Reparadores automáticos de errores mediante stack traces

Ben.Demystifier is a .NET library that transforms raw stack traces into modern C# 7+ syntax. It reads compiler-generated frames produced by async methods, iterators, lambdas, local functions, and generic types, then rewrites them to match the original source code, making exception call stacks and debug output immediately readable. The library resolves common compiler artifacts such as MoveNext frames back into their original async method or iterator names, shows declaring method names and ordinals for lambdas and local functions instead of generated identifiers, and displays resolved generi

This project is a JetBrains IDE plugin that integrates large language model coding assistants directly into the development environment. It provides a visual interface for generating, refining, and refactoring source code through an integrated coding assistance system. The plugin features an agent workflow orchestrator that executes multi-step programming tasks using external tool servers and specialized command shortcuts. It includes a visual code diff tool for analyzing and navigating changes between different versions of AI-generated code across multiple files. The system manages AI conve

CopilotForXcode is an AI-powered coding assistant integrated directly into Xcode as a source editor extension. It functions as an agent that can automate multi-step project tasks, such as editing files, running terminal commands, and searching across the entire codebase, all while understanding the full context of the current Xcode project. The assistant provides a context-aware chat interface that answers coding questions based on open files, symbols, and recent edits. It also offers diff-based code review, analyzing changes to provide feedback on code quality and potential issues before mer

Whoops is a PHP debugging tool and error handler designed to intercept and visualize exceptions and stack traces during application development. It functions as an exception renderer that converts errors into human-readable web pages or machine-readable responses. The project differentiates itself by providing a visual debugging interface with line-highlighted code views and a stack trace visualizer that links directly to source files in a local text editor or IDE. It employs environment-aware response resolution to automatically select between HTML, JSON, XML, or plain text output based on t

Potpie is an LLM codebase analysis platform and multi-agent orchestration framework designed to act as an AI software engineer. It parses repositories into a structured code knowledge graph, enabling AI agents to perform multi-hop reasoning, dependency tracing, and grounded technical analysis across large codebases. The system distinguishes itself through a spec-driven development framework where agents generate detailed technical specifications and architecture plans before implementing multi-file code changes. It utilizes a durable execution engine to coordinate specialized AI personas for

PlatformIO Core is a toolset for embedded software development that manages the compilation, flashing, and debugging of firmware for various microcontroller targets. It provides a cross-platform build system that automates the process of transforming source code into binaries and transferring them to hardware via serial protocols. The system uses a plugin-based architecture to extend hardware platform support and incorporates a manifest-driven approach to resolve and install the specific toolchains, frameworks, and libraries required for different board definitions. Capabilities cover the fu

oh-my-pi is an agentic workflow automation platform and AI coding agent orchestrator designed for autonomous software engineering. It functions as a multi-model LLM router and an LSP-integrated development environment, coordinating specialized AI agents to perform codebase analysis, automated refactoring, and complex task execution. The system distinguishes itself through the use of subagent coordination to execute parallel tasks within isolated environments and an auto-research framework for iterative experiments. It employs AST-driven structural search for code discovery and content-hash an

This project is a high-performance static type checker and comprehensive development toolkit for Python. It functions as a core analysis engine that identifies type inconsistencies and enforces code correctness, while simultaneously providing a language server implementation to deliver real-time diagnostics and intelligence directly within development environments. The tool distinguishes itself through a parallelized execution engine that maximizes performance across large-scale codebases and monorepo structures. It supports gradual type adoption, allowing developers to integrate type checkin