zhinkgit/embeddedskills

An open-source collection of embedded development and debugging skills for Claude Code, Copilot, TRAE, and other AI coding assistants that support the Skill protocol. Once installed, the AI assistant can directly operate compilers, debuggers, and communication buses, automating the full workflow from code generation to hardware verification.

What it solves

Embedded development typically requires a manual, fragmented workflow where a human must bridge the gap between an AI's code generation and the actual hardware. This project provides a set of "skills" that allow AI coding assistants to directly control compilers, debuggers, and communication buses, creating a closed-loop system from code generation to hardware verification.

How it works

The project implements a series of Python scripts that wrap existing command-line tools (such as Keil, GCC, J-Link, and OpenOCD) into structured sub-commands. These capabilities are exposed to AI assistants via SKILL.md files, which describe the functions in natural language. When the AI invokes a skill, the scripts return a unified JSON output containing the status, summary, and suggested next actions, allowing the AI to autonomously decide whether to rebuild, flash, or debug based on the AI's own analysis of the errors.

Who it’s for

Embedded software engineers and developers using AI coding assistants (like Claude Code, Cursor, or Trae) who want to automate the build-flash-debug cycle on physical hardware.

Highlights

  • Closed-loop AI workflow: Automates the cycle of code generation $\rightarrow$ compilation $\rightarrow$ flashing $\rightarrow$ debugging $\rightarrow$ error correction.
  • Toolchain agnostic: Supports Keil MDK, CMake/GCC, and EIDE build systems.
  • Broad hardware support: Compatible with J-Link, CMSIS-DAP, OpenOCD, and probe-rs.
  • Communication monitoring: Includes skills for monitoring UART, CAN/CAN-FD, and Ethernet traffic.
  • Zero-migration: Works directly on existing projects without requiring changes to project files.

Related

  • Project
    LeoKemp223/embed-ai-tool

    A comprehensive skill set for AI assistants that automates the entire MCU firmware development lifecycle, including building, flashing, and debugging across various toolchains.

  • Project
    mc3545dada/mspm0-skill

    A set of rules and scripts that enable AI Agents to configure, build, flash, and debug TI MSPM0 microcontrollers by directly interacting with SysConfig and hardware toolchains.

  • Project
    joeseesun/qiaomu-meta-skill

    A meta-skill that transforms prompts and workflows into researched, evaluated, and securely published AI agent skill packages.

  • Project
    hatayama/unity-cli-loop

    Unity CLI Loop is a Unity package + cross‑platform CLI that exposes 21 concise commands (skills) for compiling, testing, logging, hot‑reloading, UI manipulation, PlayMode input simulation, screenshots, etc. An LLM can invoke these commands to run a full development loop—compile → test → debug → verify UI—without a human opening the editor. Installation is a one‑liner for the CLI, a Unity‑package install, and a skill‑install step for the target LLM (Claude Code, Codex, …). The system talks to Unity via a Unix‑socket / named‑pipe, needs Unity 2022.3+, and is MIT‑licensed.

  • Dispatch
    Combatting AI Brain Drain: Deliberate Skill Development with Claude Code

    Explore how to use AI 'skills' to transform coding assistants from passive generators into active tutors, preventing the loss of codebase knowledge and cognitive atrophy.