How does this skill differ from standard vision-based screen recording or prompting?

Unlike vision-only models that rely on pixels, this skill accesses the Windows UI Automation (UIA) tree to see structural element IDs, ensuring your agent clicks the exact button intended even if the layout shifts.

What are the system requirements and supported application types?

This skill requires a Windows host environment and the vision-bridge MCP server; it supports native applications (Win32, WPF, UWP), Electron apps, and browsers like Chrome via the DevTools Protocol.

Can it interact with applications that don't have a standard UI hierarchy, like legacy tools or games?

Yes, for windows that expose little to UI Automation (typical for Electron/Chromium apps) the server falls back to OCR and returns text regions as clickable elements. OCR finds text only: icon-only buttons without a label cannot be located this way.

What exactly is included?

A SKILL.md that teaches your agent when and how to use vision-bridge, plus reference files: setup and client config, a full tool reference, and worked flows (forms, installers, Notepad, Electron apps, browser). The vision-bridge MCP server itself is free and open source on GitHub.

How does the skill handle errors or pop-up windows that appear unexpectedly?

The skill employs a "Result Verification" step, meaning it re-scans the UI state after every action to confirm the click or keystroke was successful before proceeding to the next task.

vision bridge windows automation

Example session with this skill installed

Open Notepad, type 'System Check Complete', and save it to the desktop as log.txt.

Read your context and instructions
Compiled the vision bridge windows

Notepad is open, the text is typed and verified, and the file is saved as log.txt on your Desktop.

What I did

Step	Tool call	Result
1	`capture("Notepad")`	Window found via UIA, document field `u0`
2	`act("u0", "set_value", value="System Check Complete")`	ok
3	`act("u0", "read")`	content = "System Check Complete" (matches)
4	`find("File", target="Notepad")` → `act("u3", "click")`	File menu opened
5	`find("Save as", target="Notepad")` → `act("u9", "click")`	Save dialog opened
6	`wait_for("File name", target="Save as", timeout_s=10)`	field `u21` ready
7	`act("u21", "set_value", value="%USERPROFILE%\Desktop\log.txt")`	ok
8	`find("Save", target="Save as")` → `act("u27", "click")`	dialog closed
9	`capture("Notepad")`	title now "log.txt - Notepad"

Verification

Typed text was read back before saving, not assumed.
Ids were refreshed after every window change, so no stale clicks.
No overwrite prompt appeared; if log.txt had existed, I would have asked before replacing it.

Next steps

Append a timestamp line on each run with act("u0", "type", ...).
Run the same flow on a schedule for a daily health-check log.

Connects securely to your tools. The creator never sees your data.

About this skill

Automating Windows desktop applications often requires fragile pixel-based scripts or expensive RPA tools. This skill provides a direct bridge between your agent and the Windows UI Automation (UIA) tree, enabling reliable interaction with native apps, Electron windows, and browsers through structured text.

What it does

Structured UI Navigation reads the screen as a hierarchy of text and elements rather than just pixels.
Native App Control drives Win32, WPF, UWP, and WinForms applications using stable element IDs.
OCR Fallback handles Electron apps and image-heavy interfaces when the accessibility tree is unavailable.
Browser Integration connects to existing Chrome sessions via CDP to reuse logged-in states and bypass manual auth.
State Verification confirms every click and type action by re-capturing the UI state to ensure reliability.

How it works

Target Identification locates specific windows by title substrings or focuses the active foreground window.
Screen Capture retrieves the current element tree, including text content, element roles, and unique IDs.
Action Execution performs clicks, double-clicks, typing, or value settings based on the discovered IDs.
Result Verification re-scans the UI after each action to confirm the application state changed as expected.

Frameworks & tools

This skill utilizes the vision-bridge MCP server, leveraging Windows UI Automation (UIA), Tesseract OCR for visual recognition, and Chrome DevTools Protocol (CDP) for browser automation.

Why this beats prompting it yourself

Standard vision prompts struggle with precision on complex desktop layouts and cannot interact with the OS. This skill provides a systematic loop of discovery and verification, ensuring the agent doesn't "hallucinate" buttons or click the wrong coordinates.

Use cases

Automating data entry into legacy ERP or accounting software without APIs.
Managing complex software installations or system configuration dialogs.
Extracting data from desktop-only programs into structured formats.
Running web workflows within the user's authenticated browser session.

Known limitations

Requires a Windows host with the vision-bridge MCP server installed. Native UIA backend is faster than OCR; OCR performance depends on installed language data.

How to use

Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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vision bridge windows automation