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crazymsn / academic-skills

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15
4
100% credibility
Found Jun 01, 2026 at 15 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Academic Skills is a collection of 139 ready-to-use skill packages designed to help researchers, scientists, and professionals with tasks like bioinformatics analysis, clinical documentation, citation management, scientific writing, and molecular modeling. These skills work with AI coding assistants to automate and improve research workflows. The collection is open-source (MIT License), thoroughly documented, and includes built-in security scanning to ensure safe use. It covers diverse domains including genomics, drug discovery, clinical trials, geospatial science, and academic publishing.

How It Works

1
🔬 You discover a research challenge

You're working on a scientific project and need help with analysis, writing, or data processing.

2
📚 You find a collection of ready-made solutions

This project offers 139 pre-built skill packages for research tasks like analyzing genetic data, managing citations, writing clinical reports, and more.

3
🧩 You connect the skills to your AI assistant

You install the skills into your AI coding assistant with a simple command, making them available whenever you need them.

4
✨ You pick the skill you need

Whether it's converting research citations, analyzing molecular data, generating scientific diagrams, or reviewing clinical documents, you select the right tool for your task.

5
🚀 Your AI assistant works with the skill

The skill guides your AI assistant to handle complex scientific tasks correctly, from proper data formats to regulatory compliance.

✅ You get professional-quality results

Your research materials are properly formatted, your analysis tools work correctly, and your documents meet scientific standards.

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Star Growth

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AI-Generated Review

What is academic-skills?

This is a curated collection of 139 agent skills designed for AI coding assistants like Claude Code, Codex, and OpenCode. Each skill is essentially a prompt template that guides an AI agent through specialized workflows in research and science. The collection spans bioinformatics, cheminformatics, clinical research, citation management, scientific writing, and AI/ML tasks. You install skills directly into your agent's skills directory using the npx skills command, then the agent can execute domain-specific tasks like converting DOIs to BibTeX, analyzing protein sequences, or generating scientific diagrams. The repository includes security scanning tools to validate skills before installation, and supports both project-local and global installation modes.

Why is it gaining traction?

The hook here is specialization. Generic AI coding agents are powerful, but they lack domain knowledge. This collection packages expert-level workflows for scientific computing into ready-to-use prompts. Researchers can get a citation manager, a pathway analyzer, or a clinical document validator without writing a single line of code. The autoskill feature is particularly interesting—it can observe your screen activity and propose new skills based on your actual workflow patterns. The security scanning baked into the project suggests the maintainers take the "skills can run commands" risk seriously.

Who should use this?

Academic researchers who rely heavily on AI coding assistants and need domain-specific capabilities. Bioinformatics teams doing gene regulatory network analysis, clinical researchers managing trial documentation, or academics writing papers with complex citation requirements will find the most value. If you're already using Claude Code or Codex and want specialized scientific workflows without building them from scratch, this saves significant setup time. However, the 15-star count and 1.0% credibility score indicate this is early-stage and unproven at scale.

Verdict

At 15 stars with a 1.0% credibility score, this is a niche project with minimal community validation. The concept is solid—specialized agent skills for scientific workflows fills a real gap—but the low adoption means you're among the first users, with all the instability that implies. Review each skill's SKILL.md file before installing, as the documentation warns. If you need these capabilities and can tolerate early-stage software, it may be worth exploring. For production research workflows, wait for stronger community signals.

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