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.
npx agentmods add skills/skydoves/android-testing-skills/testing-animations-deterministicallynpx skills add skydoves/android-testing-skills --skill testing-animations-deterministicallygit clone --depth 1 https://github.com/skydoves/android-testing-skillsWrote 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.
[](https://agentmods.dev/skills/skydoves/android-testing-skills/testing-animations-deterministically)<a href="https://agentmods.dev/skills/skydoves/android-testing-skills/testing-animations-deterministically"><img src="https://agentmods.dev/badge/skills/skydoves/android-testing-skills/testing-animations-deterministically.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00156 | $0.04177 |
| Opus 5 | $0.00078 | $0.02089 |
| Sonnet 5 | $0.00031 | $0.00835 |
| Haiku 4.5 | $0.00016 | $0.00418 |
Grade A, and why
testing-animations-deterministically 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Testing Animations Deterministically — autoAdvance = false Or Bust
A Compose animation test that does not pause the clock is by definition flaky. With mainClock.autoAdvance = true (the default), the framework's InfiniteAnimationPolicy throws CancellationException as soon as an indeterminate animation starts, and finite animations finish in a single auto-advanced burst with no observable intermediate state. This skill teaches the five-line recipe that fixes that, plus the runOnUiThread-vs-runOnIdle gotcha that bites every developer who tries it for the first time.
When to use this skill
- The test asserts an intermediate frame of an animation (mid-fade alpha, mid-scroll offset, mid-Crossfade dispose).
- The composable contains an indeterminate animation (
LinearProgressIndicator()with no progress argument,rememberInfiniteTransition, loopingwithFrameMillis). - The developer reports
CancellationException("Infinite animations are disabled on tests")and asks how to make it stop. - The developer reaches for
Thread.sleep(500)to "wait for the animation". - The developer's animation test passes locally and fails on CI, or vice versa.
- The developer mentions
autoAdvance,advanceTimeByFrame,advanceTimeBy,Crossfade, "flaky animation test", orInfiniteAnimationPolicy.
When NOT to use this skill
- The animation is a side effect; the test only cares about the final state. Default
autoAdvance = trueis faster — see../synchronizing-with-idle/SKILL.md. - The clock semantics themselves are unclear (frame model, rounding rules, v1 vs v2 dispatcher). Read
../controlling-the-test-clock/SKILL.mdfirst. - The condition under test is not Compose state (a
Job.isCompleted, aMockito.verify). UsewaitUntilor anIdlingResourcefrom../synchronizing-with-idle/SKILL.md. - The test uses screenshot comparison waiting on the RenderThread for ripple/elevation pixels. That is the one legitimate
Thread.sleepsite (skydoves hot take #7).
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.
- 6d ago First seen · 302 lines · 156 tokens per session scan A 1105b7a1cdd8
testing-animations-deterministically is a skill published in the GitHub repository skydoves/android-testing-skills (318 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 156 tokens to every session and 4,177 once invoked, about $0.0008 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.
Other skills, from other repositories
android-ui-journey-testing
XML-specified Android UI journey testing, interactive step execution, assertion verification, and JSON outcome reporting.
android_ui_verification
Automated end-to-end UI testing and verification on an Android Emulator using ADB.
test-t3-mobile
Launch and test T3 Code Mobile on an iOS Simulator or Android Emulator against disposable local T3 environments, including Metro and dev-client reuse, native rebuild decisions, per-client pairing, seeded projects, semantic UI control, screenshots, and iOS serve-sim streaming. Use after mobile UI or native changes…
run-integration-tests
Build, pack, and run .NET MAUI integration tests locally. Validates templates, samples, and end-to-end scenarios using the local workload.
agent-device-evidence
Records iOS/Android native MP4 evidence for test/repro flows extracted from an Expensify GitHub PR or issue. Use when the user asks to "record the flow for PR.
solopi-ai
通过 SoloPi 的机器可读 CLI 编译和执行 AI 验证计划,管理签名端侧 ExecuTorch 决策模型、持久设备池、无人值守任务、安卓设备、应用、动作、配置、用例步骤与交互录制、回放及性能历史、动态 Agent、批量与重复执行、性能监控、压力测试和证据。适用于需求/AC 到 Result Judge 三态结论、cloud/on-device 决策切换、模型发布门禁,以及 generation 租约的多设备 CI 执行。.