Explore our collection of Agent Skills to enhance your AI workflow.
Implements professional machine learning workflows in Python using scikit-learn for classification, regression, clustering, and data preprocessing.
Manage large-scale N-dimensional arrays with chunking, compression, and cloud-native storage for scientific computing workflows.
Accesses and analyzes functional genomics data from the NCBI Gene Expression Omnibus (GEO) repository.
Manages microscopy data and metadata via the OMERO Python API for scientific imaging and high-content screening workflows.
Accelerates drug discovery and molecular research using graph neural networks and PyTorch-based machine learning.
Converts chemical structures into high-quality numerical features for molecular machine learning and cheminformatics tasks.
Queries and retrieves comprehensive gene information from NCBI databases for genomic research and functional analysis.
Analyzes single-cell omics data using deep generative models for batch correction, multimodal integration, and differential expression.
Manages annotated data matrices for single-cell genomics and large-scale biological datasets using the AnnData Python framework.
Empowers AI agents to conduct scientific research by providing standardized access to over 600 bioinformatics, cheminformatics, and genomics tools.
Analyzes whole-slide pathology images and multiparametric imaging data using a comprehensive computational pathology toolkit.
Analyzes biological data including sequences, phylogenetic trees, and microbial community diversity using the scikit-bio Python library.
Accelerates data processing and analysis using the high-performance Polars DataFrame library for Python and Rust.
Performs real-time, AI-powered web searches and scientific literature discovery using Perplexity models via OpenRouter.
Queries the NHGRI-EBI GWAS Catalog to retrieve genetic variant associations, study metadata, and comprehensive summary statistics for genomic research.
Queries the ChEMBL database for bioactive molecules, drug targets, and medicinal chemistry data to support drug discovery research.
Automates laboratory workflows and hardware control using a hardware-agnostic Python interface for liquid handlers and analytical equipment.
Performs differential gene expression analysis on bulk RNA-seq data using the DESeq2 framework within Python.
Automates comprehensive end-to-end testing for the Kosmos autonomous AI scientist project across local and cloud LLM providers.
Implements high-performance coding patterns, caching strategies, and database query optimizations to reduce latency and improve scalability.
Diagnoses and resolves recurring software failure patterns across dependencies, environments, networking, and concurrency.
Builds, analyzes, and visualizes complex networks and graph data structures using the Python NetworkX library.
Integrates Bitcoin SV micropayments and BRC-31 authentication into Claude Code for seamless paid API interactions.
Implements a scientific, hypothesis-driven approach to identify root causes and resolve complex software failures.
Facilitates professional requirements gathering through stakeholder interviews, prioritization frameworks, and structured acceptance criteria.
Implements industry-standard testing strategies and patterns to improve code quality and test suite reliability.
Guides the implementation of Test-Driven Development using the Red-Green-Refactor cycle and industry-standard testing patterns.
Implements robust security patterns including input validation, secrets management, and secure authentication to protect applications from common vulnerabilities.
Accesses and analyzes protein-protein interaction networks and functional enrichment data using the STRING database API.
Audits source code for the most critical web application security risks with actionable remediation patterns and checklists.
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