espresso-skill

espresso-skill is a skill for Claude Code, Codex from LambdaTest/agent-skills. It costs 96 tokens per session (1,968 once invoked), scanned A, original, MIT.

A generator for Espresso UI tests for Android apps in Kotlin or Java. Espresso runs tests inside the app process to check screens and user interactions.

In plain words
What is it for?
Use it to write tests for fields, buttons, messages, and screen transitions, then run them on a local emulator, connected device, or TestMu AI cloud device.
Why use it?
It provides a repeatable way to verify Android interfaces without manually tapping through every flow.

Skill for Claude CodeCodex

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

Good fit Use it to write tests for fields, buttons, messages, and screen transitions, then run them on a local emulator, connected device, or TestMu AI cloud device.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lambdatest/agent-skills/espresso-skill
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 LambdaTest/agent-skills --skill espresso-skill
Clone the repo
git clone --depth 1 https://github.com/LambdaTest/agent-skills

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 espresso-skill

README.md
[![agentmods](https://agentmods.dev/badge/skills/lambdatest/agent-skills/espresso-skill/github.svg)](https://agentmods.dev/skills/lambdatest/agent-skills/espresso-skill)
Your own site
<a href="https://agentmods.dev/skills/lambdatest/agent-skills/espresso-skill"><img src="https://agentmods.dev/badge/skills/lambdatest/agent-skills/espresso-skill/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.

agentmods 80×15 button for espresso-skill

Your own site · 80×15
<a href="https://agentmods.dev/skills/lambdatest/agent-skills/espresso-skill"><img src="https://agentmods.dev/badge/skills/lambdatest/agent-skills/espresso-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 96 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,968 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Data Exfiltration · line 185
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
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 $0.00096 $0.01968
Opus 5 $0.00048 $0.00984
Sonnet 5 $0.00019 $0.00394
Haiku 4.5 $0.00010 $0.00197

Measured 10d ago against content hash 460208377da2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

espresso-skill scanned grade A with 1 finding 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 10d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -u "$LT_USERNAME:$LT_ACCESS_KEY" \
espresso-skill/SKILL.md · 259 lines

How it starts

The opening of the file, as written. The whole thing — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Espresso Automation Skill

You are a senior Android QA engineer specializing in Espresso UI testing.

Step 1 — Execution Target

├─ Mentions "cloud", "TestMu", "LambdaTest", "device farm"?
│  └─ TestMu AI cloud (upload APK + test APK)
│
├─ Mentions "emulator", "local", "connected device"?
│  └─ Local: ./gradlew connectedAndroidTest
│
└─ Default → Local emulator

Core Patterns — Kotlin (Default)

Basic Test

@RunWith(AndroidJUnit4::class)
class LoginTest {

    @get:Rule
    val activityRule = ActivityScenarioRule(LoginActivity::class.java)

    @Test
    fun loginWithValidCredentials() {
        // Type email
        onView(withId(R.id.emailInput))
            .perform(typeText("[email protected]"), closeSoftKeyboard())

        // Type password
        onView(withId(R.id.passwordInput))
            .perform(typeText("password123"), closeSoftKeyboard())

        // Click login button
        onView(withId(R.id.loginButton))
            .perform(click())

        // Verify dashboard is displayed
        onView(withId(R.id.dashboardTitle))
            .check(matches(isDisplayed()))
            .check(matches(withText("Welcome")))
    }

    @Test
    fun loginWithInvalidCredentials_showsError() {
        onView(withId(R.id.emailInput))
            .perform(typeText("[email protected]"), closeSoftKeyboard())
        onView(withId(R.id.passwordInput))
            .perform(typeText("wrong"), closeSoftKeyboard())
        onView(withId(R.id.loginButton))
            .perform(click())
        onView(withId(R.id.errorText))
            .check(matches(isDisplayed()))
            .check(matches(withText(containsString("Invalid"))))
    }
}

ViewMatchers (Finding Elements)

// By ID (best)
onView(withId(R.id.loginButton))

// By text
onView(withText("Login"))

// By content description (accessibility)
onView(withContentDescription("Submit form"))

// By hint text
onView(withHint("Enter your email"))

// Combined matchers
onView(allOf(withId(R.id.button), withText("Submit"), isDisplayed()))

// In RecyclerView
onView(withId(R.id.recyclerView))
    .perform(RecyclerViewActions.actionOnItemAtPosition<ViewHolder>(0, click()))

// By parent
onView(allOf(withText("Delete"), isDescendantOfA(withId(R.id.toolbar))))

Read the full file on GitHub · 259 lines

Files

What ships with it

3 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.

  1. 10d ago First seen · 259 lines · 96 tokens per session scan A 460208377da2

Subscribe to this mod's changes

espresso-skill is a skill published in the GitHub repository LambdaTest/agent-skills (366 stars, last pushed 1mo ago), licensed MIT. It adds 96 tokens to every session and 1,968 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

solopi-ai

A command-line framework for testing Android apps and devices with SoloPi, including on-device or cloud AI decision models. It manages devices, test cases, recorded interactions, replays, performance history, and evidence.

alipay/SoloPi · 127 tokens

mobile-tester

You are the Mobile Tester Specialist. You connect to real Android/iOS devices and write, execute, and report on mobile UI test cases. You master THREE testing modalities.

buiphucminhtam/forgewright · 81 tokens

device-farms

Expert guidance on running mobile tests on Firebase Test Lab, AWS Device Farm, BrowserStack App Automate, and Sauce Labs. Use when asked to set up device-farm coverage, design a device matrix, or compare vendors.

almasumdev/awesome-mobile-testing-agent-skills · 49 tokens

maestro-flows

Expert guidance on writing, running, and parallelizing Maestro YAML flows for cross-platform mobile E2E testing. Use when adding Maestro coverage, wiring Maestro to CI, or moving off Detox/Appium for smoke flows.

almasumdev/awesome-mobile-testing-agent-skills · 48 tokens

ui-testing-patterns

Compare and apply UI test tooling across mobile — Espresso, XCUITest, fluttertest / integrationtest, Detox, and Maestro. Use when deciding which UI test layer fits a feature and how to structure selectors, waits, and page objects.

almasumdev/awesome-mobile-testing-agent-skills · 53 tokens

android-ui-journey-testing

XML-specified Android UI journey testing, interactive step execution, assertion verification, and JSON outcome reporting.

sickn33/agentic-awesome-skills · 27 tokens