A simple, open format for guiding coding agents, used by over 60k open-source projects. It's a dedicated, predictable place to provide the context and instructions to help AI coding agents work on your project.
Code Wiki is a platform that maintains a continuously updated, structured wiki for code repositories, aiming to improve developer productivity by unlocking knowledge buried in source code. It features automated documentation, intelligent context-aware chat, and integrated actionable links.
High-level diagram representations for code. CodeBoarding is an open-source codebase analysis tool that generates high-level diagram representations of codebases using static analysis and LLM agents, that humans and agents can interact with.
AI-powered multi-agent system that automatically analyzes codebases and generates comprehensive documentation. Features GitLab integration, concurrent processing, and multiple LLM support for better code understanding and developer onboarding.
This document provides a developer guide for the Tiny Code Reader from Useful Sensors, a small, low-cost hardware module that reads QR codes. It covers connecting, mounting, powering up, reading data, configuration, sensor characteristics, example code, privacy considerations, and an appendix with data formats and CAD files.
This page showcases a demo of kapa.ai, an AI assistant that turns knowledge bases into reliable and production-ready AI solutions. It highlights features like an answer engine, data source integrations, deployment options, analytics, and security features.
A practical guide to Architecture Decision Records (ADRs) covering what they are, why they're important, how to use them, tools for managing them, writing good ones, when to use them, and organizing them.
An article detailing the top API documentation tools of 2025, featuring comprehensive reviews with examples, protocol support, pricing, and strengths and weaknesses.
This article explores automating the process of converting scientific code into LaTeX documents using GPT models and Python, aiming to streamline documentation workflows in scientific projects.
The importance of project documentation is emphasized through a personal anecdote, and an introduction to using MkDocs for creating beautiful documentation pages using Markdown.
