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Tags: LLM tools
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1–22 of 22 · Most stars

FULL Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new, Lovable, Manus, NotionAI, Orchids.app, Perplexity, Poke, Qoder, Replit, Same.dev, Trae, Traycer AI, VSCode Agent, Warp.dev, Windsurf, Xcode, Z.ai Code, Dia & v0. (And other Open Sourced) System Prompts, Internal Tools & AI Models

  • ai
  • cursor
  • lovable
  • system-prompts

OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.

Translated🚀 Universal AI IDE account manager for Antigravity / Codex / GitHub Copilot / Windsurf / Kiro / Cursor / Gemini-cli / CodeBuddy, with multi-account switching, quota monitoring, wake-up automation, and multi-insta

TranslatedLangGPT: Empowering everyone to become a prompt expert! 🚀 📌 Proposer of Structured Prompt 📌 Initiator of Meta-Prompt 📌 The most popular paradigm for putting prompts into practice | Language of GPT The pioneering framework for structured & meta-prompt design 10,000+ ⭐ | Battle-tested by thousands of users worldwide Created by 云中江树 (Yunzhong Jiangshu, "river and trees amid the clouds")

ProtTrans is providing state of the art pretrained language models for proteins. ProtTrans was trained on thousands of GPUs from Summit and hundreds of Google TPUs using Transformers Models.

A large language model (LLM) plugin for Neovim, provides commands to interact with LLM (like ChatGPT, Copilot, ChatGLM, kimi, deepseek, openrouter and local llms). Support Github models.

TavernGym and TavernBench: a faithful, full-content Hearthstone Battlegrounds simulator with an RL interface, and a 960-task decision benchmark. Code and data for "Build, Don't Play".

OpenTelemetry-native tracing, token tracking, cost attribution, and prompt analytics for Go backends integrating LLMs.

You need customized prompts for your tasks! 🤏SimpleGPT is a Vim plugin designed to provide a simple yet flexible way to customize your prompts for your tasks or building chat on nearly all kinds of LLM APIs.

Spends CPU cycles so you don't spend tokens. The LLM gets a briefing packet instead of a flashlight in a dark room.