Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Analyzes single-cell omics data using probabilistic models for tasks like batch correction, dimensionality reduction, and differential expression.
Create publication-quality charts, graphs, and complex data visualizations using Python's foundational plotting library.
Automates scientific hypothesis generation and empirical testing using large language models and research literature integration.
Performs advanced molecular modeling, chemical property calculation, and substructure analysis using the RDKit toolkit.
Analyzes dynamical systems to identify measures preserved by flow and evaluate qualitative stability behavior.
Evaluates the credibility and quality of information sources using standardized scientific frameworks and the CRAAP test.
Quantifies and extracts financial value from system inefficiencies by modeling transitions between selfish equilibria and optimal states.
Simulates complex physical systems using acausal equation-based modeling and Wolfram Language integration.
Performs constraint-based reconstruction and analysis (COBRA) of metabolic models for systems biology and metabolic engineering.
Integrates Claude with the OMERO platform to manage, analyze, and automate bioimaging data workflows using the Python API.
Automates biological computation tasks including sequence analysis, structural bioinformatics, and programmatic NCBI database access.
Deploys the GNU Scheme ecosystem to build secure, distributed cognitive agents using Active Inference and WebAssembly.
Analyzes and maps the qualitative transformations between dynamical systems using topological semi-conjugacy methods.
Implements self-indexing automata and metabolic computation models at the intersection of quantum and classical logic.
Generates professional, publication-ready clinical decision support documents and biomarker-stratified cohort analyses for pharmaceutical and clinical research.
Analyzes and manipulates data patterns using Gestalt perceptual principles and topological logic to identify emergent structures.
Provides high-performance, bidirectional data navigation and transformation for Julia collections, S-expressions, and ACSets.
Orchestrates complex AI skill ecosystems using category theory, topological synthesis, and deterministic GF(3) conservation.
Performs high-dimensional geometric multi-resolution analysis with deterministic local reconstructability across MATLAB, Julia, and Python.
Verifies mathematical conservation laws and manages autopoietic logic within topological computational frameworks.
Generates and evolves topological code patterns through autopoietic interaction and color-based seeds.
Enables structured generation and algebraic composition of n-ary operations using colored operads.
Performs complex algebraic graph rewriting over Attributed C-Sets (ACSets) using DPO, SPO, and SqPO methodologies.
Implements massively parallel functional computation using interaction nets and GPU-accelerated graph reduction.
Decomposes complex computational problems into three GF(3)-balanced components for optimized parallel execution and sheaf-theoretic gluing.
Simulates and analyzes Last Passage Percolation models to study Tracy-Widom fluctuations, geodesics, and KPZ universality.
Maps and analyzes bidirectional observation relationships between agents using sheaf-theoretic consistency and multi-agent awareness graphs.
Builds and manages complex signal processing flowgraphs and custom Python blocks for Software Defined Radio (SDR) applications.
Implements high-performance LLVM-level automatic differentiation for Julia code on both CPU and GPU architectures.
Models and analyzes dynamical systems on graphs to evaluate qualitative behaviors like stability, sinks, and bifurcations.
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