Data Science & ML Agent Skills

Microsoft Agent Orchestrator

Orchestrates complex multi-agent systems using Microsoft AutoGen and Semantic Kernel with local LLM support.

Gioia Methodology

Constructs and validates hierarchical data structures for qualitative research, transforming grounded participant language into abstract theoretical dimensions.

Scvitools

Analyzes single-cell omics data using deep probabilistic models for integration, batch correction, and differential expression.

ReasoningBank with AgentDB

Implements high-performance adaptive learning and experience replay for AI agents using AgentDB's ultra-fast vector storage.

AI Engineer

Architects and implements production-grade LLM applications, RAG pipelines, and intelligent agent orchestrations.

PocketFlow

Orchestrates complex LLM applications using graph-based abstractions, agentic design patterns, and modular task decomposition.

Perception Pipeline

Deploys and manages advanced smart home perception layers including NVR, facial recognition, and local voice processing pipelines.

DS-STAR Data Science Framework

Automates complex data science workflows using a multi-agent architecture and optimized model routing for efficient, iterative data analysis.

LLM Integration & Orchestration

Integrates multiple LLM providers like Anthropic, OpenAI, and Google Gemini into applications using advanced orchestration and reasoning patterns.

Ollama Model Management & Optimization

Optimizes local LLM orchestration and GPU performance for Ollama-integrated AI environments.

Flow Nexus Swarm

Deploys and orchestrates cloud-based AI agent swarms with event-driven workflow automation and intelligent coordination.

Swarm Orchestration

Orchestrates multi-agent swarms using dynamic topologies and automated task distribution for complex, parallel AI workflows.

ReasoningBank Intelligence

Implements adaptive learning and pattern recognition systems to enable AI agents to optimize strategies and improve through experience.

ReasoningBank with AgentDB

Implements high-performance adaptive learning patterns and trajectory tracking for self-learning agents using a 150x faster vector database.

AgentDB Learning

Implements and trains reinforcement learning algorithms to create autonomous agents that improve through experience.

Gtars Genomic Analysis

Accelerates genomic interval analysis and machine learning preprocessing with high-performance Rust-powered algorithms and Python bindings.

AgentDB Learning

Trains and deploys reinforcement learning models for autonomous agents using nine specialized algorithms including Decision Transformers and Q-Learning.

ReasoningBank Intelligence

Implements adaptive learning systems to enable AI agents to recognize patterns, optimize strategies, and improve continuously through experience.

Flow Nexus Neural

Deploys and trains sophisticated neural networks across distributed sandbox environments using various architectures and federated learning techniques.

AgentDB Memory Patterns

Implements high-performance persistent memory and reasoning patterns for AI agents using vector storage and reinforcement learning.

ReasoningBank with AgentDB

Implements high-performance adaptive learning and experience replay patterns for self-improving AI agents using a high-speed vector database backend.

FDA Database Access

Queries and analyzes openFDA regulatory data for drugs, medical devices, food safety, and substance identification.

PyOpenMS Mass Spectrometry Analysis

Analyzes mass spectrometry data for proteomics and metabolomics using the PyOpenMS library.

Vision & Multimodal Capabilities

Powers Claude with advanced visual perception to analyze images, process PDFs, and extract structured data from visual inputs.

ToolUniverse Scientific Research

Connects Claude to over 600 specialized scientific tools and databases for bioinformatics, drug discovery, and genomic analysis.

AI Text Summarizer & Processor

Automates large-scale text summarization and translation using intelligent length-based routing and asynchronous processing.

Gtars Genomics Toolkit

Performs high-performance genomic interval analysis and data preprocessing for machine learning using Rust-powered tools.

Biopython Bioinformatics Toolkit

Simplifies computational molecular biology tasks including sequence manipulation, NCBI database access, and structural analysis.

Gtars: Genomic Interval Analysis

Provides a high-performance Rust toolkit for genomic interval analysis, coverage track generation, and machine learning tokenization.

PyOpenMS Mass Spectrometry Analysis

Facilitates mass spectrometry data analysis, proteomics, and metabolomics workflows using Python-based OpenMS bindings.