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ScienceClaw

by beita6969

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🔬🦞 A self-evolving AI research colleague for scientists. 285 skills, zero hallucination, persistent memory.

123stars
10forks
TypeScript
Added 3/15/2026
View on GitHubDownload ZIP
AI Agentsaiai-agentbioinformaticsliterature-reviewllmmcpmeta-analysisopenclawpubmedresearchresearch-toolssciencescientific-researchself-evolvingzero-hallucination
Installation
# Add to your Claude Code skills
git clone https://github.com/beita6969/ScienceClaw
README.md
<p align="center"> <img src="assets/banner.png" alt="ScienceClaw — AI Research Gateway" width="800" /> </p> <p align="center"> <strong>A self-evolving AI research colleague for scientists.</strong> </p> <p align="center"> <img src="https://img.shields.io/github/stars/beita6969/ScienceClaw?style=flat-square&logo=github&label=Stars" alt="Stars"> <img src="https://img.shields.io/badge/skills-285-8A2BE2?style=flat-square" alt="285 Skills"> <img src="https://img.shields.io/badge/disciplines-28+-2a9d8f?style=flat-square" alt="28+ Disciplines"> <img src="https://img.shields.io/badge/hallucination-zero-e05d44?style=flat-square" alt="Zero Hallucination"> <img src="https://img.shields.io/github/license/beita6969/ScienceClaw?style=flat-square" alt="License"> </p>

Why ScienceClaw?

General-purpose AI assistants are built for everyone. ScienceClaw is built for researchers.

The core idea is simple: an AI that does real scientific work — searching literature, querying databases, running analyses — and gets better at it the more you use it. It remembers your research context across sessions, adapts its skills to your field, and never fabricates a citation.

ScienceClaw is built on the OpenClaw engine, but redesigned from the ground up for academic research.

<p align="center"> <img src="assets/comparison.png" alt="ScienceClaw vs Standard AI" width="720" /> </p>

🧬 Core 1: Self-Evolving Skills

This is ScienceClaw's most important feature.

Most AI tools ship with a fixed set of capabilities. ScienceClaw's skills evolve with you. Every time you complete a research task, the system learns:

<p align="center"> <img src="assets/skill-evolution.png" alt="Skill Self-Evolution Cycle" width="720" /> </p>

What this means in practice:

  • Week 1: You study immunology. ScienceClaw learns that PubMed + Semantic Scholar works best for your queries, that you prefer forest plots over tables, and that you always need PMID + DOI in citations.
  • Week 4: The system has created specialized skills for your subfield — optimized search templates, preferred statistical methods, database priority chains tuned to immunology literature.
  • Month 3: ScienceClaw handles your domain like a trained research assistant. It knows which databases to hit first, which journals matter, and how you like your output formatted.

Compared to standard OpenClaw: OpenClaw ships with ~54 general-purpose skills that don't change. ScienceClaw starts with 285 skills and grows from there — the agent writes new SKILL.md files at runtime without any redeployment.


🧠 Core 2: Research Memory That Persists

Standard AI assistants forget everything when the conversation ends. ScienceClaw doesn't.

<p align="center"> <img src="assets/memory-layers.png" alt="Four-Layer Research Memory" width="720" /> </p>

What this enables:

  • "Continue the literature review we started last Tuesday" ...
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