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@@ -2,9 +2,9 @@
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title: "Scientific Agent Skills"
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task: ""
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lineage_type: import
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upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/991bd993/README.md
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upstream_sha: 991bd993
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imported_at: 2026-08-08
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upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/5ad4aae7/README.md
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upstream_sha: 5ad4aae7
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imported_at: 2026-08-12
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prompt_class: catalogue
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upstream_changes: accepted
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author: upstream
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@@ -14,10 +14,11 @@ validated: false
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# Scientific Agent Skills
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[](LICENSE.md)
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[](pyproject.toml)
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[](#-whats-included)
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[](pyproject.toml)
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[](#-whats-included)
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[](#-whats-included)
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[](https://agentskills.io/)
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[](https://agent-plugins.org/)
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[](https://github.com/K-Dense-AI/scientific-agent-skills/actions/workflows/security-scan.yml)
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[](https://github.com/K-Dense-AI/scientific-agent-skills/actions/workflows/skill-tests.yml)
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[](#-getting-started)
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@@ -25,23 +26,13 @@ validated: false
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[](https://www.linkedin.com/company/k-dense-inc)
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[](https://www.youtube.com/@K-Dense-Inc)
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## Star History
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<a href="https://www.star-history.com/?repos=K-Dense-AI%2Fscientific-agent-skills&type=date&legend=top-left">
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<picture>
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<source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/chart?repos=K-Dense-AI/scientific-agent-skills&type=date&theme=dark&legend=top-left&sealed_token=rL_5GLS9f4Fbyr1_VYZLGMF-8Rr6ZlWNaYNecajc52QSQq6KL7HrzSea_tGQGy1mBMXgVvAUMSIYAc0w39si9v5Up1RIw74-UDGZg_9HvH_chiyS0Njf-5tebtPh1LJjXTG6mH5Iv2pMJNivgfPsyB-oOgbaIV3uSc7DzSeZFCTE4WOcHX4y2BR76k5g" />
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<source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/chart?repos=K-Dense-AI/scientific-agent-skills&type=date&legend=top-left&sealed_token=rL_5GLS9f4Fbyr1_VYZLGMF-8Rr6ZlWNaYNecajc52QSQq6KL7HrzSea_tGQGy1mBMXgVvAUMSIYAc0w39si9v5Up1RIw74-UDGZg_9HvH_chiyS0Njf-5tebtPh1LJjXTG6mH5Iv2pMJNivgfPsyB-oOgbaIV3uSc7DzSeZFCTE4WOcHX4y2BR76k5g" />
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<img alt="Star History Chart" src="https://api.star-history.com/chart?repos=K-Dense-AI/scientific-agent-skills&type=date&legend=top-left&sealed_token=rL_5GLS9f4Fbyr1_VYZLGMF-8Rr6ZlWNaYNecajc52QSQq6KL7HrzSea_tGQGy1mBMXgVvAUMSIYAc0w39si9v5Up1RIw74-UDGZg_9HvH_chiyS0Njf-5tebtPh1LJjXTG6mH5Iv2pMJNivgfPsyB-oOgbaIV3uSc7DzSeZFCTE4WOcHX4y2BR76k5g" />
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</picture>
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</a>
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> **🔔 Claude Scientific Skills is now Scientific Agent Skills.** Same skills, broader compatibility — now works with any AI agent that supports the open [Agent Skills](https://agentskills.io/) standard, not just Claude.
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> **New: [K-Dense BYOK](https://github.com/K-Dense-AI/k-dense-byok)** — A free, open-source AI co-scientist that runs on your desktop, powered by Scientific Agent Skills. Bring your own API keys, pick from 40+ models, and get a full research workspace with web search, file handling, 100+ scientific databases, and access to all 159 skills in this repo. Your data stays on your computer, and you can optionally scale to cloud compute via [Modal](https://modal.com/) for heavy workloads. [Get started here.](https://github.com/K-Dense-AI/k-dense-byok)
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> **New: [K-Dense BYOK](https://github.com/K-Dense-AI/k-dense-byok)** — A free, open-source AI co-scientist that runs on your desktop, powered by Scientific Agent Skills. Bring your own API keys, pick from 40+ models, and get a full research workspace with web search, file handling, 100+ scientific databases, and access to all 161 skills in this repo. Your data stays on your computer, and you can optionally scale to cloud compute via [Modal](https://modal.com/) for heavy workloads. [Get started here.](https://github.com/K-Dense-AI/k-dense-byok)
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> **Stay up to date:** Follow K-Dense on [X](https://x.com/k_dense_ai), [LinkedIn](https://www.linkedin.com/company/k-dense-inc), and [YouTube](https://www.youtube.com/@K-Dense-Inc) for new skills, release announcements, walkthroughs, research workflow demos, and examples you can use with your own AI agent.
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A comprehensive collection of **159 ready-to-use scientific and research skills** (covering cancer genomics, individual-level 1000 Genomes queries, hosted regulatory-sequence prediction, live pathogen-variant surveillance, analytical method validation, PK/PD modelling and dose selection, full-text biomedical and regulatory literature retrieval, drug-target binding, molecular dynamics, RNA velocity, geospatial science, time series forecasting, scientific ML resource discovery via Hugging Science, 78+ scientific databases, and more) for any AI agent that supports the open [Agent Skills](https://agentskills.io/) standard, created by [K-Dense](https://k-dense.ai). Works with **Cursor, Claude Code, Codex, Google Antigravity, and more**. Transform your AI agent into a research assistant capable of executing complex multi-step scientific workflows across biology, chemistry, medicine, and beyond.
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A comprehensive collection of **161 ready-to-use scientific and research skills** (covering cancer genomics, individual-level 1000 Genomes queries, hosted regulatory-sequence prediction, live pathogen-variant surveillance, analytical method validation, PK/PD modelling and dose selection, full-text biomedical and regulatory literature retrieval, drug-target binding, bounded biomedical knowledge graph search, molecular dynamics, RNA velocity, geospatial science, time series forecasting, scientific ML resource discovery via Hugging Science, 78+ scientific databases, and more) for any AI agent that supports the open [Agent Skills](https://agentskills.io/) standard, created by [K-Dense](https://k-dense.ai). The repository is also a portable [Agent Plugins](https://agent-plugins.org/) package (`plugin.json` + `skills/`), so plugin-capable clients can load the whole collection as one plugin. Works with **Cursor, Claude Code, Codex, Google Antigravity, and more**. Transform your AI agent into a research assistant capable of executing complex multi-step scientific workflows across biology, chemistry, medicine, and beyond.
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> ⭐ **Help make AI for science easier to discover:** If Scientific Agent Skills saves you time, teaches your agent a workflow, or helps your lab move faster, please [star this repository](https://github.com/K-Dense-AI/scientific-agent-skills). A star is a public signal that these open, reusable research skills are worth maintaining: it helps scientists, engineers, and open-source contributors find the project, shows which agent-skill standards are gaining real adoption, and gives us a clear reason to keep expanding the collection for the community.
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@@ -76,9 +67,9 @@ These skills enable your AI agent to seamlessly work with specialized scientific
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## 📦 What's Included
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This repository provides **159 scientific and research skills** organized into the following categories:
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This repository provides **161 scientific and research skills** organized into the following categories:
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- **100+ Scientific & Financial Databases** - A unified database-lookup skill provides deterministic, provenance-rich access to 78 public databases (PubChem, ChEMBL, UniProt, COSMIC, ClinicalTrials.gov, FRED, USPTO, and more), plus dedicated skills for DepMap, Imaging Data Commons, PrimeKG, U.S. Treasury Fiscal Data, Hugging Science, OneKGPd, and Genomic Intelligence. Multi-database packages like BioServices (~40 bioinformatics services), BioPython (39 NCBI sub-databases via Entrez), and gget (20+ genomics databases) add further coverage
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- **100+ Scientific & Financial Databases** - A unified database-lookup skill provides deterministic, provenance-rich access to 78 public databases (PubChem, ChEMBL, UniProt, COSMIC, ClinicalTrials.gov, FRED, USPTO, and more), plus dedicated skills for DepMap, Imaging Data Commons, PrimeKG, NCATS ARAX, U.S. Treasury Fiscal Data, Hugging Science, OneKGPd, and Genomic Intelligence. Multi-database packages like BioServices (~40 bioinformatics services), BioPython (39 NCBI sub-databases via Entrez), and gget (20+ genomics databases) add further coverage
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- **70+ Optimized Python Package Skills** - Explicitly defined, version-aware workflows for RDKit, Scanpy, PyTorch Lightning, scikit-learn, PyTDC, PathML, pydicom, NeuroKit2, PufferLib, QuTiP, GeoPandas, pymatgen, BioPython, Qiskit, Molecular Dynamics (OpenMM/MDAnalysis), and others. The agent can still use *any* Python package; these skills provide stronger, safer guidance for the packages listed
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- **9 Scientific Integration Skills** - Explicitly defined skills for Benchling, DNAnexus, LatchBio, OMERO, Protocols.io, Open Notebook, Ginkgo Cloud Lab, LabArchives, and Opentrons. Again, the agent is not limited to these — any API or platform reachable from Python is fair game; these skills are the optimized, pre-documented paths
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- **30+ Analysis & Communication Tools** - Literature review, evidence-traceable scientific writing, confidential peer review, document processing, Paperclip (full-text papers, FDA/PMDA/EMA filings, and trial registries with line-pinned citations), Paperzilla, Exa Search, macro-free PPTX posters, slides, schematics, infographics, Mermaid diagrams, and more
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@@ -123,7 +114,7 @@ Each skill includes:
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- **Multi-Step Workflows** - Execute complex pipelines with a single prompt
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### 🎯 **Comprehensive Coverage**
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- **159 Skills** - Extensive coverage across all major scientific domains
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- **161 Skills** - Extensive coverage across all major scientific domains
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- **100+ Databases** - Unified access to 78+ databases via database-lookup, plus dedicated data access skills and multi-database packages like BioServices, BioPython, and gget
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- **70+ Optimized Python Package Skills** - Current, version-scoped guidance for packages including RDKit, Scanpy, PyTorch Lightning, scikit-learn, PyTDC, pydicom, PufferLib, QuTiP, GeoPandas, pymatgen, Qiskit, Molecular Dynamics (OpenMM/MDAnalysis), scVelo, and TimesFM (the agent can use any Python package; these are the pre-documented paths)
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@@ -178,7 +169,7 @@ Pin to a specific release tag or commit SHA for reproducible installs:
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```bash
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# Pin to a release tag
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gh skill install K-Dense-AI/scientific-agent-skills --pin v2.62.0
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gh skill install K-Dense-AI/scientific-agent-skills --pin v2.63.0
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# Pin to a commit SHA
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gh skill install K-Dense-AI/scientific-agent-skills --pin abc123def
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@@ -194,6 +185,27 @@ gh skill update
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gh skill update --all
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```
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### Option 3: Agent Plugins (Cursor, Codex, and other plugin clients)
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This repository is a valid [Agent Plugins](https://agent-plugins.org/) 1.0.0 package: root [`plugin.json`](plugin.json) plus Agent Skills under `skills/`. Clients that support the standard discover every immediate child of `skills/` that contains a `SKILL.md`.
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**Cursor** — symlink or copy the repo into the local plugins directory, then reload:
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```bash
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mkdir -p ~/.cursor/plugins/local
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ln -s "$(pwd)" ~/.cursor/plugins/local/scientific-agent-skills
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```
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Restart Cursor or run **Developer: Reload Window**, then confirm the plugin and its skills appear under **Customize**. See [Cursor plugins](https://cursor.com/docs/plugins).
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**Codex** — install from a local checkout (confirm the current CLI flag names in Codex docs):
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```bash
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codex plugins install .
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```
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Compatible clients (Cursor, Codex, GitHub Copilot, VS Code, Kiro, and others listed at [agent-plugins.org](https://agent-plugins.org/compatible-clients)) share the same package layout; installation UX stays client-specific.
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### Other Agent Skills hosts (OpenClaw, NemoClaw, Pi, Hermes, …)
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Agent hosts differ in install paths, discovery settings, and support for optional frontmatter fields. `npx skills add` (Option 1) commonly installs into the `~/.agents/skills/` convention, with project-scoped installs under `.agents/skills/`; confirm both paths against your host's current documentation. To install manually on a host configured to scan one of those locations:
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@@ -209,7 +221,7 @@ For Hermes versions that support skill taps, add the repository as a tap:
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hermes skills tap add K-Dense-AI/scientific-agent-skills
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```
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Every `SKILL.md` has YAML frontmatter, but legacy and community skills vary in `metadata` formatting (block or flow style) and optional extension fields. Repository updates must keep `metadata.version` as a quoted numeric string and pass canonical `skills-ref validate ./skills/<skill-name>` checks. Hosts may interpret optional metadata and credential prompts differently, so verify behavior on the target host. Because 159 skills add up to a lot of standing context, consider installing a topical subset rather than the whole collection.
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Every `SKILL.md` has YAML frontmatter, but legacy and community skills vary in `metadata` formatting (block or flow style) and optional extension fields. Repository updates must keep `metadata.version` as a quoted numeric string and pass canonical `skills-ref validate ./skills/<skill-name>` checks. Hosts may interpret optional metadata and credential prompts differently, so verify behavior on the target host. Because 161 skills add up to a lot of standing context, consider installing a topical subset rather than the whole collection.
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> **NemoClaw note:** NemoClaw runs agents inside NVIDIA OpenShell with default-deny outbound networking. Skills are discovered and loaded normally, but any skill that needs the network — package installs via `uv`, or API calls (Exa, Parallel, Benchling, NCBI, Materials Project, …) — only works once the operator pre-approves the relevant domains in the OpenShell TUI.
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@@ -448,7 +460,7 @@ networks, and search GEO for similar patterns.
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## 📚 Available Skills
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This repository contains **159 scientific and research skills** organized across multiple domains. Each skill provides comprehensive documentation, code examples, and best practices for working with scientific libraries, databases, and tools.
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This repository contains **161 scientific and research skills** organized across multiple domains. Each skill provides comprehensive documentation, code examples, and best practices for working with scientific libraries, databases, and tools.
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### Skill Categories
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@@ -564,12 +576,13 @@ This repository contains **159 scientific and research skills** organized across
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- Citations: Citation Management, pyzotero
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- Illustration: Generate Image (AI image generation with FLUX.2 Pro and Gemini 3.1 Flash Image / Nano Banana 2)
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#### 🔬 **Scientific Databases & Data Access** (10 skills → 100+ databases total)
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#### 🔬 **Scientific Databases & Data Access** (11 skills → 100+ databases total)
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> A unified database-lookup skill provides deterministic REST API access to 78 public databases across all domains, with retrieval contracts, pagination/count reconciliation, and endpoint provenance. Dedicated skills cover specialized data platforms. Multi-database packages like BioServices (~40 bioinformatics services), BioPython (39 NCBI sub-databases via Entrez), and gget (20+ genomics databases) add further coverage.
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- Unified access: Database Lookup (78 databases spanning chemistry, genomics, clinical, pathways, patents, economics, and more — PubChem, ChEMBL, UniProt, PDB, AlphaFold, KEGG, Reactome, STRING, ClinVar, COSMIC, ClinicalTrials.gov, FDA, FRED, USPTO, SEC EDGAR, and dozens more — with auditable filters and provenance)
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- Cancer genomics: DepMap (cancer cell line dependencies, drug sensitivity, gene effect profiles)
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- Cancer imaging: Imaging Data Commons (NCI radiology & pathology datasets via idc-index)
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- Knowledge graph: PrimeKG (precision medicine knowledge graph — genes, drugs, diseases, phenotypes)
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- Biomedical knowledge graph search: [NCATS ARAX](skills/ncats-arax/) (bounded, Biolink-constrained one-hop and endpoint-pinned two-hop queries over knowledge graphs with up to five explicitly selected NCATS Translator providers, with provenance preservation)
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- Fiscal data: U.S. Treasury Fiscal Data (national debt, Treasury statements, auctions, exchange rates)
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- Scientific ML resource catalog: Hugging Science (curated index of datasets, models, blog posts, and interactive Spaces across 17 scientific domains — astronomy, biology, chemistry, climate, genomics, materials science, medicine, physics, scientific reasoning, and more — with usage patterns for `datasets`, `transformers`, and `gradio_client`)
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- Individual-level population genomics: OneKGPd (3,202-person high-coverage 1000 Genomes cohort queries)
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@@ -842,7 +855,7 @@ Recommended practice:
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title = {Scientific Agent Skills: A Comprehensive Collection of Scientific Tools for AI Agents},
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year = {2026},
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url = {https://github.com/K-Dense-AI/scientific-agent-skills},
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note = {159 skills covering databases, packages, integrations, and analysis tools}
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note = {161 skills covering databases, packages, integrations, and analysis tools}
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}
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```
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