AIエージェントの能力を拡張するClaudeスキルの完全なコレクションをご覧ください。
Solves complex single and multi-objective optimization problems using evolutionary algorithms and Pareto front analysis.
Implements reinforcement learning workflows including agent training, custom environment design, and model evaluation using Stable Baselines3.
Coordinates multiple specialized AI agents using a central supervisor pattern within LangGraph workflows.
Identifies architecture, ABI, and potential capabilities of unknown binary files and firmware blobs using fast fingerprinting techniques.
Generates sophisticated, master-level generative art and computational aesthetics using p5.js and seeded randomness.
Streamlines the creation of professional internal updates, reports, and company newsletters using standardized organizational formats.
Accesses ChEMBL's vast repository of bioactive molecules and drug discovery data for medicinal chemistry and pharmacology research.
Explores the Glide Template Store to provide design inspiration, implementation patterns, and data modeling guidance for no-code apps.
Facilitates the creation and optimization of modular Claude Code skills through best practices, structured anatomy, and context-efficient design patterns.
Manages issues, projects, and team workflows in Linear directly through the Claude Code environment.
Accesses the Kyoto Encyclopedia of Genes and Genomes (KEGG) REST API for biological pathway analysis and molecular interaction mapping.
Provides a comprehensive toolkit for creating, manipulating, and analyzing complex network structures and graph algorithms in Python.
Predicts accurate protein-ligand binding poses and 3D structures using state-of-the-art diffusion-based deep learning models.
Accesses and processes NCBI Gene Expression Omnibus (GEO) datasets for transcriptomics and functional genomics analysis.
Optimizes AI agent performance using Anthropic-aligned context engineering and prompt structuring principles.
Streamlines the implementation, evaluation, and deployment of classical machine learning models using the scikit-learn library.
Creates distinctive, production-grade frontend interfaces with a focus on high-quality aesthetics and creative UI/UX.
Performs deep static analysis on binary files to map structure, decompile code, and identify logic without execution.
Generates publication-quality static, animated, and interactive visualizations using Python's foundational plotting library.
Enables seamless programmatic access to UniProt for protein sequence retrieval, functional annotation, and biological database ID mapping.
Builds and manages process-based discrete-event simulations in Python to model complex systems like manufacturing, logistics, and network traffic.
Accesses and queries the Catalogue of Somatic Mutations in Cancer (COSMIC) to retrieve genomic data, mutational signatures, and cancer gene census information.
Processes and analyzes physiological signals including ECG, EEG, and EDA for psychophysiology research and clinical applications.
Orchestrates multiple parallel AI agents to compete on implementing the same design doc to ensure high-quality and varied code solutions.
Accesses over 600 scientific tools and datasets to automate research workflows across bioinformatics, genomics, and drug discovery.
Provides seamless command-line access to major knowledge sources and technical documentation including Wikipedia, Stack Exchange, and RFC documents.
Facilitates advanced biomedical literature research and programmatic access to the National Library of Medicine's PubMed database via E-utilities.
Queries the STRING API to analyze protein-protein interaction networks and perform functional enrichment for systems biology.
Manages the fundamental identity, response formatting, and operational workflows of your Personal AI Infrastructure.
Evaluates scientific manuscripts and grant proposals using systematic methodology, statistical rigor, and ethical standards.
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