agentleFS
amit-nayaramit-nayar/android-adb-skill/.cursor/rules/android-adb.mdc

android-adb-skill / rules

Cursor rule29 starsChanged 8 months agoMITView on GitHub

Android device automation via ADB — screenshots, UI inspection, gestures, app management, debugging

The file

We split this android-adb.mdc into the rules it gives an agent

4 rules. About 0 are common, 1 is distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Prefer the local command layer:

    line 9
  2. Very specific:

    Read docs/command-contract.md for the command surface and skills/*/SKILL.md for task-specific workflows.

    line 15
  3. Very specific:

    Prefer ./tools/android ...

    line 19
  4. Very specific:

    Verify state after interactions with ui dump, wait element, or screenshot.

    line 21

≈ “Common” is an estimate: at least 1 in 5 of the 6,668 Cursor rule files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
android-adb.mdc
---
description: Android device automation via ADB — screenshots, UI inspection, gestures, app management, debugging
globs: []
alwaysApply: false
---

# Android ADB Automation

Prefer the local command layer:

```bash
./tools/android ...
```

Read `docs/command-contract.md` for the command surface and `skills/*/SKILL.md` for task-specific workflows.

Default behavior:

- Prefer `./tools/android ... --json` over raw `adb`.
- Pass `--device <id>` when the target device is known.
- Verify state after interactions with `ui dump`, `wait element`, or `screenshot`.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.