Skill

scientific-agent-skills

K-Dense-AI/scientific-agent-skills · Python · MIT

Domain skills that let an agent do real scientific analysis.

この解説はまだ日本語がありません。英語の原文を表示しています。

A vertical skill pack focused on biology and data science: sequence analysis, cheminformatics, stats and reproducible research workflows an agent can run.

73.1 / 100 · スコア
★ 53k スター
+3.6k 30日間の増加
3 分 初回起動まで
不要 API キー

スコア

トレンド 83
活発度 88
品質 60
コミュニティ 91
関連 55

導入の要点

デプロイCopy
GPUGPU 不要
API キー不要
対応環境Claude Code, Cursor, Gemini CLI
UI 言語en
ドキュメント言語en
インストール
cp -r skills/* ~/.claude/skills/

深読み

A skill pack that turns a general coding agent into a domain scientist. Instead of one monolithic prompt, it ships 177 curated skills across bioinformatics, cheminformatics, proteomics, clinical research, neuroscience, microscopy and machine learning — each one documenting the exact Python stack, dependency versions and validation scope for a real research task.

The skills follow the open Agent Skills standard, so they install into Claude Code, Cursor, Codex and other hosts with a single command (npx or gh skill) and run entirely on your own machine and data. Under the hood the agent chains skills into multi-step workflows: query ChEMBL or ClinicalTrials.gov, analyse structures with RDKit, dock with DiffDock, run differential expression with PyDESeq2, and write the report — with every step traceable to a source.

It is research-only by design: clinical skills produce source-bound drafts for qualified review rather than diagnoses or treatment recommendations. Versioned releases, CI tests per skill and a published arXiv paper make it reproducible enough for serious lab use, not just demos.

ユースケース

Automate genomics or proteomics analyses
Run cheminformatics / drug-discovery tasks
Make a lab's analysis reproducible via skills

向いている / 向いていない

向いている

Research labs and bioinformaticians
Data-science teams in science
Students learning reproducible research

向いていない

General software tasks
Non-scientific domains

トレンド · 30d

代替プロジェクト