Use OmniParser for vision-based GUI parsing
Parse screenshots into structured UI elements so computer-use agents can reason about controls before acting.
npx skills add agentskillexchange/skills --skill use-omniparser-for-vision-based-gui-parsing
Use OmniParser when a computer-use or GUI automation agent needs structured screen understanding before selecting actions. The workflow is to capture a UI screenshot, run OmniParser with the downloaded model weights, convert visual regions into actionable elements, and pass that structured state to the agent or an evaluation pipeline. The scope boundary is screenshot-to-UI-element parsing for GUI agents; it is not a broad browser automation entry because it does not own navigation or task execution, only the visual grounding layer that makes those actions more reliable.
What this skill actually does
Inputs and prerequisites: Python 3.12; conda; Hugging Face model weights; optional Gradio demo.
Setup notes: Clone https://github.com/microsoft/OmniParser, create the documented conda environment, install requirements.txt, download the OmniParser model weights from Hugging Face, then run the demo or integrate the parser into a GUI-agent pipeline.
Source and verification boundary: use https://microsoft.github.io/OmniParser/ as the canonical reference before running the workflow; keep commands, API calls, CLI usage, and generated outputs reviewable against that upstream source.
Framework fit: publish this as a Multi-Framework workflow only when the operator can invoke the documented toolchain directly, rather than treating the upstream project as a generic product listing.