cli-anything-cloudcompare

Automates CloudCompare-driven point cloud and mesh processing via unified command-line interface.

Updated May 7, 2026
One-click install
npx skills add https://github.com/dawsonblock/JUDGE_ATLAS --skill cli-anything-cloudcompare-dawsonblock
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cli-anything-cloudcompare
Source: https://github.com/dawsonblock/JUDGE_ATLAS/tree/main/external/CLI-Anything-main/skills/cli-anything-cloudcompare
Command: npx skills add https://github.com/dawsonblock/JUDGE_ATLAS --skill cli-anything-cloudcompare-dawsonblock

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

CloudCompare workflows for filtering, analysis, registration, and export are complex and repetitive to run manually. This skill provides a single command-line harness to orchestrate common 3D point cloud and mesh tasks in a consistent, agent-friendly way.

Core Features & Use Cases

  • Point cloud processing pipeline: Subsample, denoise, crop, compute normals/curvature/roughness/density, and segment connected components for downstream analysis.
  • Distance and registration: Compute cloud-to-cloud and cloud-to-mesh distances, then align datasets using ICP or rigid transformations.
  • Export for analysis or visualization: Export clouds and meshes to common formats (LAS/LAZ/PLY/PCD/OBJ/STL/E57) and batch export project contents.

Use case example: Create a repeatable change-detection workflow between two scans by aligning them with ICP and then computing cloud-to-cloud distances, ending with exported LAS/PLY data for visualization or reporting.

Quick Start

Run cli-anything-cloudcompare with a new project, load your LAS files, run ICP to align the newer scan to the older one, and export the aligned cloud as LAS.

Frequently Asked Questions about cli-anything-cloudcompare

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I compute cloud-to-cloud and cloud-to-mesh distances for point cloud analysis?

You can compute cloud-to-cloud and cloud-to-mesh distances by passing command-specific parameters to a command-line interface, which deterministically executes C2C/C2M distance calculation and optionally returns results as structured JSON.

What is the best way to automate repetitive point cloud filtering and subsampling?

Automating point cloud filtering and subsampling is best handled by a unified command-line interface. It orchestrates preprocessing tasks like cropping and denoise operations across common file formats in a consistent, agent-friendly execution model.

Can I align 3D point cloud scans using ICP and rigid transformations from the command line?

Yes, you can align 3D scans using ICP and rigid transformations from the command line. The interface applies geometric transformation matrices to registered point clouds, enabling repeatable change-detection workflows between multiple datasets.

Do I need a local CloudCompare installation to run point cloud processing commands?

Yes, a local CloudCompare installation is required. The command-line interface acts as an orchestration harness that drives the underlying CloudCompare engine to execute deterministic point cloud and mesh processing tasks.

How do I export 3D point clouds and meshes to STL, OBJ, and LAS formats?

Exporting 3D point clouds and meshes to STL, OBJ, and LAS formats is done through batch export commands. The interface supports common formats like PLY, PCD, and E57, outputting data for visualization or downstream analysis.

Does command-line point cloud processing support computing normals, curvature, and roughness?

Yes, command-line point cloud processing supports computing normals, curvature, and roughness. The interface executes feature computation commands deterministically, allowing you to calculate geometric properties and density for subsequent segmentation tasks.