Developer Uses Claude Code to Build USB Dongle That Auto-Plays Chrome Dino Game
Hardware and Firmware Details
A developer created a USB dongle that automatically plays Chrome's offline Dino game without requiring host-side software or browser extensions. The device uses an ATtiny85 (Digispark) microcontroller with 8KB flash and 512 bytes of RAM, costing approximately $2.
How It Works
The dongle plugs into any PC and appears as a standard USB HID keyboard. It uses two LDR (light-dependent resistor) sensors mounted on the monitor to detect obstacles in the game:
- Lower sensor detects cacti
- Upper sensor detects birds
When obstacles are detected, the device sends appropriate keyboard commands (jump or duck) to control the game character.
Claude Code's Role in Development
The developer used Claude Code as the primary development partner for the firmware, which is written in bare-metal C using avr-gcc (not Arduino). Specific contributions included:
- Writing the V-USB HID keyboard stack integration and report descriptor
- Designing dual-sensor obstacle classification logic through iterative development
- Creating pulse-width envelope measurement for speed-adaptive timing
- Handling the fork-shaped cactus sprite issue (multiple sub-pulses merged via gap threshold)
- Writing the full README, PLAN.md, and Makefile
Technical Implementation
The adaptive timing system addresses the game's acceleration by measuring how long each obstacle takes to pass the sensor, using a rolling minimum filter, and scaling the jump delay accordingly. Codex performed a code review that caught a bug in the envelope tracking logic where sensor polarity was inverted in four places.
The total firmware size is 2699 bytes. Hardware assembly, sensor mounting, LM393 potentiometer calibration, and physical testing were done manually by the developer.
Key Differentiators
- USB HID keyboard implementation requires no host-side Python or browser extensions
- No servo or solenoid pressing the spacebar
- Dual vertically-stacked sensors for obstacle differentiation
- Adaptive timing that remains accurate as game speed increases
📖 Read the full source: r/ClaudeAI
👀 See Also
Case Study: Using Multiple AI Agents to Build a Production C++ Library
A developer documented a multi-month process using four AI agents (Claude, ChatGPT, Gemini, Grok) with distinct roles to build FAT-P, a header-only C++20 library with 107 headers and zero external dependencies. The system included cross-review, governance documents written by AI, and a demerit tracker to encode failure modes.
OpenClaw Agent Tested in Aivilization Persistent World Simulation
A developer experimented by dropping their OpenClaw agent into Aivilization, an open-world simulation where AI agents exist as residents. Instead of terminal workflows, the agent became a character that attended school, read books, farmed, found jobs, earned money, and interacted with other agents.
User Creates HTML Converter for Claude Chat Exports Using Claude Itself
A non-coder used Claude to build a converter that transforms Claude's native JSON chat exports into readable HTML with color-coded messages, collapsible conversations, and organization by date and time.
Building an Autonomous AI Agent System with Claude Code: A Case Study
A developer built Acrid, an AI agent that runs a company called Acrid Automation using Claude Code as its operating system. The system features 14 slash command skills, 4 sub-agents for delegation, file-based memory without vector databases, and an automated content pipeline bridging Claude with n8n via GitHub.