Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Automates IGV snapshot generation for visualizing genomic alignments and variant calls in BAM files.
Generates high-quality images from text prompts using Google Gemini 3 Pro via the fal.ai API.
Builds production-ready RAG systems and semantic search using optimized Gemini embedding-001 models and vector storage patterns.
Builds type-safe, composable LLM applications in Ruby using the DSPy framework to program AI behavior instead of manual prompting.
Streamlines single-cell transcriptomics workflows using standardized scverse, AnnData, and Scanpy implementation patterns.
Implements sophisticated LLM-as-judge methodologies to evaluate and compare AI model outputs with high reliability and bias mitigation.
Implements production-grade LLM-as-a-judge patterns to evaluate model outputs with high reliability and bias mitigation.
Builds, configures, and deploys native Streamlit data applications directly within the Snowflake Data Cloud.
Implements sophisticated, multi-layered memory architectures including knowledge graphs and temporal persistence for autonomous AI agents.
Implements advanced memory architectures for AI agents to maintain session continuity and manage structured entity relationships.
Builds and packages portable AI agents that operate across multiple LLM frameworks and deployment targets without vendor lock-in.
Generates interactive statistical and scientific visualizations using Plotly Express and Graph Objects APIs.
Analyzes and validates protein structures, interprets AlphaFold predictions, and performs comparative molecular modeling.
Builds robust AI applications using OpenAI's Agents SDK with multi-agent orchestration, voice capabilities, and advanced error prevention.
Implements Google Gemini File Search to build managed RAG systems with automatic document chunking and semantic search.
Generates structured, evidence-driven Product Requirements Documents (PRDs) specifically tailored for Machine Learning workflows and experiments.
Builds and validates sophisticated Bayesian probabilistic models using the PyMC library for advanced statistical inference.
Systematically assesses medical research proposals to quantify their impact on patient outcomes, clinical decision-making, and healthcare systems.
Automates protein testing and validation through a cloud laboratory platform for high-throughput protein design workflows.
Manages Open WebUI instances via Podman to provide a browser-based chat interface for Ollama LLM models.
Facilitates direct REST API operations for Ollama using Python to manage models and execute generation tasks.
Manages LocalAI services via Podman to provide OpenAI-compatible local model inference with full GPU acceleration.
Provides AI-ready datasets and benchmarks for drug discovery, including ADME, toxicity, and molecular generation tasks.
Streamlines computational molecular biology tasks including sequence analysis, biological file parsing, and genomic database integration.
Accesses and analyzes comprehensive pharmaceutical data, including drug properties, interactions, molecular targets, and chemical structures from DrugBank.
Accesses the NIH Metabolomics Workbench database to query metabolite structures, experimental study data, and standardized nomenclature.
Manages local LLM inference using Ollama and Podman Quadlet with full GPU acceleration support.
Provides ultra-fast semantic vector search and intelligent document retrieval using AgentDB's high-performance HNSW indexing.
Conducts high-performance computational fluid dynamics (CFD) simulations using Python-based pseudospectral methods and MPI parallelization.
Manages multi-instance JupyterLab environments with hardware-accelerated GPU support via Podman Quadlet.
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