qa-testing-mobile

vasilyu1983/ai-agents-public · updated Apr 8, 2026

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$npx skills add https://github.com/vasilyu1983/ai-agents-public --skill qa-testing-mobile
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summary

Design and execute reliable, cost-aware mobile testing across iOS and Android (native + cross-platform).

skill.md

QA Mobile Testing

Design and execute reliable, cost-aware mobile testing across iOS and Android (native + cross-platform).

Quick Start

  • Fill assets/mobile-test-plan.md to define risk, layers, and gates.
  • Fill assets/device-matrix.md from analytics to pick Tier 1/2/3 coverage.
  • Use references/framework-comparison.md to choose automation frameworks.
  • Use references/flake-management.md to set a flake budget, reruns, and quarantine rules.

Scope

  • Define mobile test strategy across iOS and Android.
  • Plan device matrix, OS coverage, and risk tiers.
  • Choose automation frameworks and CI + device lab setup.
  • Address performance, network/offline, backgrounding, and permissions.
  • Define pre-release gates, staged rollout, and store readiness checks.

When NOT to Use

Inputs

  • Platforms, supported OS versions, and device targets.
  • App type (native, cross-platform, hybrid/webview).
  • Critical user flows and risk areas.
  • Distribution channels and release cadence.
  • Existing test tooling, CI, and device lab access (Firebase Test Lab, BrowserStack, AWS Device Farm).
  • Observability and rollout controls (Crashlytics/Sentry, performance/RUM, feature flags, staged rollout).
  • Test data strategy (seed/reset, test accounts, environment parity).

Workflow

  1. Define quality risks and SLIs (crash-free, ANR, startup time, key flow success).
  2. Build a device matrix from analytics; keep PR gates emulator/simulator-first.
  3. Choose frameworks (default: XCUITest + Espresso/Compose; add cross-platform only when it reduces total cost).
  4. Build test layers: unit, integration/contract, UI smoke, targeted E2E on real devices.
  5. Add mobile-specific coverage: permissions, background/foreground, deep links, offline/poor network.
  6. Add performance checks (startup, scrolling/jank, memory) and accessibility checks.
  7. Set flake budget, rerun limits, quarantine policy, and failure triage (artifacts + reproducibility).
  8. Define release gates + store readiness; ship via staged rollout with monitoring + rollback.

Outputs

  • Mobile test strategy and device matrix.
  • Automation plan and framework selection.
  • Test case inventory with priorities.
  • Release readiness checklist.
  • CI pipeline and reporting plan.

Quality Checks

  • Keep UI tests focused on critical flows; keep suites small and fast.
  • Separate device specific bugs from logic regressions.
  • Track flake rate per test/device; quarantine and fix top offenders.
  • Verify permissions, notifications, and background behavior.
  • Prefer stable selectors (accessibility IDs/test tags), not localized text.

Templates

  • assets/device-matrix.md for OS and device coverage.
  • assets/mobile-test-plan.md for test scope and automation.
  • assets/release-readiness-checklist.md for release gates.

Resources

  • references/framework-comparison.md for choosing between XCUITest, Espresso/Compose, Appium, Detox, Maestro, and Flutter testing.
  • references/flake-management.md for flake control guidance.
  • references/device-farm-strategies.md for cloud device farm selection and cost optimization.
  • references/mobile-performance-testing.md for startup, jank, memory, and battery testing.
  • references/cross-platform-test-patterns.md for React Native, Flutter, and KMP testing patterns.
  • data/sources.json for curated documentation and device lab links.

Related Skills

Fact-Checking

  • Use web search/web fetch to verify current external facts, versions, pricing, deadlines, regulations, or platform behavior before final answers.
  • Prefer primary sources; report source links and dates for volatile information.
  • If web access is unavailable, state the limitation and mark guidance as unverified.
how to use qa-testing-mobile

How to use qa-testing-mobile 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 qa-testing-mobile
2

Execute installation command

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

$npx skills add https://github.com/vasilyu1983/ai-agents-public --skill qa-testing-mobile

The skills CLI fetches qa-testing-mobile from GitHub repository vasilyu1983/ai-agents-public 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/qa-testing-mobile

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

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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)
  • No comments yet — start the thread.
general reviews

Ratings

4.627 reviews
  • Henry Khan· Dec 8, 2024

    qa-testing-mobile fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Chaitanya Patil· Dec 4, 2024

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

  • Piyush G· Nov 23, 2024

    qa-testing-mobile has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Henry Martinez· Oct 18, 2024

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

  • Shikha Mishra· Oct 14, 2024

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

  • Rahul Santra· Sep 25, 2024

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

  • Carlos Patel· Sep 21, 2024

    qa-testing-mobile fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Arjun Abebe· Sep 9, 2024

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

  • Jin Perez· Sep 1, 2024

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

  • Jin Srinivasan· Aug 28, 2024

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

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