argent-test-ui-flow

argent-test-ui-flow is a skill for Claude Code, Codex from software-mansion/argent. It costs 64 tokens per session (2,523 once invoked), scanned A, original, Apache-2.0.

A workflow for testing an iOS or Android app by performing actions, taking screenshots, and checking the results on a simulator or emulator.

In plain words
What is it for?
Use it for end-to-end UI tests, manual quality checks, navigation tests, login checks, and verifying changes to the app's screens.
Why use it?
It provides a repeatable way to verify that screens, navigation, login, and other visible app behavior work as expected.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for end-to-end UI tests, manual quality checks, navigation tests, login…

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Install with agentmods
npx agentmods add skills/software-mansion/argent/argent-test-ui-flow
About the project

Argent is a toolkit that lets an AI assistant control and inspect iOS, Android, TV, Electron, and Chromium applications through simulators, emulators, physical devices, or desktop connections. It is for developers who want an agent to interact with interfaces, reproduce issues, test features, debug applications, or run profiling tasks. The catalogue add-ons expose Argent's device-control and development workflows to coding agents.

software-mansion/argent · 2,387 stars · on GitHub · argent.swmansion.com

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 software-mansion/argent --skill argent-test-ui-flow
Clone the repo
git clone --depth 1 https://github.com/software-mansion/argent

Made for: Claude Code, Codex.

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.

agentmods badge for argent-test-ui-flow

README.md
[![agentmods](https://agentmods.dev/badge/skills/software-mansion/argent/argent-test-ui-flow.svg)](https://agentmods.dev/skills/software-mansion/argent/argent-test-ui-flow)
Your own site
<a href="https://agentmods.dev/skills/software-mansion/argent/argent-test-ui-flow"><img src="https://agentmods.dev/badge/skills/software-mansion/argent/argent-test-ui-flow.svg" alt="Measured on agentmods" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,523 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00064 $0.02523
Opus 5 $0.00032 $0.01262
Sonnet 5 $0.00013 $0.00505
Haiku 4.5 $0.00006 $0.00252

Measured 3d ago against content hash 8e8aa74944a8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

argent-test-ui-flow 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 3d 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.

packages/skills/skills/argent-test-ui-flow/SKILL.md · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Platform-agnostic

Physical iPhone (kind: "device"): read argent-ios-device-interact first. launch-app before anything; describe fails while the app is backgrounded.

The interaction tool names are identical on iOS and Android — gesture-tap, gesture-swipe, describe, screenshot, launch-app, etc. — and the tool-server auto-dispatches based on the udid you pass (UUID-shape → iOS, adb serial → Android).

Before testing, resolve which device to test on. Call list-devices and follow <device_selection_rule>: prefer a running device on any platform;

Once a platform is chosen, the per-platform setup skill takes over:

Platform Setup skill Find devices with
iOS argent-ios-simulator-setup list-devicesboot-device with udid if none booted
Android argent-android-emulator-setup list-devicesboot-device with avdName if none ready

1. Workflow

All interactions go through argent MCP tools. Ensure the simulator/emulator is ready before starting.

For implementation tasks that modify visible UI, this workflow can also serve as a visual acceptance path.

  1. Baseline screenshot: Call screenshot to see the current UI state. For visual regression comparison or UI change verification, capture the baseline at scale: 1.0 with includeImageInContext: false and keep the returned path before editing whenever feasible.
  2. Find target: Before tapping, use a discovery tool to get element coordinates:
    • React Native apps: use debugger-component-tree — it returns component names with (tap: x,y) coordinates. This is the preferred tool for RN apps on either platform. To use it, resolve the argent-react-native-app-workflow skill for setup; on Android you must also run adb -s <serial> reverse tcp:8081 tcp:8081 so Metro is reachable from the device.
    • Standard app screens and in-app modals: use describe. On iOS this returns the AX tree (falls back to native-devtools when AX is empty); on Android it returns the uiautomator tree in the same DescribeNode shape.
    • Permission prompts / system modal overlays: try describe first. Fall back to screenshot only if the overlay is not exposed reliably. When the app raises its own permission dialog, answer it here — that's the real flow under test. To take a prompt out of the flow (pre-grant/deny before launch, re-enable a permission the user already denied, or reset it so the dialog reappears), use the argent-settings-permissions skill during setup instead of interacting with the dialog.
    • Fallback: use screenshot to estimate where the desired component is, then verify immediately after the action.
  3. Interact: Perform the action (gesture-tap, gesture-swipe, keyboard, button, ...) — you receive a screenshot automatically.
  4. Verify: Check the returned screenshot for expected results. If it shows a loading/transitional state, prefer blocking until it settles with await-ui-element (expected element visible, or a spinner hidden) over a guessed delay — but only with a selector you can trust (text/identifier/role) that the screen is known to have or that you saw in a prior describe; a guessed one just times out. Otherwise use a short fixed wait. Pick evidence by what's being asserted:
    • Visual (layout, spacing, color, typography, image/icon rendering, clipping, overflow, text rendering): prefer screenshot-diff against the baseline captured in step 1 — it surfaces pixel-visible changes the auto-screenshot might miss. Fall back to visual inspection of the auto-screenshot only when a stable baseline isn't available.
    • Structural (navigation state, element existence, accessibility labels/values, selection, hierarchy, route): verify with describe, debugger-component-tree, or native-describe-screen.
    • Runtime / log / network (console errors, API calls, persistence, timing): verify with view-network-logs, debugger-log-registry, debugger-evaluate, or targeted tests. Note debugger-log-registry returns { status: "not_connected", reason, guidance } with no log file when the debugger is unreachable — that is not evidence about the app; follow its guidance to reconnect, then re-verify.
    • Mixed: collect evidence for each relevant class.
    • Report the combined verdict: expected behavior, observed behavior, evidence used, and any blocker for requested visual diffing.
  5. Repeat for each step in the flow.

Read the full file on GitHub · 134 lines

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.

  1. 3d ago Changed · +2 lines 8e8aa74944a8
  2. 7d ago First seen · 132 lines · 64 tokens per session scan A fa567be2bc9c

Subscribe to this mod's changes

argent-test-ui-flow is a skill published in the GitHub repository software-mansion/argent (2,387 stars, last pushed 2d ago), licensed Apache-2.0. It adds 64 tokens to every session and 2,523 once invoked, about $0.0003 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 2026-08-30.