Semi-automated research assistant for academic research and software development. Supports Claude Code, Codex CLI, Kimi Code CLI, and OpenCode across ideation, coding, experiments, writing, and pub…

AKShare is an elegant and simple financial data interface library for Python, built for human beings! 开源财经数据接口库

Practical patterns, starters & CLI tools for loop engineering with AI coding agents. Design systems that prompt and orchestrate agents (inspired by Addy Osmani and Boris Cherny). Includes loop-audi…

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A curated, multilingual library of 182 installable AI agent skills for end-to-end academic research—spanning literature discovery, scientific writing, grant development, bioinformatics, drug discov…

本仓库包含三个面向学术科研人员的Skills，覆盖从文献阅读、论文写作到科学计算的完整研究工作流。office-academic-skill 负责论文阅读报告与学术 PPT/Word 文档生成；research-writing-skill 提供论文写作、润色与审稿回复辅助；scientific-toolkit-skill 整合 MATLAB/Python 科学计算与期刊级图表生成。三个 Sk…

AI 驱动的学术论文配图生成平台。上传论文 → AI 分析内容生成 Prompt → 一键生成高质量科研配图，还有配套的skill可在主流agent中使用

Elevate your AI research writing, no more tedious polishing ✨

A cross-platform desktop All-in-One assistant for Claude Code, Codex, OpenCode, OpenClaw, Grok Build & Hermes Agent. Only official website: ccswitch.io

Academic Research Skills for Claude Code: research → write → review → revise → finalize

Universal memory layer for AI Agents

Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings and DeepSeek Harness support.

A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy's observations on LLM coding pitfalls.

The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search

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Harness Engineering 学习指南 — 从概念理解到独立实践的深度学习档案

[Up-to-date] Large Language Model Agent: A Survey on Methodology, Applications and Challenges

PaperBanana: Automating Academic Illustration For AI Scientists

SGLang is a high-performance serving framework for large language models and multimodal models.

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Lighteval is your all-in-one toolkit for evaluating LLMs across multiple backends

A high-throughput and memory-efficient inference and serving engine for LLMs

Fast and memory-efficient exact attention

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