Discover Agent Skills for data science & ml. Browse 61skills for Claude, ChatGPT & Codex.
Implements production-ready reinforcement learning algorithms using a unified, scikit-learn-style API for efficient agent training and evaluation.
Automates scientific hypothesis generation and testing from tabular datasets using LLMs and literature integration.
Enables autonomous tool calling for Grok models including X search, web search, and Python code execution.
Connects Claude Scientific Skills with the K-Dense Web platform to handle complex, multi-agent scientific research workflows.
Explains machine learning model predictions and feature importance using Shapley Additive exPlanations for transparent AI.
Accesses comprehensive financial market data including stocks, forex, cryptocurrency, and technical indicators for automated analysis.
Builds and orchestrates stateful Python-based AI agents with MCP integration and multi-agent patterns.
Queries the ClinicalTrials.gov API v2 to search, filter, and extract comprehensive clinical research data and trial details.
Accesses and analyzes data from over 20 genomic and proteomic databases through a unified interface.
Queries gene-drug interactions, clinical guidelines, and genetic variant annotations from the ClinPGx database for precision medicine applications.
Performs differential gene expression analysis for bulk RNA-seq data using Python-based DESeq2 workflows.
Performs real-time sentiment analysis on Twitter/X content using Grok's native integration and natural language processing.
Generates and customizes professional-grade static, animated, and interactive visualizations using Python's foundational plotting library.
Builds machine learning models and embeddings for genomic interval data to enable similarity searches, clustering, and single-cell analysis.
Streamlines the development, deployment, and management of serverless bioinformatics workflows on the LatchBio platform.
Optimizes data processing and analysis workflows using the high-performance Polars DataFrame library.
Simulates high-performance computational fluid dynamics using pseudospectral methods and optimized Python solvers.
Analyzes and visualizes high-throughput sequencing data including ChIP-seq, RNA-seq, and ATAC-seq.
Generates high-resolution 4K images, renders precise text, and performs conversational image editing using the Gemini 3 Pro Image model.
Develops and trains Graph Neural Networks (GNNs) using the PyTorch Geometric library for irregular data structures and geometric deep learning.
Provides direct access to the KEGG REST API for biological pathway analysis, gene mapping, and metabolic research.
Streamlines deep learning development by organizing PyTorch code into scalable, boilerplate-free Lightning modules and automated training workflows.
Provides comprehensive tools for phylogenetic tree manipulation, evolutionary analysis, and high-quality biological data visualization.
Manages and analyzes microscopy data through the OMERO Python API for scientific imaging and high-content screening workflows.
Evaluates scientific research rigor and evidence quality using standardized frameworks like GRADE and Cochrane.
Transforms chemical structures into machine learning-ready numerical features using a library of over 100 featurizers and pretrained models.
Transforms monolithic Python research code and notebooks into modular, production-ready package structures.
Performs precise unit conversions, dimensional analysis, and unit-aware arithmetic using the Pint library.
Builds process-based discrete-event simulations in Python to model complex systems with resource contention and time-based events.
Optimizes vector search and RAG applications through intelligent embedding model selection and advanced document chunking strategies.
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