{"id":47037459,"title":"Show HN: DroidClaw – Turn old Android phones into AI agents","points":1,"user":"spikey_sanju","time":1771261520,"time_ago":"6 hours ago","type":"link","content":"

Hey all, I built an open-source tool that lets you give an Android phone a goal in plain English. It reads the accessibility tree, sends the UI state to an LLM, executes actions via ADB, and loops until the task is done.

The core loop: dump accessibility tree via uiautomator → parse and filter to ~40 relevant elements → LLM returns {think, plan, action} → execute via ADB → repeat.

Some technical decisions worth noting:

- Primary input is the accessibility tree, not vision. Vision (screenshots + multimodal model) is only a fallback for when the tree is empty (WebViews, Flutter).

- Stuck detection: if the screen state doesn't change for 3 steps, recovery kicks in with back navigation, home, or app re-launch.

- Two execution modes: AI-powered workflows (JSON, LLM decides navigation) and deterministic flows (YAML, fixed sequences, no LLM calls).

- ADB over WiFi + Tailscale for remote control. The phone becomes an always-on agent you can trigger from anywhere.

- Supports Groq (free tier), OpenAI, OpenRouter, Bedrock. Ollama support just landed for fully local inference.

- One-line install: curl -fsSL https://droidclaw.ai/install.sh | sh

Built with Bun + TypeScript. 35 example workflows included covering messaging, social, productivity, research, and lifestyle tasks.

https://github.com/unitedbyai/droidclaw\nhttps://droidclaw.ai","url":"https://droidclaw.ai","domain":"droidclaw.ai","comments":[],"comments_count":0}