ai-scientist - 技术专题

Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 170,000+ scientists worldwide. 156 ready-to-use skills plus 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Pi, Antigravity, and the open Agent Skills standard.

DeepAnalyze is the first agentic LLM for autonomous data science. 🎈你的AI数据分析师，自动分析大量数据，一键生成专业分析报告！

A blueprint-driven AutoResearch runtime for orchestrating AI research workflows from idea generation and experiments to paper writing and peer review.

VibeSkills is a general-purpose Skill that automatically routes local Skills and intelligently orchestrates harness workflows.

MCP, CLI, Skills for searching and downloading academic papers from multiple sources like arXiv, PubMed, bioRxiv, etc.

🦞+🔬 NanoResearch: The Autonomous AI Research Assistant

Best Data Science, Data Analytics, AI, and SDE roadmaps. This repository is continually updated based on the top job postings on LinkedIn and Indeed in the data science and AI domain.

A Super AI Lab with massive AI Doctors as Assistants. Best IDE for Research via AI Power.

Open Science Desktop — local-first, model-agnostic AI research workbench for macOS, Windows & Linux. Open-source Claude Science desktop alternative built on Tauri + MCP + agent skills.

AI handles execution, humans own the direction, and every run becomes an inspectable research artifact on disk.

🔥 A Survey on AI Auto-Research

Principia extracts reusable principles, composes those principles into traceable research ideas, and helps researchers inspect why an idea may be worth testing.

900+ pure-markdown skills for autonomous AI research, organized as 9 freely-composable packages over a 4-layer hierarchy (Campaign → Strategy → Tactic → SOP). Non-linear orchestration with backtracking, 6 MCP integrations. The AI is the researcher — you set the direction.

Fully Autonomous AI Research System with Self-Evolution, built natively on Claude Code

🦞 ResearchClawBench: Evaluating AI Agents for Automated Research from Re-Discovery to New-Discovery

BioAgents: An AI scientist framework for autonomous deep research in biological sciences. Multi-agent system combining literature analysis agents with data scientist agents to enable deep research automation through user feedback integration and iterative scientific discovery. Inspired by advances in Edison Kosmos, Sakana AI, K-Dense and others.

Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows

A collection of resources and papers on AI Scientist / Robot Scientist

Open-source agent skills for AI for Science: topic exploration, literature survey, experiments, paper writing, and integrity audit — driven by any coding agent.

A Large-Scale Knowledge Graph for Automated Scientific Research