Skill Detail

Run an agent across browser and local file workflows with Magentic-UI

Use Microsoft's Magentic-UI to run supervised browser and local file tasks with an agentic UI, model endpoint, and approval-aware configuration.

Browser AutomationCustom Agents
Browser Automation Custom Agents Published
⭐ 9.9k GitHub stars
COPY SKILL INSTRUCTIONS (OPTIONAL)
npx skills add agentskillexchange/skills --skill run-an-agent-across-browser-and-local-file-workflows-with-magentic-ui Copy
Uses the third-party skills CLI, not an ASE-owned installer. Check your agent’s compatibility. This copies instructions; complete the upstream tool setup below separately.
At a glance
Tools required
Python 3.12, uv, Magentic-UI, browser/runtime prerequisites, configured model endpoint
Install & setup
Create a Python 3.12 environment with uv venv --python=3.12 --seed .venv, install the current package with uv pip install "magentic_ui>=0.2.0", then follow the upstream installation and model hosting guides to connect a model endpoint.
Author
Microsoft
Publisher
Organization
Last updated
May 29, 2026
Quick brief

Use Magentic-UI when a task needs an agent to coordinate browser actions and local file work while the operator can inspect progress, configure models, and keep approvals in the loop. It is useful for repeatable computer-use tasks where a chat-only assistant lacks the right UI and local/browser control surface. The boundary is supervised browser-plus-file agent execution, not a generic Microsoft research project or broad AutoGen framework listing.

How it works

What this skill actually does

Inputs and prerequisites: Python 3.12, uv, Magentic-UI, browser/runtime prerequisites, configured model endpoint.

Setup notes: Create a Python 3.12 environment with `uv venv –python=3.12 –seed .venv`, install the current package with `uv pip install “magentic_ui>=0.2.0″`, then follow the upstream installation and model hosting guides to connect a model endpoint.

Source and verification boundary: use https://github.com/microsoft/magentic-ui/blob/main/docs/installation.md 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 Custom Agents workflow only when the operator can invoke the documented toolchain directly, rather than treating the upstream project as a generic product listing.