Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Provides standardized C++20 implementations for high-performance numerical computing, matrix operations, and parallel I/O.
Axiomatizes the directed interval 0 → 1 to model irreversible processes and time-directed homotopy in synthetic infinity-categories.
Evaluates research rigor and scientific claims by assessing methodology, statistical validity, and potential biases using standardized frameworks.
Constructs, validates, and exports hierarchical data structures for qualitative research using the Gioia methodology.
Performs transcription factor footprinting and differential binding detection on ATAC-seq data using the TOBIAS framework.
Performs specialized biological validation for ChIP-seq data by calculating cross-correlation metrics and fraction of reads in peaks.
Implements intrinsic motivation for AI agents by rewarding compression progress and the discovery of learnable patterns.
Performs ultra-fast portfolio backtesting and trading strategy analysis using the Polars library.
Optimizes trade execution using advanced algorithms like TWAP, VWAP, and Iceberg orders to minimize market impact and slippage.
Synthesizes multiple advanced theoretical frameworks from world-class researchers to solve complex problems through high-level meta-reasoning.
Implements interventional and counterfactual reasoning patterns for deliberate System 2 deep learning and causal world modeling.
Generates structured plans to decompose complex AI include chains into modular, reusable components.
Evaluates research rigor, methodology, and statistical validity to perform critical analysis of scientific claims.
Composes complex 3D environments and terrains for robotic simulation and reinforcement learning training.
Provides a unified framework for humanoid robot development, reinforcement learning training, and sim-to-real deployment.
Manipulates, analyzes, and visualizes phylogenetic trees and genomic data with the Environment for Tree Exploration (ETE) framework.
Integrates polynomial functors and category-theoretic operads to model complex interaction patterns and dynamical systems within AI workflows.
Processes and analyzes complex physiological signals including ECG, EEG, and EDA for psychophysiology research and medical data science.
Orchestrates a polyglot environment for social network analysis and multimedia processing using Clojure, Julia, and DuckDB.
Implements high-performance persistent memory and learning patterns for AI agents using AgentDB.
Deploys and manages cloud-based AI agent swarms using event-driven workflow automation and intelligent coordination.
Enables Claude to perform complex scientific research by providing access to over 600 bioinformatics, genomics, and cheminformatics tools.
Implements high-performance adaptive learning and experience replay for AI agents using AgentDB's ultra-fast vector storage.
Performs Gene Ontology and KEGG pathway enrichment analysis from genomic regions or gene lists with automated R-based visualizations.
Trains and deploys complex neural networks across distributed E2B sandbox environments directly within Claude.
Analyzes protein-mediated chromatin interactions to identify and visualize regulatory communities from ChIA-PET datasets.
Streamlines the development of data processing pipelines, ABAP integrations, and machine learning scenarios within SAP Data Intelligence Cloud.
Streamlines in-database machine learning workflows within SAP HANA using the Python hana-ml library.
Streamlines the deployment and management of enterprise AI/ML workloads and LLM orchestration on SAP BTP.
Validates the biological quality of ATAC-seq data by calculating metrics like TSS enrichment, fragment size distribution, and peak overlap.
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