K-Dense-AI

A multi-objective optimization framework featuring NSGA-II, NSGA-III, MOEA/D, Pareto fronts, and constraint handling. It includes benchmarks like ZDT and DTLZ for engineering design and optimization problems.

Comprehensive citation management for academic research, allowing you to search Google Scholar and PubMed, extract metadata, validate citations, and generate BibTeX entries. Use this skill to find papers, verify citations, convert DOIs, or ensure reference accuracy in scientific writing.

Electronic lab notebook API integration. Access notebooks, manage entries/attachments, backup notebooks, and integrate with Protocols.io/Jupyter/REDCap for programmatic ELN workflows.

Google quantum computing framework. Ideal for Google Quantum AI hardware, designing noise-aware circuits, and quantum characterization experiments, focusing on noise modeling and low-level circuit design.

Infers gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). It's used to analyze transcriptomics data (bulk/single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions, supporting distributed computation for large datasets.

Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.

Programmatically query the CELLxGENE Census (61M+ cells) to get expression data across tissues, diseases, or cell types from the largest curated single-cell atlas. It is best for population-scale queries and reference atlas comparisons.

This skill demonstrates using the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval, covering various assays like binding, screening, BLI/SPR, and thermostability, and is triggered by relevant keywords or code imports.

This skill provides the data structure for annotated matrices in single-cell analysis, ideal for .h5ad files or integration with the scverse ecosystem. For analysis workflows, use scanpy; for probabilistic models, scvi-tools; and for population-scale queries, cellxgene-census.

Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

Observes the user's screen via screenpipe to detect repeated research workflows, matching them against existing scientific-agent-skills and drafting new ones for uncovered patterns. Use this skill when the user asks to analyze their recent work and propose skills based on their actual activities.

Benchling Python SDK and REST API integration for registry entities, inventory, ELN entries, workflows, Benchling Apps, and Data Warehouse queries. Use to automate lab data with benchling-sdk or the v2 API.

Use this skill for working with Brain Imaging Data Structure (BIDS) datasets, including organizing neuroscience and biomedical data, querying layouts, validating compliance, converting DICOM to BIDS, and creating BIDS derivatives.

A comprehensive molecular biology toolkit for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access. Ideal for batch processing, custom bioinformatics pipelines, and BLAST automation.

A unified Python interface for over 40 bioinformatics services, ideal for querying multiple databases like UniProt, KEGG, ChEMBL, and Reactome in a single workflow with a consistent API. It excels in cross-database analysis and ID mapping across services.

This skill orchestrates end-to-end bulk RNA-seq analysis, processing raw FASTQ reads through QC, trimming, alignment, and quantification to assemble a gene-level counts matrix. It then performs differential expression, pathway enrichment, and generates publication-ready figures.

Generates professional clinical decision support (CDS) documents for pharmaceutical and clinical research, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). It supports GRADE evidence grading, statistical analysis, and biomarker integration.

Write comprehensive clinical reports, including case reports, diagnostic reports, clinical trial reports, and patient documentation. Full support is provided with templates, regulatory compliance, and validation tools.

Constraint-based metabolic modeling (COBRA) covers FBA, FVA, gene knockouts, flux sampling, and SBML models for systems biology and metabolic engineering analysis.

Facilitate a multi-perspective Mind Council deliberation for any question, decision, or creative challenge, providing diverse viewpoints and aiding in complex problem-solving.

Distributed computing for larger-than-RAM pandas/NumPy workflows, scaling existing code beyond memory or across clusters. Ideal for parallel file processing, distributed ML, and integration with pandas.

Search 78 public scientific, biomedical, materials science, and economic databases via REST APIs, covering fields like physics, chemistry, biology, and materials.

Molecular ML for property prediction (ADMET, toxicity) using diverse featurizers and pre-built datasets, supporting traditional ML or GNNs. It's excellent for quick experiments with pre-trained models and extensive featurization, often leveraging MoleculeNet benchmarks.

NGS analysis toolkit for BAM to bigWig conversion, QC (correlation, PCA, fingerprints), and visualization of ChIP-seq, RNA-seq, and ATAC-seq data through heatmaps/profiles (TSS, peaks).

Extract cognitive patterns and thinking fingerprints from any text. Use this skill to analyze how someone thinks, understand cognitive style, profile writing or speech patterns, or compare thinking styles between people.

DNAnexus is a cloud genomics platform for building apps/applets, managing data (upload/download), and running workflows using the dxpy Python SDK. It supports FASTQ/BAM/VCF for genomics pipeline development and execution.

This skill is for creating, reading, editing, or manipulating Word documents (.docx), including tasks like formatting professional documents, extracting content, or managing images.

Phylogenetic tree toolkit (ETE) for phylogenomics, offering tree manipulation (Newick/NHX), evolutionary event detection, orthology/paralogy, NCBI taxonomy integration, and visualization (PDF/SVG).

This web toolkit, powered by Exa, is tuned for scientific and technical content. Use it for web search, including semantic lookups and academic filtering, or for fetching and extracting URL content like pages, articles, and academic PDFs.

Performs comprehensive exploratory data analysis on scientific data files across 200+ formats. It automatically detects file types and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations to understand data structure, content, and quality.

Parses FCS (Flow Cytometry Standard) files v2.0-3.1. Extracts events as NumPy arrays, reads metadata/channels, and converts to CSV/DataFrame for flow cytometry data preprocessing.

A Python framework for computational fluid dynamics simulations, supporting Navier-Stokes (2D/3D), shallow water, and stratified flows, as well as turbulence and vortex dynamics analysis. It offers pseudospectral methods with FFT, HPC support, and comprehensive output analysis.

Generate or edit images using AI models (FLUX, Nano Banana 2). Use for general-purpose image generation, including photos, illustrations, artwork, and concept art, but not technical diagrams. For technical diagrams, use the scientific-schematics skill.

This skill is for machine learning tasks involving genomic interval data (BED files), such as training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), or building consensus peaks. It applies to BED file collections, scATAC-seq data, and chromatin accessibility datasets.

This comprehensive geospatial science skill covers remote sensing, GIS, spatial analysis, machine learning for earth observation, and over 30 scientific domains. It supports satellite imagery processing, vector and raster data operations, spatial statistics, point cloud processing, network analysis, and cloud-native workflows.

A Python library for working with geospatial vector data like shapefiles, GeoJSON, and GeoPackage files. It's used for spatial analysis, geometric operations, coordinate transformations, and other tasks involving vector geographic data, supporting PostGIS databases and interactive maps.

This skill detects and reports available system resources (CPU cores, GPUs, memory, disk space) at the start of computationally intensive scientific tasks. It generates a JSON file with resource information and strategic recommendations to guide computational approach decisions, such as using parallel processing or out-of-core computing.

Perform fast CLI/Python queries across 20+ bioinformatics databases for quick lookups of gene info, BLAST searches, AlphaFold structures, and enrichment analysis. It's best for interactive exploration and simple queries, with biopython or bioservices recommended for batch processing or advanced workflows.

Submit and manage protocols on Ginkgo Bioworks Cloud Lab (cloud.ginkgo.bio), a web-based interface for autonomous lab execution on Reconfigurable Automation Carts (RACs). Use for cell-free protein expression, fluorescent pixel art generation, or interacting with Ginkgo Cloud Lab services, covering protocol selection, input preparation, pricing, and ordering.

Analyze and engineer protein glycosylation. Scan sequences for N-glycosylation sequons (N-X-S/T), predict O-glycosylation hotspots, and access curated glycoengineering tools (NetOGlyc, GlycoShield, GlycoWorkbench) for glycoprotein engineering, therapeutic antibody optimization, and vaccine design.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. It's used for genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

This tool provides lightweight WSI tile extraction and preprocessing, ideal for basic slide processing, tissue detection, and stain normalization for H&E images. It's best suited for simple pipelines, dataset preparation, and quick tile-based analysis, with pathml recommended for advanced applications.

Hugging Science is a curated catalog of scientific datasets, models, blog posts, and interactive Spaces, designed for users engaged in AI/ML work across various scientific domains like biology, chemistry, and physics.

Automated LLM-driven hypothesis generation and testing on tabular datasets. Use to systematically explore patterns in empirical data, combining literature insights with data-driven hypothesis testing.

Formulates structured, testable hypotheses from experimental observations or data, including predictions, proposed mechanisms, and experimental designs, following the scientific method.

Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research without authentication, querying by metadata, visualizing in browser, and checking licenses.

Create professional infographics with Nano Banana Pro AI, featuring smart iterative refinement and Gemini 3 Pro for quality review. It integrates research and web search for accurate data, supporting 10 infographic types, 8 industry styles, and colorblind-safe palettes.

A comprehensive toolkit for preparing ISO 13485 certification documentation for medical device Quality Management Systems, assisting with gap analysis, Quality Manuals, procedures, Medical Device Files, and understanding ISO 13485 requirements.