Data Science & ML Claude 技能

ML PRD Generator

Generates structured, evidence-driven Product Requirements Documents (PRDs) specifically tailored for Machine Learning workflows and experiments.

PyMC Bayesian Modeling

Builds and validates sophisticated Bayesian probabilistic models using the PyMC library for advanced statistical inference.

Clinical Value Evaluator

Systematically assesses medical research proposals to quantify their impact on patient outcomes, clinical decision-making, and healthcare systems.

Adaptyv Protein Engineering

Automates protein testing and validation through a cloud laboratory platform for high-throughput protein design workflows.

PyTDC Therapeutics Data Commons

Provides AI-ready datasets and benchmarks for drug discovery, including ADME, toxicity, and molecular generation tasks.

Biopython Molecular Biology

Streamlines computational molecular biology tasks including sequence analysis, biological file parsing, and genomic database integration.

QIG Purity Guardian

Enforces E8 architecture standards and QIG purity protocols within the Pantheon development ecosystem.

Rust Machine Learning & AI

Guides the development of high-performance ML and AI applications in Rust using memory-efficient patterns and GPU acceleration.

Book SFT & Style Transfer Pipeline

Builds high-quality fine-tuning datasets from literary works to train AI models in specific authorial voices and writing styles.

Context Degradation Diagnostics

Diagnoses and mitigates AI agent performance failures caused by long-context attention loss, poisoning, and informational clash.

Multi-Agent Architecture Patterns

Designs and implements sophisticated multi-agent systems using supervisor, swarm, and hierarchical patterns to solve complex context management challenges.

Context Engineering Fundamentals

Provides foundational expertise in context engineering to optimize AI agent performance and manage token usage effectively.

BDI Mental State Modeling

Transforms external RDF context into formal Belief-Desire-Intention (BDI) models to enable rational agency and explainable reasoning in AI agents.

LLM Project Development Methodology

Architects and optimizes LLM-powered applications using structured methodologies, pipeline design, and agent-assisted development patterns.

Context Optimization

Optimizes AI agent context through compression, masking, and strategic partitioning to maximize token efficiency and model performance.

Data Visualization Expert

Implements high-performance, accessible, and perceptually accurate data visualizations using industry-standard algorithms and best practices.

Denario Academic Research Assistant

Automates the end-to-end scientific research lifecycle from data analysis and hypothesis generation to publication-ready LaTeX manuscripts.

Denario Scientific Research Automation

Automates end-to-end scientific research workflows from data analysis and hypothesis generation to publication-ready LaTeX manuscripts.

Biomni Biomedical AI Agent

Automates complex biomedical research tasks including drug discovery, genomics analysis, and CRISPR screening design using an autonomous AI agent framework.

DNAnexus Integration

Integrates Claude with the DNAnexus cloud platform to build genomic apps, manage biomedical data, and automate bioinformatics workflows using the dxpy SDK.

DrugBank Database & Pharmacology Analysis

Access and analyze comprehensive pharmaceutical data from DrugBank for drug discovery, pharmacology research, and chemical property analysis.

ClinVar Database Navigator

Queries and interprets NCBI ClinVar data to identify genetic variant clinical significance and pathogenicity.

LLM Application Development

Builds robust AI-powered applications using advanced prompt engineering, RAG patterns, and multi-provider LLM integrations.

AI Model Validation

Validates AI model checkpoints against datasets to measure performance and benchmark key metrics.

arXiv Daily Paper Reader

Automates the discovery and retrieval of the latest research papers from arXiv across multiple scientific categories.

Hyperparameter Sweep

Systematically optimizes machine learning model performance by searching for the ideal hyperparameter configurations.

Neural Network Trainer

Executes and monitors neural network training runs using best-practice configurations and mandatory logging backends.

Training Curve Interpreter

Analyzes machine learning training logs to visualize loss curves, detect training issues, and provide diagnostic insights.

Scaling Analysis & Law Investigation

Analyzes and predicts AI model performance by empirically testing relationships between model size, dataset volume, and compute budget.

Experiment Design Coach

Guides the creation of rigorous, well-controlled experiments for machine learning and data science projects.