The Problem

Thousands of Agent Skills are scattered across official registries and community repos. A researcher who needs to run a gene ontology enrichment, draft a grant proposal, and plot dose-response curves shouldn't have to dig through 30,000+ entries to find the right three skills. And once found, they shouldn't have to wire them together from scratch.

The Goal

Build a single, clone-ready repository of high-quality skills selected and organized for scientific research — spanning bioinformatics, cheminformatics, data analysis, scientific writing, literature search, and beyond.

Phase 1 (current): A curated link collection — the reading list before the library.

Phase 2: Import and reorganize selected skills into a unified directory structure.

Phase 3: Composition recipes — multi-skill workflows for real research tasks.

Why This Repo?

Skill Sources

We draw from two tiers of upstream repositories:

Official Skill Registries

Community Curations

Science-Specific

Specialized Domain Tools (Top Priority)

Academic Writing

Literature Search

Neuroscience

Scientific Skill Categories

Below is the target taxonomy. Skills from the sources above are mapped into these categories. Checked boxes indicate categories already well-covered upstream; unchecked indicate gaps we aim to fill.

Wet-Lab & Life Sciences

• Bioinformatics & Genomics — sequence analysis, single-cell RNA-seq (Scanpy), variant annotation, phylogenetics, gene regulatory networks
• Cheminformatics & Drug Discovery — molecular property prediction (RDKit), docking, ADMET, compound library search (ChEMBL)
• Structural Biology — protein structure prediction, PDB retrieval, molecular visualization
• Clinical & Medical Research — ClinicalTrials.gov search, ICD coding, adverse event analysis, COSMIC/TCGA queries

Computational & Data Science

• Statistical Analysis — hypothesis testing, Bayesian inference, survival analysis, power calculations
• Machine Learning for Science — PyTorch Lightning workflows, scikit-learn pipelines, hyperparameter tuning
• Simulation & Modeling — molecular dynamics, finite element analysis, agent-based modeling
• High-Performance Computing — job submission (SLURM/PBS), distributed training, GPU profiling

Literature & Knowledge

• Literature Search & Retrieval — PubMed, arXiv, Semantic Scholar, CrossRef, DOI resolution
• Scientific Writing — paper drafting, grant proposals, peer review assistance, citation management
• Knowledge Graphs — ontology navigation (Gene Ontology, MeSH), entity linking, relationship extraction

Research Operations

• Data Wrangling — tabular data cleaning, format conversion, missing data imputation
• Visualization — publication-quality plots (Matplotlib/Seaborn), interactive dashboards, figure layout
• Reproducibility — environment capture, notebook-to-pipeline conversion, data provenance tracking
• Document Processing — PDF extraction, DOCX/PPTX generation, LaTeX compilation

Quantitative & Financial Research

• Financial Data — SEC EDGAR, Alpha Vantage, OFR Hedge Fund Monitor, Treasury fiscal data
• Econometrics — time series analysis, causal inference, panel data methods

Quick Start

Option 1 — Browse and pick

Explore the [Skill Sources](#Skill Sources) above, find what you need, and copy individual skill folders into your project:

your-project/
└── .claude/
    └── skills/
        ├── pubmed-search/
        ├── rdkit-molecular-analysis/
        └── scientific-writer/

Option 2 — Clone the science stack (Phase 2)

# Coming soon — once we consolidate skills into this repo
git clone https://github.com/InternScience/Awesome-Scientific-Skills.git
cp -r Awesome-Scientific-Skills/skills/ your-project/.claude/skills/

Compatibility

Skills follow the open Agent Skills specification. They work with:

• Claude Code — /skills or .claude/skills/ directory
• Cursor — reads from .claude/skills/ and .codex/skills/
• Codex — .codex/skills/ directory
• Gemini CLI / Antigravity — compatible via the Agent Skills standard

Selection Criteria

Not every skill makes the cut. We apply these filters:

Contributing

Contributions are welcome. This is a curated list — quality over quantity.

To suggest a skill:

1. Fork this repository
2. Add the skill to the appropriate section in readme.md with format:

   | [skill-name](https://github.com/...) | Brief description of what it does |
   

3. Submit a Pull Request with a short note on why this skill is useful for scientific research

What we're looking for:

• Skills that solve real problems researchers face daily
• Skills that compose well with others (e.g., a search skill whose output feeds into an analysis skill)
• Skills maintained by their authors — not abandoned after initial commit

What we don't accept:

• Crypto/blockchain/DeFi skills (off-scope)
• Skills with no documentation
• Bulk-generated or spam skills
• Skills that require proprietary backends without free tiers

Security Notice

Skills can execute arbitrary code in your agent's environment. Always review a skill's SKILL.md and any bundled scripts before installing. The skills listed here are curated, not audited — they may be updated or modified by their original maintainers at any time.

Roadmap

• Phase 1 — Curated link collection with source taxonomy
• Phase 2 — Community skill registry with ratings and usage metrics
• Phase 3 — Test skill in OpenClaw and Claude Code
• Phase 4 — Develop skill creator which can create skill from paper and agentic trace

Related Projects

Companion open-source tools from our team for skill generation and repository evaluation:

License

This curated list is released under MIT. Individual skills retain their own licenses as specified in their respective SKILL.md files.