A skills set and methodology for coding agents: clarify the task, plan, write tests, then code. The agent works with more discipline.
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The best AI repositories
224 living projects — from agent frameworks to prompt-injection defense. Each comes with our own note: why it matters, who it is for and how to start in three steps.
Stars, forks and activity refresh daily via the GitHub API · updated October 6, 2026
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A service that turns any website into clean Markdown or structured data for models. It can search, scrape, crawl a whole site and even click through a page.
A small Microsoft utility that converts PDF, Word, PowerPoint, Excel and other files into Markdown that is easy to hand to a language model.
An open coding agent for the terminal with a desktop app. It is not tied to one provider: plug in whichever models you have.
A toolkit for spec-driven development: principles and a spec first, then a plan and tasks, and only then code. Works with several coding agents.
OpenAI's lightweight coding agent that runs in the terminal and works on your project's code. Written in Rust.
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8 repositories
Repository of the large open DeepSeek-V3 mixture-of-experts model: description, benchmark results and run instructions. It showed an open model can stand next to closed ones.
The open DeepSeek-R1 model, trained with reinforcement learning to reason step by step, plus its smaller distilled versions on Qwen and Llama.
An open text-to-speech model with multilingual synthesis and voice cloning. Comes with docs, a Docker image and a server mode.
The open Qwen3 model family from Alibaba, from small to large, with reasoning modes. The README collects run examples for Transformers, llama.cpp and Ollama.
A parameter-efficient fine-tuning library: LoRA and related methods train only a small fraction of the weights. Large models fine-tune on consumer hardware.
Two open OpenAI models, gpt-oss-120b and gpt-oss-20b, plus reference run implementations including Metal for Mac. A rare case of OpenAI releasing weights.
The Qwen team's family of multimodal models: understand images, documents and video, locate objects in a frame and work with UIs.
A modern rethink of the recurrent LSTM with exponential gating and matrix memory. The authors trained an xLSTM 7B language model on it, with weights on Hugging Face.
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