What GitHub workflows are created during integration?

It sets up three specialized workflows: a report generator for PRs, a comment bot for status updates, and an onboarding workflow to process historical commit data.

What architectures does this skill support?

It supports major embedded platforms including ARM Cortex-M (STM32, SAMD, NXP), ESP32/ESP8266, RISC-V, and Unix-based builds.

Do I need a MemBrowse account to use this?

Yes, you will need a MemBrowse API key from your dashboard to configure the repository secrets required for the GitHub Actions to function.

How does it identify build targets?

The skill scans the repository for Makefiles, CMakeLists.txt, linker scripts (.ld), and existing CI workflows to identify build patterns and output locations.

MemBrowse Embedded Memory Tracking

Name: MemBrowse Embedded Memory Tracking
Author: membrowse

bymembrowse

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Analytics & Monitoring

Integrates MemBrowse memory analysis into embedded firmware projects to track and visualize RAM and Flash usage.

About

This skill automates the setup of MemBrowse for embedded firmware repositories, providing developer teams with deep visibility into memory consumption across various hardware targets. It intelligently discovers build systems, linker scripts, and ELF outputs to generate a configuration matrix and high-performance GitHub Actions workflows. By establishing automated memory reporting on every pull request and creating historical onboarding paths, this skill helps firmware engineers prevent memory overflows and optimize resource allocation throughout the development lifecycle.

Key Features

Automated discovery of Make, CMake, and linker script configurations
Supports ARM Cortex-M, ESP32, RISC-V, and generic Unix toolchains
10 GitHub stars
Generates multi-stage GitHub Actions workflows for PR reporting and commenting
Configures historical memory analysis through an onboarding workflow
Automatically integrates memory status badges into project READMEs

Use Cases

Setting up automated memory footprint tracking for new firmware projects
Monitoring RAM/Flash trends across multiple board variants in a single CI pipeline
Preventing memory-related regressions by analyzing footprint changes in pull requests

About

Key Features

Automated discovery of Make, CMake, and linker script configurations
Supports ARM Cortex-M, ESP32, RISC-V, and generic Unix toolchains
10 GitHub stars
Generates multi-stage GitHub Actions workflows for PR reporting and commenting
Configures historical memory analysis through an onboarding workflow
Automatically integrates memory status badges into project READMEs

Use Cases

Setting up automated memory footprint tracking for new firmware projects
Monitoring RAM/Flash trends across multiple board variants in a single CI pipeline
Preventing memory-related regressions by analyzing footprint changes in pull requests