ai-dashboad/flutter-skill

e2e-testing

AI-powered E2E testing for any app — Flutter, React Native, iOS, Android, Electron, Tauri, KMP, .NET MAUI.

Trending #9416 First seen Feb 15, 2026

Installation

$ npx skills add ai-dashboad/flutter-skill --skill e2e-testing

Summary

  • AI-powered E2E testing for any app — Flutter, React Native, iOS, Android, Electron, Tauri, KMP, .NET MAUI.
  • Connects via MCP to running apps so the agent can take screenshots, tap elements, enter text, scroll, inspect UI trees, and verify state with natural language.
  • Use when the user wants to test an app's UI end-to-end, automate cross-platform testing, run smoke tests, validate form flows, or verify navigation without writing test code.

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Also in this package

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 369
License LICENSE
Default branch main
Open issues 6
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents windsurf

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 6,013 B
  • docs SUMMARY.md 3,948 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 224 installs

SKILL.md

AI E2E Testing — 8 Platforms, Zero Test Code

flutter-skill is an MCP server that connects AI agents to running apps across 8 platforms. The agent takes screenshots, taps elements, enters text, scrolls, navigates, inspects UI trees, and verifies state — all through natural language.

Supported Platforms

Platform Setup
Flutter (iOS/Android/Web) flutter pub add flutter_skill
React Native npm install flutter-skill-react-native
Electron npm install flutter-skill-electron
iOS (Swift/UIKit) SPM: FlutterSkillSDK
Android (Kotlin) Gradle: flutter-skill-android
Tauri (Rust) cargo add flutter-skill-tauri
KMP Desktop Gradle dependency
.NET MAUI NuGet package

Install

# npm (recommended)
npm install -g flutter-skill

# Homebrew
brew install ai-dashboad/flutter-skill/flutter-skill

# Or download binary from GitHub Releases

MCP Configuration

Add to your AI agent's MCP config (Claude Desktop, Cursor, Windsurf, OpenClaw, etc.):

{
  "mcpServers": {
    "flutter-skill": {
      "command": "flutter-skill",
      "args": ["server"]
    }
  }
}

Quick Start

1. Initialize your app (one-time)

flutter-skill init

Auto-detects project type and patches your app with the testing bridge.

Verify: Output should confirm the project type was detected and main entry point was patched. If it fails, check that you are in the project root and the framework is supported.

2. Launch and connect

flutter-skill launch .

Verify: A VM Service URI appears in the output (e.g. ws://127.0.0.1:50000/ws). If no URI appears, check that Flutter/the target framework is installed and the app compiles.

3. Test with natural language

The agent follows this core loop:

  1. screenshot() — see the current screen
  2. inspect_interactive() — discover all tappable/typeable elements with semantic refs
  3. tap(ref: "button:Login") — tap using stable semantic reference
  4. enter_text(ref: "input:Email", text: "[email protected]") — type into field
  5. waitforelement(key: "Dashboard") — verify navigation succeeded
  6. screenshot() — confirm final state

If inspectinteractive() returns no elements: Take a screenshot to confirm the screen loaded, then check getlogs() for errors. The app may still be loading — retry after a short wait.

Available MCP Tools

Core Actions

Tool Description
screenshot Capture current screen as image
tap Tap element by key, text, ref, or coordinates
enter_text Type text into a field
scroll Scroll up/down/left/right
swipe Swipe gesture between points
long_press Long press an element
drag Drag from point A to B
go_back Navigate back
press_key Send keyboard key events

Inspection

Tool Description
inspect_interactive Get all interactive elements with semantic ref IDs
get_elements List all elements on screen
find_element Find element by key or text
waitforelement Wait for element to appear (with timeout)
getelementproperties Get detailed properties of an element

Text Manipulation

Tool Description
set_text Replace text in a field
clear_text Clear a text field
get_text Read text content

App Control

Tool Description
get_logs Read app logs
clear_logs Clear log buffer

Semantic Refs

inspect_interactive returns elements with stable semantic reference IDs:

button:Login          → Login button
input:Email           → Email text field
toggle:Dark Mode      → Dark mode switch
button:Submit[1]      → Second Submit button (disambiguated)

Format: {role}:{content}[{index}]

7 roles: button, input, toggle, slider, select, link, item

Use refs for reliable element targeting that survives UI changes:

tap(ref: "button:Login")
enter_text(ref: "input:Email", text: "[email protected]")

Testing Workflow

Core Loop

screenshot() → inspect_interactive() → tap/enter_text → screenshot() → verify

Always call screenshot() before and after actions. Use waitforelement() after navigation — apps need time to transition.

Validation Checkpoints

  • After screenshot(): Confirm the expected screen is visible before acting.
  • After tap() or enter_text(): Call screenshot() to verify the UI responded.
  • After navigation: Use waitforelement(key: "targetscreen") with a timeout. If it times out, call screenshot() and getlogs() to diagnose.
  • On unexpected state: Call getlogs() and inspectinteractive() to understand what elements are present.

Element Targeting Priority

  1. ref: (most reliable) — semantic ref from inspect_interactive()
  2. key: — widget key set by the developer
  3. text: — visible text content (fragile if text changes)
  4. Coordinates — last resort, breaks on different screen sizes

Links