Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Predicts 3D binding poses for protein-ligand complexes using state-of-the-art diffusion-based deep learning.
Explains and implements core Transformer architecture components for LLM development, fine-tuning, and model analysis.
Facilitates automated protein testing and validation through cloud-based laboratory services and sequence optimization tools.
Streamlines molecular machine learning workflows for drug discovery, property prediction, and materials science using graph neural networks.
Evaluates LLM outputs and optimizes prompts using Evidently.ai metrics and LLM-as-a-judge patterns.
Automates protein testing and validation workflows through cloud-based laboratory services and sequence optimization tools.
Integrates Google's Gemini AI models into Claude Code for advanced reasoning and multi-model code analysis.
Simplifies molecular cheminformatics and drug discovery workflows using a Pythonic interface for RDKit.
Optimizes LLM fine-tuning using LoRA, QLoRA, and Unsloth to drastically reduce memory requirements and accelerate training cycles.
Provides a clean, Pythonic interface for interacting with Ollama to handle text generation, chat completions, and model management.
Applies advanced machine learning techniques to chemistry, biology, and materials science using the DeepChem library.
Performs constraint-based reconstruction and analysis of metabolic models for systems biology and metabolic engineering.
Aligns AI models with human preferences using Direct Preference Optimization to improve reasoning and response quality without explicit reward models.
Automates laboratory workflows and controls liquid handling robots, plate readers, and other lab equipment using a hardware-agnostic Python SDK.
Provides rapid, unified access to over 20 genomic and proteomic databases for sequence analysis and protein structure prediction.
Optimizes large language models for efficient inference and training using various precision types and memory estimation techniques.
Simplifies molecular cheminformatics workflows by providing a Pythonic wrapper around RDKit with sensible defaults and parallel processing.
Queries the NCBI Gene database to retrieve comprehensive genetic information, sequences, and functional annotations via E-utilities and Datasets APIs.
Integrates ChromaDB capabilities for building AI applications with persistent memory and semantic search.
Provides comprehensive access to the Human Metabolome Database (HMDB) for metabolite identification, chemical analysis, and clinical research.
Streamlines the supervised fine-tuning of Large Language Models using Unsloth for optimized performance and reasoning model development.
Simplifies building LLM-powered applications by providing standardized abstractions for prompt engineering, model orchestration, and structured output parsing.
Generates insightful, professional-grade charts and interactive dashboards using industry-standard libraries and design principles.
Accesses and retrieves genomic data, nucleotide sequences, and metadata from the European Nucleotide Archive (ENA) via REST APIs and FTP.
Builds, simulates, and optimizes quantum circuits for execution on leading quantum hardware and simulators.
Provides a comprehensive toolkit for protein language models to design, predict, and analyze protein sequences and structures.
Provides programmatic access to over 40 bioinformatics web services and databases for integrated biological data analysis.
Manages local Ollama inference servers using Podman Quadlet to provide GPU-accelerated LLM capabilities.
Generates interactive, publication-quality scientific and statistical visualizations for Python data analysis.
Accesses and analyzes real-time SEC filings and financial statements with token-efficient data retrieval.
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