Search Results for "loops"

Auto-Claude is an autonomous, multi-agent coding framework that organizes software work into a structured workflow where agents plan, build, and validate code with minimal manual micromanagement. Instead of relying on a single chat thread to do everything, it uses coordinated agents and a task-driven approach so multiple steps—like investigation, implementation, and testing—can be executed systematically. The project aims to make “agentic software engineering” feel like running a small...

...It uses a Mixture-of-Experts (MoE) architecture with 230 billion total parameters but only 10 billion activated per token, giving it the behavior of a very large model at a fraction of the runtime cost. The model is tuned for end-to-end developer flows such as multi-file edits, compile–run–fix loops, and test-validated repairs across real repositories and diverse programming languages. It is also optimized for multi-step agent tasks, planning and executing long toolchains that span shell commands, browsers, retrieval systems, and code runners. Benchmarks show that it achieves highly competitive scores on a wide range of intelligence and agent benchmarks, including SWE-Bench variants, Terminal-Bench, BrowseComp, GAIA, and several long-context reasoning suites.

Oh My codeX (OMX) is a multi-agent orchestration layer designed to extend the capabilities of OpenAI Codex CLI by introducing structured teamwork, automation, and advanced workflow management. It addresses limitations in the base Codex environment, such as the lack of hooks, agent coordination, and persistent execution, by layering a shell-based system that enables richer interaction patterns. The project transforms a single AI coding assistant into a coordinated system of specialized agents...

darwin-skill is an experimental framework designed to automatically improve AI agent “skills” through iterative evaluation and optimization loops inspired by machine learning training processes. Instead of treating prompts or skill definitions as static assets, the system applies a continuous improvement cycle that evaluates performance, proposes changes, tests outcomes, and either retains or reverts modifications. The framework introduces a scoring system across multiple dimensions, enabling quantitative assessment of skill quality and ensuring that only improvements are preserved over time. ...

...It uses generative modeling techniques to interpret input descriptors such as genre, mood, tempo, instrument palette, and creative themes, then outputs sequences that can serve as sketches, loops, or full musical ideas. The workflow prioritizes interactivity, letting users refine prompts, adjust musical fingerprints, and iterate on compositions in near real-time, making it suitable for ideation, prototyping, or inspiration workflows. The application also emphasizes usability by exporting to common audio formats and DAW-friendly stems, enabling seamless integration into existing music production environments.

Codex Autoresearch is an autonomous software improvement framework that enables AI coding agents to iteratively enhance codebases without continuous human input. The system operates in a loop where the agent modifies code, evaluates results against measurable metrics, and either keeps or discards changes based on performance. It generalizes the concept of autoresearch beyond machine learning, allowing optimization of test coverage, latency, lint errors, and overall code quality. Developers...