
CloudAnalyzer Command-Line Harness
Lets an agent run CloudAnalyzer point cloud and trajectory QA checks from the command line
- Repository
- HKUDS/CLI-Anything
- Stars
- 58,084
- Licence
- Apache-2.0
- Files
- 1 file
What it does
This skill teaches an AI agent to operate CloudAnalyzer, a QA tool for checking 3D point cloud outputs from mapping, localization and perception systems. Once installed, the agent can run evaluations such as Chamfer distance, F1 and trajectory error (ATE/RPE), apply pass/fail quality gates from a config file, manage baseline histories, and process or convert point cloud files. It exposes 27 commands and asks for JSON output so the agent can read results.
Great for
- Robotics or autonomous driving engineers checking SLAM map and trajectory quality
- Teams that want automated pass/fail QA gates on mapping outputs in CI pipelines
- Developers who want an agent to batch-evaluate many point cloud runs
Skip it if
- General 3D modelling or image work, since it only covers point cloud QA and processing
- Users without Python and point cloud data, because the commands need local .pcd, .las or CSV trajectory files to be useful
- Running on sensitive datasets without review, since the tool executes local processing and some commands open viewers or write files
Try asking
- “Evaluate output.pcd against reference.pcd and report Chamfer and F1 as JSON”
- “Check trajectory est.csv against gt.csv with a max ATE of 0.5 m and tell me if it passes”
- “Create a starter integrated QA config and run the quality gate”
- “Compare this week's QA summary with the stored baseline history and recommend whether to promote it”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 1 original files, the Apache-2.0 licence and an attribution note.
skills.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip skills.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip skills.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Always pass --json so the agent gets machine-readable output to parse
- Start with check init to generate a config, then edit thresholds before running check run
- Keep baseline history in a dedicated directory and use baseline list to inspect it before promoting
What's inside
- SKILL.md
Redistributed unmodified from HKUDS/CLI-Anything under the Apache-2.0 licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.