axiom-ui-testing

charleswiltgen/axiom · updated Apr 8, 2026

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$npx skills add https://github.com/charleswiltgen/axiom --skill axiom-ui-testing
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summary

Wait for conditions, not arbitrary timeouts. Core principle Flaky tests come from guessing how long operations take. Condition-based waiting eliminates race conditions.

skill.md

UI Testing

Overview

Wait for conditions, not arbitrary timeouts. Core principle Flaky tests come from guessing how long operations take. Condition-based waiting eliminates race conditions.

NEW in WWDC 2025: Recording UI Automation allows you to record interactions, replay across devices/languages, and review video recordings of test runs.

Example Prompts

These are real questions developers ask that this skill is designed to answer:

1. "My UI tests pass locally on my Mac but fail in CI. How do I make them more reliable?"

→ The skill shows condition-based waiting patterns that work across devices/speeds, eliminating CI timing differences

2. "My tests use sleep(2) and sleep(5) but they're still flaky. How do I replace arbitrary timeouts with real conditions?"

→ The skill demonstrates waitForExistence, XCTestExpectation, and polling patterns for data loads, network requests, and animations

3. "I just recorded a test using Xcode 26's Recording UI Automation. How do I review the video and debug failures?"

→ The skill covers Video Debugging workflows to analyze recordings and find the exact step where tests fail

4. "My test is failing on iPad but passing on iPhone. How do I write tests that work across all device sizes?"

→ The skill explains multi-factor testing strategies and device-independent predicates for robust cross-device testing

5. "I want to write tests that are not flaky. What are the critical patterns I need to know?"

→ The skill provides condition-based waiting templates, accessibility-first patterns, and the decision tree for reliable test architecture


Red Flags — Test Reliability Issues

If you see ANY of these, suspect timing issues:

  • Tests pass locally, fail in CI (timing differences)
  • Tests sometimes pass, sometimes fail (race conditions)
  • Tests use sleep() or Thread.sleep() (arbitrary delays)
  • Tests fail with "UI element not found" then pass on retry
  • Long test runs (waiting for worst-case scenarios)

Quick Decision Tree

Test failing?
├─ Element not found?
│  └─ Use waitForExistence(timeout:) not sleep()
├─ Passes locally, fails CI?
│  └─ Replace sleep() with condition polling
├─ Animation causing issues?
│  └─ Wait for animation completion, don't disable
└─ Network request timing?
   └─ Use XCTestExpectation or waitForExistence

Core Pattern: Condition-Based Waiting

❌ WRONG (Arbitrary Timeout):

func testButtonAppears() {
    app.buttons["Login"].tap()
    sleep(2)  // ❌ Guessing it takes 2 seconds
    XCTAssertTrue(app.buttons["Dashboard"].exists)
}

✅ CORRECT (Wait for Condition):

func testButtonAppears() {
    app.buttons["Login"].tap()
    let dashboard = app.buttons["Dashboard"]
    XCTAssertTrue(dashboard.waitForExistence(timeout: 5))
}

Common UI Testing Patterns

Pattern 1: Waiting for Elements

// Wait for element to appear
func waitForElement(_ element: XCUIElement, timeout: TimeInterval = 5) -> Bool {
    return element.waitForExistence(timeout: timeout)
}

// Usage
XCTAssertTrue(waitForElement(app.buttons["Submit"]))

Pattern 2: Waiting for Element to Disappear

func waitForElementToDisappear(_ element: XCUIElement, timeout: TimeInterval = 5) -> Bool {
    let predicate = NSPredicate(format: "exists == false")
    let expectation = XCTNSPredicateExpectation(predicate: predicate, object: element)
    let result = XCTWaiter().wait(for: [expectation], timeout: timeout)
    return result == .completed
}

// Usage
XCTAssertTrue(waitForElementToDisappear(app.activityIndicators["Loading"]))

Pattern 3: Waiting for Specific State

func waitForButton(_ button: XCUIElement, toBeEnabled enabled: Bool, timeout: TimeInterval = 5) -> Bool {
    let predicate = NSPredicate(format: "isEnabled == %@", NSNumber(value: enabled))
    let expectation = XCTNSPredicateExpectation(predicate: predicate, object: button)
    let result = XCTWaiter().wait(for: [expectation], timeout: timeout)
    return result == .completed
}

// Usage
let submitButton = app.buttons["Submit"]
XCTAssertTrue(waitForButton(submitButton, toBeEnabled: true))
submitButton.tap()

Pattern 4: Accessibility Identifiers

Set in app:

Button("Submit") {
    // action
}
.accessibilityIdentifier("submitButton")

Use in tests:

func testSubmitButton() {
    let submitButton = app.buttons["submitButton"]  // Uses identifier, not label
    XCTAssertTrue(submitButton.waitForExistence(timeout: 5))
    submitButton.tap()
}

Why: Accessibility identifiers don't change with localization, remain stable across UI updates.

Pattern 5: Network Request Delays

func testDataLoads() {
    app.buttons["Refresh"].tap()

    // Wait for loading indicator to disappear
    let loadingIndicator = app.activityIndicators["Loading"]
    XCTAssertTrue(waitForElementToDisappear(loadingIndicator, timeout: 10))

    // Now verify data loaded
    XCTAssertTrue(app.cells.count > 0)
}

Pattern 6: Animation Handling

func testAnimatedTransition() {
    app.buttons["Next"].tap()

    // Wait for destination view to appear
    let destinationView = app.otherElements["DestinationView"]
    XCTAssertTrue(destinationView.waitForExistence(timeout: 2))

    // Optional: Wait a bit more for animation to settle
    // Only if absolutely necessary
    RunLoop.current.run(until: Date(timeIntervalSinceNow: 0.3))
}

Testing Checklist

Before Writing Tests

  • Use accessibility identifiers for all interactive elements
  • Avoid hardcoded labels (use identifiers instead)
  • Plan for network delays and animations
  • Choose appropriate timeouts (2s UI, 10s network)

When Writing Tests

  • Use waitForExistence() not sleep()
  • Use predicates for complex conditions
  • Test both success and failure paths
  • Make tests independent (can run in any order)

After Writing Tests

  • Run tests 10
how to use axiom-ui-testing

How to use axiom-ui-testing 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 axiom-ui-testing
2

Execute installation command

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

$npx skills add https://github.com/charleswiltgen/axiom --skill axiom-ui-testing

The skills CLI fetches axiom-ui-testing from GitHub repository charleswiltgen/axiom 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/axiom-ui-testing

Reload or restart Cursor to activate axiom-ui-testing. Access the skill through slash commands (e.g., /axiom-ui-testing) 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.

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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)
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general reviews

Ratings

4.545 reviews
  • Sophia Martinez· Dec 24, 2024

    axiom-ui-testing reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Dhruvi Jain· Dec 20, 2024

    Solid pick for teams standardizing on skills: axiom-ui-testing is focused, and the summary matches what you get after install.

  • Xiao Martinez· Dec 12, 2024

    Registry listing for axiom-ui-testing matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Xiao Desai· Dec 12, 2024

    I recommend axiom-ui-testing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Noor Sanchez· Dec 4, 2024

    Keeps context tight: axiom-ui-testing is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Hassan Ndlovu· Nov 15, 2024

    I recommend axiom-ui-testing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Oshnikdeep· Nov 11, 2024

    We added axiom-ui-testing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Xiao Ghosh· Nov 3, 2024

    Useful defaults in axiom-ui-testing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • William Chawla· Nov 3, 2024

    axiom-ui-testing reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Charlotte Flores· Oct 22, 2024

    I recommend axiom-ui-testing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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