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/dinglebear-ai/dendrite/android-app-testingnpx skills add dinglebear-ai/dendrite --skill android-app-testinggit clone --depth 1 https://github.com/dinglebear-ai/dendriteWhat 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 | $0.00212 | $0.01678 |
| Opus 5 | $0.00106 | $0.00839 |
| Sonnet 5 | $0.00042 | $0.00336 |
| Haiku 4.5 | $0.00021 | $0.00168 |
Grade A, and why
android-app-testing 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 2d 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.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
6 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.
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.
- 2d ago First seen · 91 lines · 212 tokens per session scan A 70dce4b3f7aa
android-app-testing is a skill published in the GitHub repository dinglebear-ai/dendrite (1 stars, last pushed 6d ago), licensed AGPL-3.0. It adds 212 tokens to every session and 1,678 once invoked, about $0.0011 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.
Other skills, from other repositories
android-device-testing
Use when writing or debugging instrumented tests (Espresso, UI Automator, Compose test rules), using ADB, managing emulators, or inspecting UI with Layout Inspector.
android-e2e-verification
Use when a feature slice needs proof it works end-to-end on a device, or when closing the implement → run → assert loop for any UI-facing change. Maestro YAML flows turn acceptance criteria into executable checks that run against release builds locally, in CI, and via MCP from the agent.
ios-qa
Live-device iOS QA for SwiftUI apps. (gstack).
testing
Testing workflow and quality standards for writing and running tests. Use when: (1) Writing new tests, (2) Adding a new feature that needs tests, (3) Modifying logic that has existing tests, (4) Before claiming a task is complete.
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。.