Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Detects hardware capabilities and provides optimized computational strategies for resource-intensive scientific tasks.
Generates testable, evidence-based scientific hypotheses and experimental designs across multiple research domains.
Optimizes vector database performance by tuning HNSW parameters, quantization strategies, and scaling configurations for high-efficiency similarity search.
Generates publication-ready, journal-standard scientific figures and multi-panel layouts using Matplotlib, Seaborn, and Plotly.
Persists knowledge and learned patterns across autonomous coding sessions using Graphiti-based memory management.
Generates testable, evidence-based scientific hypotheses and structured experimental designs across research domains.
Integrates Google’s Gemini AI capabilities into Claude Code for multimodal tasks, advanced code analysis, and automated tool execution.
Evaluates the rigor of scientific research by assessing methodology, statistical validity, and potential biases using established frameworks like GRADE and Cochrane.
Implement and automate comprehensive evaluation strategies for Large Language Model applications using metrics, human feedback, and LLM-as-judge patterns.
Conducts systematic, multi-database literature reviews and meta-analyses with verified academic citations and professional PDF output.
Designs and implements sophisticated LLM applications using LangChain 1.x and LangGraph for advanced agentic workflows and state management.
Builds and orchestrates end-to-end MLOps pipelines from data preparation through production model deployment.
Automates the creation, editing, and analysis of complex Excel spreadsheets with support for dynamic formulas and financial modeling standards.
Automates professional spreadsheet creation, financial modeling, and data analysis with dynamic formulas and industry-standard formatting.
Facilitates the development and migration of Python-based AI agents using LangGraph v1 and LangChain v1 standards.
Manages high-fidelity voice cloning workflows, library organization, and audio optimization for synthetic speech generation.
Automates Oxford Nanopore sequence alignment, reference genome management, and edit distance computations for genomic data analysis.
Generates and validates recursive string diagrams using category theory primitives for complex system modeling.
Implements production-ready RAG pipelines and multi-step agent workflows using LangChain, LangGraph, and LangSmith templates.
Accesses the NIH Metabolomics Workbench REST API to retrieve comprehensive metabolomics study data, metabolite structures, and standardized RefMet nomenclature.
Provides production-ready machine learning templates and training workflows for classification, text generation, and financial analysis.
Configures and optimizes Google Cloud Platform environments for BigQuery ML and Vertex AI training workloads.
Reviews machine learning and deep learning code to optimize model architecture, training loops, and data pipelines for PyTorch and TensorFlow.
Orchestrates complex multi-agent systems using Microsoft AutoGen and Semantic Kernel with local LLM support.
Provides comprehensive documentation and implementation patterns for building AI-powered applications using the Vercel AI SDK.
Facilitates direct interaction with OpenAI GPT models through a command-line interface within the Claude environment.
Develops, optimizes, and executes quantum circuits on IBM Quantum hardware and simulators using the industry-standard Qiskit framework.
Sets up comprehensive monitoring dashboards using TensorBoard and Weights & Biases to track machine learning experiments in real-time.
Extracts and validates federated taxonomy tags from text to enable multi-hop graph traversal and structured memory storage.
Orchestrates complex multi-agent AI workflows using standardized coordination patterns and robust infrastructure primitives.
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