Claude Scientific Skills for Claude
Comprehensive collection of 128+ ready-to-use scientific skills for Claude enabling research across biology, chemistry, medicine, genomics, and advanced analysis domains.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/Microck/ordinary-claude-skills --skill claude-scientific-skillsWhat comes with it
504 349 bytes besides the instructionThe instruction itself
14 sections, as written by the authorClaude Scientific Skills Collection
A comprehensive collection of 128+ ready-to-use scientific skills that transforms Claude into an AI research assistant capable of executing complex multi-step scientific workflows.
Scientific Domains
🧬 Bioinformatics & Genomics
Sequence analysis, single-cell RNA-seq, gene regulatory networks, variant annotation, phylogenetic analysis
🧪 Cheminformatics & Drug Discovery
Molecular property prediction, virtual screening, ADMET analysis, molecular docking, lead optimization
🔬 Proteomics & Mass Spectrometry
LC-MS/MS processing, peptide identification, spectral matching, protein quantification
🏥 Clinical Research & Precision Medicine
Clinical trials, pharmacogenomics, variant interpretation, drug safety, precision therapeutics
🧠 Healthcare AI & Clinical ML
EHR analysis, physiological signal processing, medical imaging, clinical prediction models
🖼️ Medical Imaging & Digital Pathology
DICOM processing, whole slide image analysis, computational pathology, radiology workflows
🤖 Machine Learning & AI
Deep learning, reinforcement learning, time series analysis, model interpretability, Bayesian methods
🔮 Materials Science & Chemistry
Crystal structure analysis, phase diagrams, metabolic modeling, computational chemistry
🌌 Physics & Astronomy
Astronomical data analysis, cosmological calculations, symbolic mathematics, physics computations
⚙️ Engineering & Simulation
Discrete-event simulation, optimization, metabolic engineering, systems modeling
Included Skill Categories
- 26+ Scientific Databases - OpenAlex, PubMed, ChEMBL, UniProt, COSMIC, ClinicalTrials.gov
- 54+ Python Packages - RDKit, Scanpy, PyTorch, scikit-learn, BioPython, PennyLane, Qiskit
- 15+ Scientific Integrations - Benchling, DNAnexus, LatchBio, OMERO, Protocols.io
- 20+ Analysis & Communication Tools - Literature review, scientific writing, peer review
Getting Started
Each skill within this collection includes:
- Comprehensive documentation (SKILL.md)
- Practical code examples
- Use cases and best practices
- Integration guides
- Reference materials
Explore the scientific-skills/ subdirectory for individual skill implementations and detailed documentation.
Other skills for the same job
different authors, same section of the catalogue
Generate clinical trial protocols for medical devices or drugs. This skill should be used when users say "Create a clinical trial protocol", "Generate protocol for [device/drug]", "Help me design a clinical study", "Research similar trials for [intervention]", or when developing FDA submission documentation for investigational products.
Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.
Multi-agent research skill for parallel research execution (10 agents, battle-tested with real case studies).
Generate and prioritize US equity long-side edge research tickets from EOD observations, then export pipeline-ready candidate specs for trade-strategy-pipeline Phase I. Use when users ask to turn hypotheses/anomalies into reproducible research tickets, convert validated ideas into `strategy.yaml` + `metadata.json`, or preflight-check interface compatibility (`edge-finder-candidate/v1`) before running pipeline backtests.
Use this skill when building or modifying Minecraft server plugins for Paper, Spigot, or Bukkit, including plugin.yml setup, commands, listeners, schedulers, player state, team or arena systems, persistent progression, economy or profile data, configuration files, Adventure text, and version-safe API usage. Trigger for requests like "build a Minecraft plugin", "add a Paper command", "fix a Bukkit listener", "create plugin.yml", "implement a minigame mechanic", "add a perk or quest system", or "debug server plugin behavior".
Internal guidance for composing Codex and GPT-5.4 prompts for coding, review, diagnosis, and research tasks inside the Codex Claude Code plugin
Use when the user asks how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains.
This skill should be used when designing autonomous agent harnesses: research loops, evaluation scaffolds, locked and editable surfaces, durable logs, novelty gates, pruning, rollback, PR preparation, and human approval boundaries.
How to use it
Take microck/claude-scientific-skills from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.