by memohai · Agent Tool · ★ 108
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Autofish English | 中文 Android control infrastructure for agents and multi-agent systems. Autofish gives any agent a stable, explicit, and observable Android execution layer: inspect the screen, act through stable refs instead of brittle coordinates, verify outcomes after every step, and recover with local execution memory. How It Works Autofish has two components: Android Service — A foreground service running on the device, exposing an HTTP API. It handles screenshots, UI tree inspection, tap/swipe/text input execution, and on-screen overlay annotations. CLI () — A Rust binary that talks to the service over HTTP. It provides the command interface, manages local tool memory (SQLite), and handles artifact storage. Distributed via npm (). Install and Connect Install Autofish from npm: Install the matching official Autofish Android app through the CLI: Then open Autofish on the Android device: Enable the Autofish accessibility service. Enable Shizuku support when available. Turn on Service from the Autofish home page. Copy the commands or raw / / from the home page connection card
| Stars | 108 |
| Forks | 10 |
| Language | Rust |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 74.6008549961917/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-28 |
| Created | 2026-03-13 |
| Platforms | rust |
| Est. Tokens | ~1054k |
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Autofish is An AI Agent tool to automate Android devices reliably. It is categorized as a Agent Tool with 108 GitHub stars.
Autofish is primarily written in Rust. It covers topics such as ai-agent, android, android-automation.
You can find installation instructions and usage details in the Autofish GitHub repository at github.com/memohai/Autofish. The project has 108 stars and 10 forks, indicating an active community.
Autofish is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to Autofish on Agent Skills Hub include OpenGUI, compose-skill, mobileClaw. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.