Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Analyzes and visualizes high-throughput sequencing data including ChIP-seq, RNA-seq, and ATAC-seq.
Simulates high-performance computational fluid dynamics using pseudospectral methods and optimized Python solvers.
Optimizes data processing and analysis workflows using the high-performance Polars DataFrame library.
Streamlines the development, deployment, and management of serverless bioinformatics workflows on the LatchBio platform.
Builds machine learning models and embeddings for genomic interval data to enable similarity searches, clustering, and single-cell analysis.
Generates and customizes professional-grade static, animated, and interactive visualizations using Python's foundational plotting library.
Implements adaptive learning and high-speed memory patterns for self-improving Claude Code agents using AgentDB.
Deploys and manages a self-hosted AI infrastructure stack including LLM proxies, inference servers, vector databases, and observability tools.
Performs real-time sentiment analysis on Twitter/X content using Grok's native integration and natural language processing.
Provides expert guidance and implementation patterns for training large-scale Mixture-of-Experts (MoE) models using enterprise-grade Reinforcement Learning.
Performs differential gene expression analysis for bulk RNA-seq data using Python-based DESeq2 workflows.
Generates customized Jupyter notebook practice challenges for Python algorithms and pandas data manipulation.
Queries gene-drug interactions, clinical guidelines, and genetic variant annotations from the ClinPGx database for precision medicine applications.
Accesses and analyzes data from over 20 genomic and proteomic databases through a unified interface.
Automatically synchronizes the latest LLM model specifications, pricing, and API documentation to ensure optimal architecture decisions.
Queries the ClinicalTrials.gov API v2 to search, filter, and extract comprehensive clinical research data and trial details.
Architects sophisticated LLM applications using LangChain patterns for agents, memory management, and complex tool integration.
Builds and orchestrates stateful Python-based AI agents with MCP integration and multi-agent patterns.
Implements comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and LLM-as-judge patterns.
Accesses comprehensive financial market data including stocks, forex, cryptocurrency, and technical indicators for automated analysis.
Optimizes LLM context windows through compaction, masking, and caching strategies to maximize performance and minimize token costs.
Explains machine learning model predictions and feature importance using Shapley Additive exPlanations for transparent AI.
Implements advanced prompt engineering techniques to optimize LLM performance, reliability, and output controllability in production environments.
Implements comprehensive evaluation frameworks for LLM applications using automated metrics, human feedback, and benchmarking.
Optimizes LLM context windows through strategic compaction, masking, and caching to improve model performance and reduce costs.
Connects Claude Scientific Skills with the K-Dense Web platform to handle complex, multi-agent scientific research workflows.
Enables high-quality text and image generation using a reverse-engineered Gemini Web API interface.
Enables autonomous tool calling for Grok models including X search, web search, and Python code execution.
Designs and implements sophisticated LLM applications using the LangChain framework for agents, memory management, and modular workflows.
Designs and implements sophisticated LLM applications using the LangChain framework for agents, memory, and complex workflows.
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