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Agent skills
claudecode

Topic: claudecode

654 skills in this topic.

cellxgene-census Query the CELLxGENE Census (61M+ cells) programmatically. Use when you need expression data across tissues, diseases, or cell types from the largest curated single-cell atlas. Best for population-scale queries, reference atlas comparisons. For analyzing your own data use scanpy or scvi-tools.
K-Dense-AI/claude-scientific-skills 16,890
consciousness-council Run a multi-perspective Mind Council deliberation on any question, decision, or creative challenge. Use this skill whenever the user wants diverse viewpoints, needs help making a tough decision, asks for a council/panel/board discussion, wants to explore a problem from multiple angles, requests devil's advocate analysis, or says things like "what would different experts think about this", "help me think through this from all sides", "council mode", "mind council", or "deliberate on this". Also trigger when the user faces a dilemma, trade-off, or complex choice with no obvious answer.
K-Dense-AI/claude-scientific-skills 16,890
dask Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
K-Dense-AI/claude-scientific-skills 16,890
database-lookup Search 78 public scientific, biomedical, materials science, and economic databases via their REST APIs and return structured JSON results. Covers physics/astronomy (NASA, NIST, SDSS, SIMBAD, Exoplanet Archive), earth/environment (USGS, NOAA, EPA, OpenWeatherMap), chemistry/drugs (PubChem, ChEMBL, DrugBank, FDA, KEGG, DailyMed, ZINC, BindingDB), materials science (Materials Project, COD), biology/genomics (Reactome, BRENDA, UniProt, STRING, Ensembl, NCBI Gene, GEO, GTEx, PDB, AlphaFold, InterPro, ChEBI, BioGRID, Gene Ontology, QuickGO, NCBI Protein/Taxonomy, dbSNP, SRA, ENA, gnomAD, UCSC Genome, ENCODE, JASPAR, MouseMine, PRIDE, LINCS L1000, Human Protein Atlas, Human Cell Atlas, RummaGEO, Metabolomics Workbench, EMDB, Addgene), disease/clinical (COSMIC, Open Targets, ClinPGx, ClinicalTrials.gov, OMIM, ClinVar, GDC/TCGA, cBioPortal, DisGeNET, GWAS Catalog, Monarch, HPO), regulatory (FDA, USPTO, SEC EDGAR), economics/finance (FRED, BEA, BLS, Federal Reserve, World Bank, ECB, US Treasury, Alpha Vantage, Data Commons), and demographics (US Census, Eurostat, WHO). Use this skill whenever the user wants to look up compounds, drugs, proteins, genes, pathways, enzymes, gene expression, variants, clinical trials, patents, SEC filings, economic indicators, crystal structures, astronomical objects, earthquakes, weather, or any data from a public database API. Also trigger when the user mentions any database by name or asks about molecular properties, drug-target interactions, binding affinities, protein interactions, pathway membership, pharmacogenomics, economic time series, materials properties, commercially available compounds, virtual screening, compound purchasability, chemical libraries, building blocks, cancer genomics, somatic mutations, tumor mutation profiles, nucleotide sequences, genome assemblies, sequencing reads, ENA accessions, INSDC data, or wants to cross-reference entities across sources.
K-Dense-AI/claude-scientific-skills 16,890
diffdock Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction.
K-Dense-AI/claude-scientific-skills 16,890
dnanexus-integration DNAnexus cloud genomics platform. Build apps/applets, manage data (upload/download), dxpy Python SDK, run workflows, FASTQ/BAM/VCF, for genomics pipeline development and execution.
K-Dense-AI/claude-scientific-skills 16,890
gtars High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
K-Dense-AI/claude-scientific-skills 16,890
histolab Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
K-Dense-AI/claude-scientific-skills 16,890
labarchive-integration Electronic lab notebook API integration. Access notebooks, manage entries/attachments, backup notebooks, integrate with Protocols.io/Jupyter/REDCap, for programmatic ELN workflows.
K-Dense-AI/claude-scientific-skills 16,890
latchbio-integration Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
K-Dense-AI/claude-scientific-skills 16,890
matplotlib Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.
K-Dense-AI/claude-scientific-skills 16,890
neuropixels-analysis Neuropixels neural recording analysis. Load SpikeGLX/OpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen/IBL curation, AI-assisted visual analysis, for Neuropixels 1.0/2.0 extracellular electrophysiology. Use when working with neural recordings, spike sorting, extracellular electrophysiology, or when the user mentions Neuropixels, SpikeGLX, Open Ephys, Kilosort, quality metrics, or unit curation.
K-Dense-AI/claude-scientific-skills 16,890
pdf Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
K-Dense-AI/claude-scientific-skills 16,890
polars-bio High-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames. Overlap, nearest, merge, coverage, complement, subtract for BED/VCF/BAM/GFF intervals. Streaming, cloud-native, faster bioframe alternative.
K-Dense-AI/claude-scientific-skills 16,890
pptx Use this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates, layouts, speaker notes, or comments. Trigger whenever the user mentions "deck," "slides," "presentation," or references a .pptx filename, regardless of what they plan to do with the content afterward. If a .pptx file needs to be opened, created, or touched, use this skill.
K-Dense-AI/claude-scientific-skills 16,890
pymatgen Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.
K-Dense-AI/claude-scientific-skills 16,890
qiskit IBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware use cirq; for gradient-based quantum ML use pennylane; for open quantum system simulations use qutip.
K-Dense-AI/claude-scientific-skills 16,890
scanpy Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.
K-Dense-AI/claude-scientific-skills 16,890
scholar-evaluation Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable feedback.
K-Dense-AI/claude-scientific-skills 16,890
scientific-brainstorming Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.
K-Dense-AI/claude-scientific-skills 16,890
scikit-learn Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.
K-Dense-AI/claude-scientific-skills 16,890
stable-baselines3 Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.
K-Dense-AI/claude-scientific-skills 16,890
statistical-analysis Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.
K-Dense-AI/claude-scientific-skills 16,890
transformers This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
K-Dense-AI/claude-scientific-skills 16,890