

Done

  • Physics time advances and the expected world and model are present.
  • Every required Gazebo topic has a matching, correctly directed ROS interface.
  • Sensor rate, frame, timestamp, and render output are believable.
  • The run works in its intended graphical or headless environment.
  • Release-specific claims match current Gazebo and ros_gz documentation.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.