vitest-midscene-e2e

web-infra-dev/midscene-skills · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/web-infra-dev/midscene-skills --skill vitest-midscene-e2e
0 commentsdiscussion
summary

Supported platforms:

skill.md

Vitest Midscene E2E

Modules

Module Role
Vitest TypeScript test framework. Provides describe/it/expect/hooks for test organization, assertions, and lifecycle.
Midscene AI-driven UI automation. Interacts with UI elements via natural language — no fragile selectors. Core API: aiAct.

Supported platforms:

  • WebWebTest (Playwright Chromium): ctx.agent + ctx.page
  • AndroidAndroidTest (ADB + scrcpy): ctx.agent only
  • iOSIOSTest (WebDriverAgent): ctx.agent only

Workflow

Step 1: Clone boilerplate & ensure project ready

bash scripts/clone-boilerplate.sh

The boilerplate at ~/.midscene/boilerplate/vitest-all-platforms-demo/ is the canonical reference for project structure, configs, platform context classes, and test conventions. Compare the current project against it. If anything is missing, ask the user which platform(s) they need (Web / Android / iOS), then fill in what's missing using the boilerplate as the target state. Only include files for the requested platform(s). Do NOT overwrite existing configs or files. Copy .env.example from the boilerplate as .env if it doesn't exist, and prompt the user to fill in the env vars.

Step 2: Read the Midscene Agent API section below before writing tests

It contains mandatory rules for using aiAct — the primary API for all UI operations. Do NOT skip this step.

Step 3: Create, update, or run tests

Use the boilerplate's e2e/ directory and src/context/ as reference for patterns and conventions. Before running tests, ensure dependencies are installed and .env is configured. When debugging failures, check troubleshooting.md.

Midscene Agent API

ctx.agent is a platform-specific agent instance. All methods return Promises.

  • Web: PlaywrightAgent from @midscene/web/playwright
  • Android: AndroidAgent from @midscene/android
  • iOS: IOSAgent from @midscene/ios

All three agents share the same AI methods below.

Mandatory Rule: Use aiAct for User-Described Steps

When the user describes a UI action or state confirmation in natural language, you MUST use aiAct to implement it. Do NOT decompose user instructions into aiTap/aiInput/aiAssert or other fine-grained APIs. Pass the user's intent directly to aiAct and let Midscene's AI handle the planning and execution.

// User says: "type iPhone in the search box and click search"

// WRONG — manually decomposing into fine-grained APIs
await ctx.agent.aiInput('search box', { value: 'iPhone' });
await ctx.agent.aiTap('search button');

// CORRECT — pass intent directly to aiAct
await ctx.agent.aiAct('type "iPhone" in the search box, then click the search button');

Assertions, data extraction, and waiting should also be done via aiAct — it handles all of these. Do NOT use aiAssert, aiQuery, aiWaitFor, aiTap, or aiInput separately.

aiAct(taskPrompt, opt?) — Primary API

aiAct is the primary API for all UI operations and state confirmations. It accepts natural language instructions and autonomously plans and executes multi-step interactions.

// UI operations
await ctx.agent.aiAct('type "iPhone" in the search box, then click the search button');
await ctx.agent.aiAct('hover over the user avatar in the top right');

// State confirmations / assertions — also use aiAct
await ctx.agent.aiAct('verify the page shows "Login successful"');
await ctx.agent.aiAct('verify the error message is visible');

Phase splitting: If the task prompt is too long or covers multiple distinct stages, split it into separate aiAct calls — one per phase. Each phase should be a self-contained logical step, and all phases combined must match the user's original intent.

// Incorrect — prompt spans multiple pages and too many steps, AI may lose context mid-way
await ctx.agent.aiAct('click the settings button in the top nav, go to settings page, find personal info and click into it, change email to "[email protected]", change phone to "13800000000", click save, wait for success');

// Correct — split by page/stage boundary, each phase stays within one logical context
await ctx.agent.aiAct('click the settings button in the top nav, go to settings page, find personal info and click into it');
await ctx.agent.aiAct('change email to "[email protected]", change phone to "13800000000", click save');
await ctx.agent.aiAct('verify the save success message appears');

aiAction is deprecated. Use aiAct or ai instead.

Common Mistakes

  • Vague locators'button' is ambiguous; use 'the blue "Submit" button at the top of the page'
  • Deprecated aiAction — use aiAct instead
  • Ambiguous multi-element targets — specify row/position: 'the delete button in the first product row'

Agent Configuration — aiActionContext

aiActionContext is a system prompt string appended to all AI actions performed by the agent. Use it to define the AI's role and expertise.

// Set via agentOptions in setup()
const ctx = WebTest.setup('https://example.com', {
  agentOptions: {
    aiActionContext: 'You are a Web UI testing expert.',
  },
});

Good examples:

  • 'You are a Web UI testing expert.'
  • 'You are an Android app testing expert who is familiar with Chinese UI.'

Bad examples:

  • 'Click the login button.' — specific actions belong in aiAct(), not aiActionContext
  • 'The page is in Chinese.' — this is page description, not a system prompt

How to Look Up More

  1. In node_modules/@midscene/web, node_modules/@midscene/android, and node_modules/@midscene/ios, find the type definitions for the agent classes
  2. If types are not enough, follow the source references in the .d.ts files to read the implementation code in node_modules
  3. Download https://midscenejs.com/llms.txt, then use grep to search for the API or concept you need (the file is large, do not read it in full)
how to use vitest-midscene-e2e

How to use vitest-midscene-e2e on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add vitest-midscene-e2e
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/web-infra-dev/midscene-skills --skill vitest-midscene-e2e

The skills CLI fetches vitest-midscene-e2e from GitHub repository web-infra-dev/midscene-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/vitest-midscene-e2e

Reload or restart Cursor to activate vitest-midscene-e2e. Access the skill through slash commands (e.g., /vitest-midscene-e2e) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.851 reviews
  • Mei Chawla· Dec 28, 2024

    I recommend vitest-midscene-e2e for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Diego Diallo· Dec 20, 2024

    vitest-midscene-e2e reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Dhruvi Jain· Dec 12, 2024

    vitest-midscene-e2e reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Arjun Johnson· Dec 4, 2024

    Useful defaults in vitest-midscene-e2e — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Noor Tandon· Nov 23, 2024

    Registry listing for vitest-midscene-e2e matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Anaya Thomas· Nov 19, 2024

    vitest-midscene-e2e reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Arya Iyer· Nov 15, 2024

    vitest-midscene-e2e has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Advait Sanchez· Nov 11, 2024

    I recommend vitest-midscene-e2e for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Anika Srinivasan· Nov 11, 2024

    Solid pick for teams standardizing on skills: vitest-midscene-e2e is focused, and the summary matches what you get after install.

  • Oshnikdeep· Nov 3, 2024

    I recommend vitest-midscene-e2e for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

showing 1-10 of 51

1 / 6