android_unit_testing_bdd

Guidelines for unit tests written in BDD style, where each test describes a behavior using Given, When, and Then steps.

In plain words
What is it for?
Use them when testing Kotlin code, including suspend functions, repositories, and other components with mocked dependencies.
Why use it?
They make tests easier to understand and help keep each test focused on one expected behavior without depending on real time, randomness, or external services.

Cursor rule for Cursor

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.

agentmods
npx agentmods add rules/nphausg/ai-agent-skills/android_unit_testing_bdd
Clone the repo
git clone --depth 1 https://github.com/nphausg/ai-agent-skills

Made for: Cursor.

Per session 8 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 186 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00008 $0.00186
Opus 5 $0.00004 $0.00093
Sonnet 5 $0.00002 $0.00037
Haiku 4.5 $0.00001 $0.00019

Measured yesterday against content hash 6b37a4b4904c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

android_unit_testing_bdd 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 yesterday.

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.

.cursor/rules/android/android_unit_testing_bdd.mdc · 25 lines

What it actually says

  • Name test functions in BDD style: given_whenthen
  • Use GIVEN, WHEN, THEN comments in the test body for clarity.
  • Write one behavioral scenario per test.
  • Use mocks (MockK, Mockito) to isolate dependencies.
  • Prefer runTest or coroutine test rules for suspend functions.
  • Avoid fragile tests with real-time delays or random input.
  • Example:
@Test
fun givenValidUser_whenFetchUser_thenReturnsUser() {
    // GIVEN
    val userId = 123
    coEvery { userRepo.getUser(userId) } returns User(userId, "Alice")

    // WHEN
    val result = runBlocking { sut.fetchUser(userId) }

    // THEN
    assertEquals("Alice", result.name)
}
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. yesterday First seen · 25 lines · 8 tokens per session scan A 6b37a4b4904c

Subscribe to this mod's changes

android_unit_testing_bdd is a cursor rule published in the GitHub repository nphausg/ai-agent-skills (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 8 tokens to every session and 186 once invoked, about $0.0000 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.