dsh-computer-use-windows
Run the following command in DeepSeek Harness:
dsh plugin install Altairpaca/dsh-computer-use-windows
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install Altairpaca/dsh-computer-use-windows in your DeepSeek Harness terminal to install the Windows desktop-automation plugin from https://github.com/Altairpaca/dsh-computer-use-windows.
About this plugin
In real desktop automation, coordinate-only clicking is surprisingly brittle: screenshots capture unrelated windows, OCR positions drift, and a click can silently land on the wrong UI state. dsh-computer-use-windows was built to address exactly this failure mode, treating every action as an observable state transition rather than a blind pixel command.
The core design rests on three invariants: window-scoped coordinates, text before pixels, and post-action verification. Capabilities include target-window screenshots with OCR text grounding, an OCR-locate-click-verify-retry loop, mouse-keyboard-clipboard primitives, window enumeration and focus, batch action execution, and an optional OpenAI-compatible vision endpoint. In OCR-only mode screenshots never leave the machine, so no external vision model is required.
The plugin is currently an experimental alpha. It is best suited for teams or individuals developing and testing Windows desktop-automation workflows in controlled environments. While it does not yet promise production-grade unattended automation, it provides a clear engineering skeleton for the see-act-verify pattern that makes desktop automation reliable.
Use Cases
- Reliably clicking UI elements inside a specific Windows window via OCR text grounding
- Building pure-local OCR automation pipelines where screenshots never leave the machine
- Developing and testing Windows desktop-automation workflows in controlled environments
Best For
- Developers building Windows desktop-automation pipelines on DeepSeek Harness
- Teams that need a local-only OCR path and want screenshots to stay on-device
- Engineers prototyping the see-act-verify pattern in controlled desktop-automation settings
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