Best practices, design patterns, and common pitfalls for ROS1 (Robot Operating System 1) development.

Apache-2.0Auto-check passedDevelopment

Install Ros1

skills CLI
$ npx skills add arpitg1304/robotics-agent-skills --skill ros1 -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install arpitg1304/robotics-agent-skills ros1 --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/arpitg1304/robotics-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ros1 .claude/skills/ros1 && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ros1
GitHub stars
369
Token cost
~3.3k tokens
SKILL.md length
256 words
Files
1
Skills in repo
10
Repo updated
First seen
Licence
Apache-2.0

At a glance

Best practices, design patterns, and common pitfalls for ROS1 (Robot Operating System 1) development.

  • Works in 5 steps: Node Design → Topic Design → Launch File Best Practices → …
  • Building ROS1 nodes
  • SKILL.md covers When to Use This Skill, Core Architecture Principles, Common Pitfalls & Failure Modes and Nodelets for Zero-Copy Transport, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Ros1 is an agent skill from arpitg1304/robotics-agent-skills. Best practices, design patterns, and common pitfalls for ROS1 (Robot Operating System 1) development. Use this skill when building ROS1 nodes, packages, launch files, or debugging ROS1 systems. Trigger whenever the user mentions ROS1, catkin, rospy, roscpp, roslaunch, roscore, rostopic, tf, actionlib, message types, services, or any ROS1-era robotics middleware. Also trigger for migrating ROS1 code to ROS2, maintaining legacy ROS1 systems, or building ROS1-ROS2 bridges. Covers catkin workspaces, nodelets, dynamic…

Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Design patterns. The repository describes itself as: Agent skills that make AI coding assistants write production-grade robotics software. ROS1, ROS2, design patterns, SOLID principles, and testing — for Claude Code, Cursor… The licence is Apache-2.0.

When your agent uses it

  • Building ROS1 nodes
  • Debugging ROS1 systems
  • Ever the user mentions ROS1
  • Any ROS1-era robotics middleware

Example prompts

  • “/ros1”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Node Design
  2. Topic Design
  3. Launch File Best Practices
  4. TF Transform Tree
  5. Actionlib for Long-Running Tasks

What it can do on your machine

Read from SKILL.md and the folder at commit f9bc546. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python, xml, cpp and bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Ros1 loads about 3.3k tokens when it runs. Until then it costs about 144 tokens; SKILL.md has 256 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~144
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from arpitg1304/robotics-agent-skills at commit f9bc546, republished under its Apache-2.0 licence (© arpitg1304). 256 words, ~3,330 tokens.

Download SKILL.mdSave it as .claude/skills/ros1/SKILL.md (or your agent's skills folder).
name
ros1
description
Best practices, design patterns, and common pitfalls for ROS1 (Robot Operating System 1) development. Use this skill when building ROS1 nodes, packages, launch files, or debugging ROS1 systems. Trigger whenever the user mentions ROS1, catkin, rospy, roscpp, roslaunch, roscore, rostopic, tf, actionlib, message types, services, or any ROS1-era robotics middleware. Also trigger for migrating ROS1 code to ROS2, maintaining legacy ROS1 systems, or building ROS1-ROS2 bridges. Covers catkin workspaces, nodelets, dynamic reconfigure, pluginlib, and the full ROS1 ecosystem.

ROS1 Development Skill

When to Use This Skill

  • Building or maintaining ROS1 packages and nodes
  • Writing launch files, message types, or services
  • Debugging ROS1 communication (topics, services, actions)
  • Configuring catkin workspaces and build systems
  • Working with tf/tf2 transforms, URDF, or robot models
  • Using actionlib for long-running tasks
  • Optimizing nodelets for zero-copy transport
  • Planning ROS1 → ROS2 migration

Core Architecture Principles

1. Node Design

Single Responsibility Nodes: Each node should do ONE thing well. Resist the temptation to build monolithic "do-everything" nodes.

python
# BAD: Monolithic node
class RobotNode:
    def __init__(self):
        self.sub_camera = rospy.Subscriber('/camera/image', Image, self.camera_cb)
        self.sub_lidar = rospy.Subscriber('/lidar/points', PointCloud2, self.lidar_cb)
        self.pub_cmd = rospy.Publisher('/cmd_vel', Twist, queue_size=10)
        self.pub_map = rospy.Publisher('/map', OccupancyGrid, queue_size=1)
        # This node does perception, planning, AND control

# GOOD: Decomposed nodes
class PerceptionNode:    # Fuses sensor data → publishes /obstacles
class PlannerNode:       # Subscribes /obstacles → publishes /path
class ControllerNode:    # Subscribes /path → publishes /cmd_vel

Node Initialization Pattern:

python
#!/usr/bin/env python
import rospy
from std_msgs.msg import String

class MyNode:
    def __init__(self):
        rospy.init_node('my_node', anonymous=False)

        # 1. Load parameters FIRST
        self.rate = rospy.get_param('~rate', 10.0)
        self.frame_id = rospy.get_param('~frame_id', 'base_link')

        # 2. Set up publishers BEFORE subscribers
        #    (prevents callbacks firing before publisher is ready)
        self.pub = rospy.Publisher('~output', String, queue_size=10)

        # 3. Set up subscribers LAST
        self.sub = rospy.Subscriber('~input', String, self.callback)

        rospy.loginfo(f"[{rospy.get_name()}] Initialized with rate={self.rate}")

    def callback(self, msg):
        # Process and republish
        result = String(data=msg.data.upper())
        self.pub.publish(result)

    def run(self):
        rate = rospy.Rate(self.rate)
        while not rospy.is_shutdown():
            # Periodic work here
            rate.sleep()

if __name__ == '__main__':
    try:
        node = MyNode()
        node.run()
    except rospy.ROSInterruptException:
        pass
2. Topic Design

Naming Conventions:

/robot_name/sensor_type/data_type

# Examples:
/ur5/joint_states              # Robot joint states
/realsense/color/image_raw     # Camera color image
/realsense/depth/points        # Depth point cloud
/mobile_base/cmd_vel           # Velocity commands
/gripper/command               # Gripper commands

Queue Sizes Matter:

python
# For sensor data (high frequency, OK to drop old messages):
rospy.Subscriber('/camera/image', Image, self.cb, queue_size=1)

# For commands (don't want to miss any):
rospy.Publisher('/cmd_vel', Twist, queue_size=10)

# For large data (point clouds, images) - use small queues to prevent memory bloat:
rospy.Subscriber('/lidar/points', PointCloud2, self.cb, queue_size=1)

# NEVER use queue_size=0 (infinite) for high-frequency topics
# This WILL cause memory leaks under load

Latched Topics for data that changes infrequently:

python
# Robot description, static maps, calibration data
pub = rospy.Publisher('/robot_description', String, queue_size=1, latch=True)
3. Launch File Best Practices
xml
<launch>
  <!-- ALWAYS use args for configurability -->
  <arg name="robot_name" default="ur5"/>
  <arg name="sim" default="false"/>
  <arg name="debug" default="false"/>

  <!-- Group by subsystem with namespaces -->
  <group ns="$(arg robot_name)">

    <!-- Conditional loading based on sim vs real -->
    <group if="$(arg sim)">
      <include file="$(find my_pkg)/launch/sim_drivers.launch"/>
    </group>
    <group unless="$(arg sim)">
      <include file="$(find my_pkg)/launch/real_drivers.launch"/>
    </group>

    <!-- Node with proper remapping -->
    <node pkg="my_pkg" type="perception_node.py" name="perception"
          output="screen" respawn="true" respawn_delay="5">
      <param name="rate" value="30.0"/>
      <param name="frame_id" value="$(arg robot_name)_base_link"/>
      <remap from="~input_image" to="/$(arg robot_name)/camera/image_raw"/>
      <remap from="~output_detections" to="detections"/>
      <!-- Load a YAML param file -->
      <rosparam file="$(find my_pkg)/config/perception.yaml" command="load"/>
    </node>

  </group>

  <!-- Debug tools (conditionally loaded) -->
  <group if="$(arg debug)">
    <node pkg="rviz" type="rviz" name="rviz"
          args="-d $(find my_pkg)/rviz/debug.rviz"/>
    <node pkg="rqt_graph" type="rqt_graph" name="rqt_graph"/>
  </group>
</launch>
4. TF Transform Tree

Rules:

  • Every frame has EXACTLY one parent (tree, not graph)
  • Static transforms use static_transform_publisher
  • Dynamic transforms publish at consistent rates
  • ALWAYS set timestamps correctly
python
import tf2_ros

# Publishing transforms
br = tf2_ros.TransformBroadcaster()
t = TransformStamped()
t.header.stamp = rospy.Time.now()  # CRITICAL: Use current time
t.header.frame_id = "odom"
t.child_frame_id = "base_link"
t.transform.translation.x = x
t.transform.translation.y = y
t.transform.rotation = quaternion_from_euler(0, 0, theta)
br.sendTransform(t)

# Listening for transforms (with timeout and exception handling)
tf_buffer = tf2_ros.Buffer()
listener = tf2_ros.TransformListener(tf_buffer)

try:
    trans = tf_buffer.lookup_transform(
        'map', 'base_link',
        rospy.Time(0),          # Get latest available
        rospy.Duration(1.0)     # Wait up to 1 second
    )
except (tf2_ros.LookupException,
        tf2_ros.ConnectivityException,
        tf2_ros.ExtrapolationException) as e:
    rospy.logwarn(f"TF lookup failed: {e}")
5. Actionlib for Long-Running Tasks
python
import actionlib
from my_msgs.msg import PickPlaceAction, PickPlaceGoal, PickPlaceResult

# Server
class PickPlaceServer:
    def __init__(self):
        self.server = actionlib.SimpleActionServer(
            'pick_place',
            PickPlaceAction,
            execute_cb=self.execute,
            auto_start=False  # ALWAYS set auto_start=False
        )
        self.server.start()

    def execute(self, goal):
        feedback = PickPlaceFeedback()

        # Check for preemption INSIDE your loop
        for step in self.plan_steps(goal):
            if self.server.is_preempt_requested():
                self.server.set_preempted()
                return
            self.execute_step(step)
            feedback.progress = step.progress
            self.server.publish_feedback(feedback)

        result = PickPlaceResult(success=True)
        self.server.set_succeeded(result)

Common Pitfalls & Failure Modes

Time Synchronization
python
# BAD: Comparing timestamps from different clocks
if camera_msg.header.stamp == lidar_msg.header.stamp:  # Almost never true

# GOOD: Use message_filters for approximate time sync
import message_filters
sub_cam = message_filters.Subscriber('/camera/image', Image)
sub_lidar = message_filters.Subscriber('/lidar/points', PointCloud2)
sync = message_filters.ApproximateTimeSynchronizer(
    [sub_cam, sub_lidar], queue_size=10, slop=0.05  # 50ms tolerance
)
sync.registerCallback(self.synced_callback)
Callback Threading
python
# ROS1 uses a single-threaded spinner by default.
# Long-running callbacks BLOCK all other callbacks.

# BAD:
def callback(self, msg):
    result = self.expensive_computation(msg)  # Blocks for 2 seconds!
    self.pub.publish(result)

# GOOD: Use a MultiThreadedSpinner or process in a separate thread
rospy.init_node('my_node')
# ... setup ...
spinner = rospy.MultiThreadedSpinner(num_threads=4)
spinner.spin()

# Or use a processing thread:
import threading, queue
class MyNode:
    def __init__(self):
        self.work_queue = queue.Queue(maxsize=1)
        self.worker = threading.Thread(target=self._process_loop, daemon=True)
        self.worker.start()

    def callback(self, msg):
        try:
            self.work_queue.put_nowait(msg)  # Non-blocking
        except queue.Full:
            pass  # Drop old data

    def _process_loop(self):
        while not rospy.is_shutdown():
            msg = self.work_queue.get()
            result = self.expensive_computation(msg)
            self.pub.publish(result)
Parameter Server Anti-Patterns
python
# BAD: Hardcoded values
self.threshold = 0.5

# BAD: Global params without namespace
self.threshold = rospy.get_param('threshold', 0.5)  # Collides across nodes

# GOOD: Private params with defaults
self.threshold = rospy.get_param('~threshold', 0.5)

# GOOD: Dynamic reconfigure for runtime tuning
from dynamic_reconfigure.server import Server
from my_pkg.cfg import MyNodeConfig
self.dyn_server = Server(MyNodeConfig, self.dyn_callback)

Nodelets for Zero-Copy Transport

When nodes exchange large data (images, point clouds) within the same process, nodelets eliminate serialization overhead:

cpp
// my_nodelet.h
#include <nodelet/nodelet.h>
#include <pluginlib/class_list_macros.h>

class MyNodelet : public nodelet::Nodelet {
  virtual void onInit() {
    ros::NodeHandle& nh = getNodeHandle();
    ros::NodeHandle& pnh = getPrivateNodeHandle();
    // Use shared_ptr for zero-copy: pass pointers, not copies
    pub_ = nh.advertise<sensor_msgs::Image>("output", 1);
    sub_ = nh.subscribe("input", 1, &MyNodelet::callback, this);
  }
};
PLUGINLIB_EXPORT_CLASS(MyNodelet, nodelet::Nodelet)

Package Structure

my_robot_pkg/
├── CMakeLists.txt
├── package.xml
├── setup.py                    # For Python packages
├── config/
│   ├── robot_params.yaml       # Default parameters
│   └── dynamic_reconfigure/    # .cfg files
├── launch/
│   ├── robot.launch            # Top-level launcher
│   ├── drivers.launch          # Hardware drivers
│   └── perception.launch       # Perception pipeline
├── msg/                        # Custom message definitions
│   └── Detection.msg
├── srv/                        # Service definitions
│   └── GetPose.srv
├── action/                     # Action definitions
│   └── PickPlace.action
├── src/                        # C++ source
│   └── my_node.cpp
├── scripts/                    # Python nodes (executable)
│   └── perception_node.py
├── include/my_robot_pkg/       # C++ headers
│   └── my_node.h
├── rviz/                       # RViz configs
│   └── debug.rviz
├── urdf/                       # Robot model
│   └── robot.urdf.xacro
└── test/                       # Unit and integration tests
    ├── test_perception.py
    └── test_perception.test    # rostest launch file

Debugging Toolkit

bash
# Essential diagnostic commands
rostopic list                     # See all active topics
rostopic hz /camera/image_raw     # Check publish rate
rostopic bw /lidar/points         # Check bandwidth
rostopic echo /joint_states -n 1  # Inspect one message

rosnode list                      # Active nodes
rosnode info /perception          # Connections and subscriptions

roswtf                            # Automated diagnostics

rqt_graph                         # Visual node/topic graph
rqt_console                       # Log viewer with filtering

# TF debugging
rosrun tf tf_monitor              # Monitor TF tree health
rosrun tf view_frames             # Generate TF tree PDF
rosrun tf tf_echo map base_link   # Print transform continuously

# Bag file operations
rosbag record -a                  # Record everything (careful with disk!)
rosbag record /camera/image /tf   # Record specific topics
rosbag info recording.bag         # Inspect bag contents
rosbag play recording.bag --clock # Playback with simulated time

ROS1 → ROS2 Migration Checklist

When planning a migration, note these key differences:

  • rospy → rclpy, roscpp → rclcpp
  • catkin_make → colcon build
  • roslaunch XML → ROS2 Python launch files
  • Global parameter server → Per-node parameters
  • rospy.Rate → node.create_timer()
  • Single roscore → DDS discovery (no central master)
  • message_filters works in both, but API differs
  • Custom messages: same .msg format, different build system
  • Nodelets → ROS2 Components (intra-process communication)
  • dynamic_reconfigure → ROS2 parameters with callbacks

Start migration from leaf nodes (sensors, actuators) and work inward. Use the ros1_bridge package to run both stacks simultaneously during transition.

© arpitg1304, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/ros1 of arpitg1304/robotics-agent-skills.

Open the folder on GitHubat commit f9bc546

Compare with similar skills

Ros1 next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Categories

Questions about Ros1

What does Ros1 do?

Best practices, design patterns, and common pitfalls for ROS1 (Robot Operating System 1) development. Ros1 is an agent skill from arpitg1304/robotics-agent-skills. Best practices, design patterns, and common pitfalls for ROS1 (Robot Operating System 1) development.

When should I use Ros1?

Ros1 fits situations like: building ROS1 nodes; debugging ROS1 systems; ever the user mentions ROS1; any ROS1-era robotics middleware.

How do I install Ros1 in Claude Code?

Run `npx skills add arpitg1304/robotics-agent-skills --skill ros1 -a claude-code`. Or copy the skill folder (skills/ros1 in arpitg1304/robotics-agent-skills) into .claude/skills/ros1 in your project. Claude Code loads it when a task matches its description.

How do I install Ros1 in Codex?

Run `npx skills add arpitg1304/robotics-agent-skills --skill ros1 -a codex`. Or copy the skill folder (skills/ros1 in arpitg1304/robotics-agent-skills) into .agents/skills/ros1 in your project. Codex loads it when a task matches its description.

Can I use Ros1 in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add arpitg1304/robotics-agent-skills --skill ros1 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ros1, .gemini/skills/ros1, .github/skills/ros1 and .opencode/skills/ros1 in your project.

What does Ros1 need to run?

SKILL.md names no scripts, command-line tools or credentials: Ros1 is instructions for the agent only. Our summary lists: Python 3.

Does Ros1 access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Ros1 safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Ros1 use?

Ros1 is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ros1 use?

About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Ros1?

Skills that share tags, products or a category with Ros1: Vercel Composition Patterns (supabase/supabase, 111k stars), Swiftui View Refactor (Dimillian/Skills, 4k stars), RTK Rust Design Patterns (rtk-ai/rtk, 83k stars) and Effect Client Wrapper (UsefulSoftwareCo/executor, 4.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ros1?

arpitg1304 (a GitHub user) maintains it in arpitg1304/robotics-agent-skills, which has 369 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on August 12, 2026.

Source: arpitg1304/robotics-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.