What is mobile-qa-expert?

A set of instructions for testing mobile apps on emulators, physical devices, and cloud device services. It covers Appium, Maestro, AWS Device Farm, BrowserStack, and common Android and iOS testing obstacles.

Use it to build or extend Appium or Maestro tests, run tests on AWS Device Farm or BrowserStack, automate login and OTP flows, debug taps in React Native or Flutter apps, and collect screenshots or screen-structure evidence.

It helps find why a mobile test passes in an emulator but fails on a real device, including timing, device security checks, certificate pinning, screen differences, and login barriers.

mobile-qa-expert — Skill for Claude Code by Aarvion-AI

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add Aarvion-AI/stackwise-skills --skill mobile-qa-expert

Clone the repo

git clone --depth 1 https://github.com/Aarvion-AI/stackwise-skills

Made for: Claude Code.

Or install stackwise, the plugin that ships this one along with the rest of its 15 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/aarvion-ai/stackwise-skills/mobile-qa-expert/github.svg)](https://agentmods.dev/skills/aarvion-ai/stackwise-skills/mobile-qa-expert)

Your own site

<a href="https://agentmods.dev/skills/aarvion-ai/stackwise-skills/mobile-qa-expert"><img src="https://agentmods.dev/badge/skills/aarvion-ai/stackwise-skills/mobile-qa-expert/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/aarvion-ai/stackwise-skills/mobile-qa-expert"><img src="https://agentmods.dev/badge/skills/aarvion-ai/stackwise-skills/mobile-qa-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 133 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,055 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00133	$0.02055
Opus 5	$0.00067	$0.01027
Sonnet 5	$0.00027	$0.00411
Haiku 4.5	$0.00013	$0.00205

Measured 9d ago against content hash 5b85f2b2af36, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

mobile-qa-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/mobile-qa-expert/SKILL.md · 99 lines

How it starts

The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Mobile QA Expert

Turns Claude into a senior mobile automation engineer who ships suites that pass on real cloud devices, not just on the emulator that wrote them.

When to Use This Skill

Write or extend an Appium 2.x suite (UiAutomator2 or XCUITest) for an Android/iOS app
Run an existing suite on AWS Device Farm or BrowserStack App Automate as a release gate
Automate a login/OTP-gated flow so it runs unattended in CI
Fix taps that silently do nothing on React Native / Flutter screens
Add fast Maestro YAML smoke flows alongside a heavier Appium suite
Diagnose tests that pass on emulator but fail on real devices (attestation, pinning, timing, resolution)
Capture screenshot + view-hierarchy evidence bundles for QA review

Core Workflow

Analyze the app and constraints - Identify the build type (debug vs prod), UI framework (native, React Native, Flutter - determines locator strategy), and blockers: Play Integrity / attestation and cert pinning mean prod builds only run on real, non-rooted devices, and the network layer stays pinned-blind (verify via screenshots/OCR, not proxying). Check for existing testID/accessibility labels; request them from the app team before resorting to coordinates.
Set up local Appium 2.x - Install [email protected] plus the driver (appium driver install uiautomator2 / xcuitest) at a version compatible with your Appium major. Start with --base-path / and match the client path. Write W3C capabilities (appium: prefixed). Verify: start the server, run appium driver list --installed, and open one session against the emulator; fix all reported issues and re-run until clean.
Develop the suite emulator-first - Build flows on a local emulator for speed. Prefer accessibility-id and testID locators; for opaque RN/Flutter trees use the page-source → bounds → mobile: clickGesture pattern (see references/opaque-ui-strategies.md). After every asserted state, save screenshot + page-source XML as the evidence bundle. Verify: run the suite locally; fix all reported issues and re-run until clean (zero failures, evidence artifacts present).
Automate auth unattended - Log in once per suite via email OTP over IMAP with a dedicated test account; secrets come from env/secret store, never hardcoded. Exploit session persistence: terminate/relaunch keeps the session, clearing app data does not. Verify: run the full suite twice back-to-back with no human input; fix all reported issues and re-run until clean.
Promote to real-device cloud - Package for Device Farm (custom environment testspec - remember to shadow the preinstalled Appium 1.x) or BrowserStack App Automate. Pin device models for any coordinate-dependent steps. Verify: run on the cloud device pool; triage every failure as app bug vs environment gap (attestation, resolution, timing), fix all reported issues and re-run until clean.
Add Maestro smoke layer + flake hardening - Encode the 3-5 critical paths as Maestro YAML flows for fast PR-level checks; keep Appium as the deep release gate. Add explicit waits (never bare sleeps), retries with evidence on retry, and quarantine rules. Verify: run smoke + full suite 3 consecutive times on the release device pool; fix all reported issues and re-run until clean, then wire both into CI.

Read the full file on GitHub · 99 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

9d ago First seen · 99 lines · 133 tokens per session scan A 5b85f2b2af36

Subscribe to this mod's changes

mobile-qa-expert is a skill published in the GitHub repository Aarvion-AI/stackwise-skills (5 stars, last pushed 6d ago), licensed MIT. It adds 133 tokens to every session and 2,055 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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