Agent skill

Add Noise Model

by lge-ros2 in lge-ros2/cloisim

Add a custom noise model for sensor data simulation. An agent skill from lge-ros2/cloisim.

MITAuto-check passed

Install Add Noise Model

skills CLI
$ npx skills add lge-ros2/cloisim --skill add-noise-model -a claude-code

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

GitHub CLI
$ gh skill install lge-ros2/cloisim add-noise-model --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/lge-ros2/cloisim.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/add-noise-model .claude/skills/add-noise-model && 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
add-noise-model
GitHub stars
176
Token cost
~1.5k tokens
SKILL.md length
233 words
Files
1
Skills in repo
18
Repo updated
First seen
Licence
MIT

At a glance

Add a custom noise model for sensor data simulation. An agent skill from lge-ros2/cloisim.

  • Works in 3 steps: Create the Noise Model Class → Register in Noise Facade → Use in a Device
  • : implementing a non-Gaussian noise type
  • SKILL.md covers When to Use, Architecture, Procedure and NoiseModel Base Class API, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Add Noise Model is an agent skill from lge-ros2/cloisim. Add a custom noise model for sensor data simulation. Use when: implementing a non-Gaussian noise type, adding distance-dependent noise, creating a new sensor-specific noise profile.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Unity 6 based multi-robot simulator for ROS 2, SDFormat/SDF, LiDAR, camera, depth, IMU, GPS, and large-scale robotics simulation. The licence is MIT.

When your agent uses it

  • : implementing a non-Gaussian noise type
  • Adding distance-dependent noise
  • Creating a new sensor-specific noise profile

Example prompts

  • “/add-noise-model”

Workflow steps

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

  1. Create the Noise Model Class
  2. Register in Noise Facade
  3. Use in a Device

What it can do on your machine

Read from SKILL.md and the folder at commit f4c1f0b. 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 csharp).

    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

Add Noise Model loads about 1.5k tokens when it runs. Until then it costs about 49 tokens; SKILL.md has 233 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~49
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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 lge-ros2/cloisim at commit f4c1f0b, republished under its MIT licence (© lge-ros2). 233 words, ~1,509 tokens.

Download SKILL.mdSave it as .claude/skills/add-noise-model/SKILL.md (or your agent's skills folder).
name
add-noise-model
description
Add a custom noise model for sensor data simulation. Use when: implementing a non-Gaussian noise type, adding distance-dependent noise, creating a new sensor-specific noise profile.

Add a New Noise Model

Procedure for creating a custom noise model and integrating it with sensor devices.

When to Use

  • Implementing a new noise type beyond Gaussian (e.g., salt-and-pepper, Perlin, structured)
  • Adding distance-dependent or range-binned noise for lidar/depth sensors
  • Creating a sensor-specific noise profile from real-world calibration data

Architecture

Noise (facade)
  └── NoiseModel (abstract base)
        ├── GaussianNoiseModel (standard + dynamic bias)
        └── CustomNoiseModel (extends Gaussian, range-binned, XML-parameterized)
  • Noise is the public API used by devices — handles threading via Parallel.For
  • NoiseModel is the abstract base with bias sampling, clamping, quantization
  • GaussianNoiseModel implements standard Gaussian with dynamic bias correlation
  • CustomNoiseModel extends Gaussian with range-binned noise from XML parameters

Procedure

1. Create the Noise Model Class

Create Assets/Scripts/Devices/Modules/NoiseModel/MyNoiseModel.cs:

csharp
/*
 * Copyright (c) 2026 LG Electronics Inc.
 *
 * SPDX-License-Identifier: MIT
 */

using System;

public class MyNoiseModel : NoiseModel
{
	// Custom parameters
	private readonly double _myParam;

	public MyNoiseModel(in SDFormat.Noise parameter)
		: base(parameter)
	{
		// Extract parameters from SDFormat.Noise or custom fields
		_myParam = parameter.StdDev; // or a custom parameter
	}

	public override T Generate<T>(T data, float deltaTime)
	{
		var value = Convert.ToDouble(data);

		// Apply your noise model
		var noise = ComputeNoise(value, deltaTime);
		var output = value + bias + noise;

		// Apply quantization if enabled
		if (_quantized)
		{
			if (Math.Abs(_parameter.Precision - 0d) > Epsilon)
			{
				output = Math.Round(output / _parameter.Precision) * _parameter.Precision;
			}
		}

		// Apply clamping
		return (T)Convert.ChangeType(Clamp(output), typeof(T));
	}

	private double ComputeNoise(double value, float deltaTime)
	{
		// Your noise algorithm here
		// Use RandomNumberGenerator for RNG:
		var random = RandomNumberGenerator.GetNormal(0, _myParam);
		return random;
	}
}
2. Register in Noise Facade

Edit Assets/Scripts/Devices/Modules/Noise.cs — add a case in the constructor:

csharp
public Noise(in SDFormat.Noise noise)
{
	switch (noise.Type)
	{
		case SDFormat.NoiseType.Gaussian:
		case SDFormat.NoiseType.GaussianQuantized:
			_noiseModel = new GaussianNoiseModel(noise);
			if (noise.Type == SDFormat.NoiseType.GaussianQuantized)
				_noiseModel.SetQuantization(true);
			break;

		case SDFormat.NoiseType.MyType:  // Add new case
			_noiseModel = new MyNoiseModel(noise);
			break;

		default:
			_noiseModel = null;
			break;
	}
}

If using a custom noise type string, add it to the SDFormat.NoiseType enum in the SDFormat package.

3. Use in a Device
csharp
// In the sensor device class:
private Noise _noise;

public void SetupNoise(in SDFormat.Noise noise)
{
	_noise = new Noise(noise);
	_noise.SetClampMin(0);        // optional: clamp minimum
	_noise.SetClampMax(maxRange); // optional: clamp maximum
}

// Apply to single value:
protected override void GenerateMessage()
{
	float value = ReadSensorValue();
	_noise.Apply<float>(ref value, Time.fixedDeltaTime);
	_msg.Value = value;
}

// Apply to array (parallelized automatically):
protected override void GenerateMessage()
{
	float[] data = ReadSensorArray();
	_noise.Apply<float>(data, Time.fixedDeltaTime);
}

NoiseModel Base Class API

csharp
// Available in base class:
protected readonly SDFormat.Noise _parameter;  // Original SDF noise parameters
protected double bias;                          // Sampled bias (from BiasMean/BiasStdDev)
protected bool _quantized;                      // Whether to quantize output
protected double clampMin, clampMax;            // Output clamping bounds

// Methods:
protected double Clamp(in double value);        // Apply clamping
protected double Expm1(in double value);        // exp(x) - 1 helper

// Static RNG:
RandomNumberGenerator.GetNormal(mean, stddev);  // Box-Muller Gaussian
RandomNumberGenerator.GetNormal();              // Standard normal (0, 1)
RandomNumberGenerator.GetUniform();             // Uniform [0, 1)

Dynamic Bias (from GaussianNoiseModel)

If your model needs time-correlated bias drift:

csharp
// Available if extending GaussianNoiseModel:
protected double ComputeDynamicBias(in float deltaTime)
{
	// Uses _parameter.DynamicBiasStdDev and DynamicBiasCorrelationTime
	// Returns time-varying bias using Ornstein-Uhlenbeck process
}

GPU Noise (Shader-Based)

For camera sensors, noise is applied on the GPU via AddGaussianNoise.shader:

csharp
// In a camera device:
_noiseMaterial = new Material(Shader.Find("Sensor/Camera/GaussianNoise"));
_noiseMaterial.SetFloat("_Mean", mean);
_noiseMaterial.SetFloat("_StdDev", stddev);

// Applied via CommandBuffer blit in the camera's render pipeline

Threading

The Noise class uses Parallel.For with adaptive parallelism:

csharp
// Thread count: max(1, ProcessorCount / 4)
Parallel.For(0, data.Length, _parallelOptions, i =>
{
    data[i] = _noiseModel.Generate(data[i], deltaTime);
});

Each Generate() call must be thread-safe — avoid shared mutable state. RandomNumberGenerator uses ThreadLocal<Random> internally.

Checklist

  • Noise model class extends NoiseModel (or GaussianNoiseModel)
  • Generate<T>() is thread-safe
  • Registered in Noise constructor switch
  • Uses RandomNumberGenerator for RNG (thread-safe)
  • Applies Clamp() on output
  • Handles quantization if _quantized is true
  • SDFormat noise type enum extended (if new type)
  • License header on file
  • Tabs for indentation, Allman braces

© lge-ros2, MIT. 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 .github/skills/add-noise-model of lge-ros2/cloisim.

Open the folder on GitHubat commit f4c1f0b

Compare with similar skills

Add Noise Model 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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Add Noise Model this skilllge-ros2/cloisim176—~1.5kAutomated safety check: PassMIT
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Simulateindranilbanerjee/digital-marketing-pro8621 repos~2kAutomated safety check: PassMIT
Limrun iOS Simulatorsuperset-sh/superset15k—~5.2kAutomated safety check: NotesCustom licence
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Questions about Add Noise Model

What does Add Noise Model do?

Add a custom noise model for sensor data simulation. An agent skill from lge-ros2/cloisim. Add Noise Model is an agent skill from lge-ros2/cloisim. Add a custom noise model for sensor data simulation.

When should I use Add Noise Model?

Add Noise Model fits situations like: : implementing a non-Gaussian noise type; adding distance-dependent noise; creating a new sensor-specific noise profile.

How do I install Add Noise Model in Claude Code?

Run `npx skills add lge-ros2/cloisim --skill add-noise-model -a claude-code`. Or copy the skill folder (.github/skills/add-noise-model in lge-ros2/cloisim) into .claude/skills/add-noise-model in your project. Claude Code loads it when a task matches its description.

How do I install Add Noise Model in Codex?

Run `npx skills add lge-ros2/cloisim --skill add-noise-model -a codex`. Or copy the skill folder (.github/skills/add-noise-model in lge-ros2/cloisim) into .agents/skills/add-noise-model in your project. Codex loads it when a task matches its description.

Can I use Add Noise Model 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 lge-ros2/cloisim --skill add-noise-model -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/add-noise-model, .gemini/skills/add-noise-model, .github/skills/add-noise-model and .opencode/skills/add-noise-model in your project.

What does Add Noise Model need to run?

SKILL.md names no scripts, command-line tools or credentials: Add Noise Model is instructions for the agent only.

Does Add Noise Model 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 Add Noise Model 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 Add Noise Model use?

Add Noise Model is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Add Noise Model use?

About 1.5k tokens (SKILL.md is roughly 6k 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 Add Noise Model?

Skills that share tags, products or a category with Add Noise Model: Eas Simulator (sickn33/agentic-awesome-skills, 47k stars), Flux Balance Analysis Simulator (aiming-lab/AutoResearchClaw, 15k stars), Simulate (indranilbanerjee/digital-marketing-pro, 862 stars) and Limrun iOS Simulator (superset-sh/superset, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Add Noise Model?

lge-ros2 (a GitHub organization) maintains it in lge-ros2/cloisim, which has 176 GitHub stars. The repository holds 18 skills in this directory. The repository was last updated on October 6, 2026.

Source: lge-ros2/cloisim on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.