Testdriver:Parse logo

Testdriver:Parse

Organization
testdriverai
testdriver:parse

Detect all UI elements on screen using OmniParser

Overview

Publishertestdriverai
Repositorytestdriverai
Skill nametestdriver:parse
Stars
465
Forks
39
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by testdriverai on GitHub. Read the source before you install it.

Installation

Install the Testdriver:Parse AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/testdriverai/testdriverai/tree/main/ai/skills/testdriver-parse
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/testdriverai/testdriverai.git /tmp/testdriverai
mkdir -p .claude/skills
cp -r /tmp/testdriverai/ai/skills/testdriver-parse .claude/skills/testdriverai-testdriver-parse
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Testdriver:Parse in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Testdriver:Parse on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Testdriver:Parse is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Overview

Parse the screen with OmniParser v2 to find all visible UI elements. TestDriver returns structured data. This includes element types, text content, interactivity levels, and bounding box coordinates.

This method examines all of the screen and returns each element that it finds. Use it for these:

  • To understand the full UI layout of a screen
  • To find all clickable or interactive elements
  • To build custom element logic
  • To debug which elements TestDriver can find
  • To do an accessibility audit

Syntax

javascript
const result = await testdriver.parse()

Parameters

None.

Returns

Promise<ParseResult> - Object containing detected UI elements

ParseResult

PropertyTypeDescription
elementsParsedElement[]Array of detected UI elements
annotatedImageUrlstringURL of the annotated screenshot with bounding boxes
imageWidthnumberWidth of the analyzed screenshot
imageHeightnumberHeight of the analyzed screenshot

ParsedElement

PropertyTypeDescription
indexnumberElement index
typestringElement type (e.g. "text", "icon", "button")
contentstringText content or description of the element
interactivitystringInteractivity level (e.g. "clickable", "non-interactive")
bboxobjectBounding box in pixel coordinates {x0, y0, x1, y1}
boundingBoxobjectBounding box as {left, top, width, height}

Examples

Get All Elements on Screen

javascript
const result = await testdriver.parse();
console.log(`Found ${result.elements.length} elements`);

result.elements.forEach((el, i) => {
  console.log(`${i + 1}. [${el.type}] "${el.content}" (${el.interactivity})`);
});

Find Clickable Elements

javascript
const result = await testdriver.parse();

const clickable = result.elements.filter(e => e.interactivity === 'clickable');
console.log(`Found ${clickable.length} clickable elements`);

clickable.forEach(el => {
  console.log(`- "${el.content}" at (${el.bbox.x0}, ${el.bbox.y0})`);
});

Find and Click an Element by Content

javascript
const result = await testdriver.parse();

// Find a "Submit" button
const submitBtn = result.elements.find(e => 
  e.content.toLowerCase().includes('submit') && e.interactivity === 'clickable'
);

if (submitBtn) {
  // Calculate center of the bounding box
  const x = Math.round((submitBtn.bbox.x0 + submitBtn.bbox.x1) / 2);
  const y = Math.round((submitBtn.bbox.y0 + submitBtn.bbox.y1) / 2);
  
  await testdriver.click({ x, y });
}

Filter by Element Type

javascript
const result = await testdriver.parse();

// Get all text elements
const textElements = result.elements.filter(e => e.type === 'text');
textElements.forEach(e => console.log(`Text: "${e.content}"`));

// Get all icons
const icons = result.elements.filter(e => e.type === 'icon');
console.log(`Found ${icons.length} icons`);

// Get all buttons
const buttons = result.elements.filter(e => e.type === 'button');
console.log(`Found ${buttons.length} buttons`);

Build Custom Assertions

javascript
import { describe, expect, it } from "vitest";
import { TestDriver } from "testdriverai/vitest/hooks";

describe("Login Page", () => {
  it("should have expected form elements", async (context) => {
    const testdriver = TestDriver(context);
    
    await testdriver.provision.chrome({
      url: 'https://myapp.com/login',
    });

    const result = await testdriver.parse();
    
    // Assert expected elements exist
    const textContent = result.elements.map(e => e.content.toLowerCase());
    expect(textContent).toContain('email');
    expect(textContent).toContain('password');
    
    // Assert there are clickable elements
    const clickable = result.elements.filter(e => e.interactivity === 'clickable');
    expect(clickable.length).toBeGreaterThan(0);
  });
});

Use Bounding Box Coordinates

javascript
const result = await testdriver.parse();

result.elements.forEach(el => {
  // Pixel coordinates
  console.log(`Element "${el.content}":`);
  console.log(`  bbox: (${el.bbox.x0}, ${el.bbox.y0}) to (${el.bbox.x1}, ${el.bbox.y1})`);
  console.log(`  size: ${el.boundingBox.width}x${el.boundingBox.height}`);
  console.log(`  position: left=${el.boundingBox.left}, top=${el.boundingBox.top}`);
});

View Annotated Screenshot

javascript
const result = await testdriver.parse();

// The annotated image shows all detected elements with bounding boxes
console.log('Annotated screenshot:', result.annotatedImageUrl);
console.log(`Image dimensions: ${result.imageWidth}x${result.imageHeight}`);

How It Works

  1. TestDriver captures a screenshot of the current screen
  2. The image is sent to the TestDriver API
  3. OmniParser v2 analyzes the image to detect all UI elements
  4. Each element is classified by type (text, icon, button, etc.) and interactivity
  5. Bounding box coordinates are returned in pixel coordinates matching the screen resolution

Best Practices

```javascript
// Prefer this for clicking a specific element
await testdriver.find("Submit button").click();

// Use parse() for full UI analysis
const result = await testdriver.parse();
const allButtons = result.elements.filter(e => e.type === 'button');
```
```javascript
const result = await testdriver.parse();
const interactive = result.elements.filter(e => e.interactivity === 'clickable');
const static_ = result.elements.filter(e => e.interactivity === 'non-interactive');
```
```javascript
// Wait for page to stabilize
await testdriver.wait(2000);

// Then parse
const result = await testdriver.parse();
```
```javascript
const result = await testdriver.parse();
console.log('View annotated screenshot:', result.annotatedImageUrl);
```

Related

Frequently asked questions

What does the Testdriver:Parse AI skill do?

Detect all UI elements on screen using OmniParser

Why use Testdriver:Parse on TypingMind?

Because you install it once and use it with any model. Testdriver:Parse is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Testdriver:Parse in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/testdriverai/testdriverai/tree/main/ai/skills/testdriver-parse. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Testdriver:Parse?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Testdriver:Parse?

As many as you like. As long as a model supports skills, you can use Testdriver:Parse with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Testdriver:Parse AI skill free?

It is published on GitHub by testdriverai. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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