automation-skill advanced active

Computer Use

No API means no automation — until now. Legacy desktop apps block every workflow you try to build. Give OpenClaw full GUI control over any application.

What breaks without openclaw computer use skill

No-API desktop apps. Manual clicks consuming hours. RPA tools that break on resize.

Full desktop automation × 200-star proven skill ÷ 20–35 minutes ÷ no new infrastructure = every app becomes automatable.

openclaw computer use skill — what it actually does

01
Control mouse clicks and keyboard input on any desktop application.
02
Read screen state to make context-aware automation decisions.
03
Build end-to-end RPA pipelines without an API.
04
Use semantic selectors to survive window resizes.
05
Test safely on non-production machines before going live.

Security check — openclaw computer use skill

Privacy score: 7/10 — accesses connected platform APIs only. Lock it: review OAuth scopes before install, confirm Linux with display server; OpenClaw ≥1.0; xdotool compatibility.

Quick start — openclaw computer use skill in 20–35 minutes

Setup time: 20–35 minutes

!
You need:
  • OpenClaw core
  • display server
  • xdotool or equivalent

Install the package:

# Install via ClawhHub
clawhub install ram-raghav-s/computer-use
1
Install xdotool: sudo apt install xdotool
2
Install the skill
3
Set DISPLAY=:0 in .env if running headless
4
Run /computer click <x> <y> or /computer type <text>

Troubleshooting openclaw computer use skill

1
1. UI coordinates change when windows are resized — use semantic selectors when possible
2
2. Computer-use actions are irreversible — always test on a non-production machine first

Compatibility & status

Works with: Linux with display server; OpenClaw ≥1.0; xdotool advanced Last updated: Nov 2025 ★ 200 on GitHub MIT

Official docs →

View on GitHub →

Related — more like openclaw computer use skill

Every GUI workflow you run manually today costs you minutes you will never recover. Install on a test machine now before the next repetitive task lands in your queue.

Get it on GitHub →