Data Science & ML Agent Skills

Jupyter Notebooks

Manages, executes, and converts Jupyter notebooks to streamline data science and machine learning workflows.

Agent SDK Builder

Guides users through an interactive interview and research process to build custom AI agents using the OpenHands SDK.

Ollama Local Inference

Powers local LLM integration and performance tuning for private, cost-effective AI development using Ollama.

Memory Fabric

Orchestrates unified AI memory by combining local knowledge graphs with semantic cloud search for persistent, high-context retrieval.

Audio Language Models

Implements real-time voice agents, high-accuracy transcription, and text-to-speech using leading audio AI providers.

LangGraph State Management

Designs and manages robust state schemas for AI agent workflows using LangGraph best practices and modern design patterns.

RAG Reranking Patterns

Enhances search precision in RAG pipelines by re-scoring retrieved documents using high-accuracy Cross-Encoders and LLM relevance patterns.

Semantic Caching

Optimizes LLM performance and reduces API costs by implementing Redis-powered vector similarity caching.

Fine-Tuning & Customization

Simplifies Large Language Model fine-tuning and alignment using parameter-efficient techniques like LoRA, QLoRA, and DPO.

Semantic Embeddings & Vector Search

Converts text into high-dimensional vector representations for semantic search, document similarity, and RAG pipelines.

LangGraph Conditional Routing

Implements dynamic workflow routing, retry loops, and semantic branching for LangGraph-based AI agents.

LangGraph Parallel Execution

Implements high-performance parallel execution patterns for LangGraph workflows using fan-out/fan-in and map-reduce strategies.

Contextual Retrieval for RAG

Implements Anthropic's contextual retrieval technique to improve RAG performance by prepending situational metadata to document chunks.

HyDE Semantic Retrieval

Enhances RAG retrieval quality by generating and embedding hypothetical answer documents to bridge vocabulary gaps between queries and data.

Golden Dataset Curation

Curates high-quality evaluation datasets for AI models using multi-agent validation and automated quality scoring.

Vision Language Model Integration

Integrates advanced vision-language models for image analysis, document understanding, and multimodal reasoning within Claude Code.

HyDE Semantic Retrieval

Improves semantic search accuracy by generating hypothetical answer documents to bridge vocabulary gaps in RAG pipelines.

Agentic Workflows & Loops

Implements autonomous reasoning patterns like ReAct and Plan-and-Execute to enable LLMs to solve complex, multi-step tasks.

Agentic RAG Patterns

Builds self-correcting RAG systems using LangGraph for adaptive retrieval, document grading, and web search fallbacks.

Prompt Engineering Suite

Optimizes LLM performance through production-ready patterns including Chain-of-Thought, dynamic few-shot learning, and automated prompt tuning.

LangGraph Agent Supervisor

Orchestrates multi-agent workflows using a central supervisor pattern to intelligently route tasks between specialized worker agents.

Multimodal RAG Patterns

Implements advanced retrieval-augmented generation systems that integrate text and image data for hybrid search and visual question answering.

Prompt Engineering Suite

Optimizes AI application performance through production-ready prompt engineering patterns, versioning, and automated tuning.

Agentic RAG Patterns

Implements advanced Self-RAG and Corrective-RAG architectures for self-correcting AI retrieval systems.

LangGraph Supervisor Pattern

Coordinates complex multi-agent workflows using a centralized supervisor-worker orchestration pattern.

Mem0 Long-Term Memory

Persists semantic context and project decisions across multiple Claude Code sessions using Mem0.

Contextual Retrieval RAG

Enhances RAG pipelines by prepending situational context to document chunks to preserve semantic meaning and significantly improve retrieval accuracy.

Prompt Caching Optimizer

Optimizes LLM API costs and performance by implementing provider-native prompt caching for Claude and OpenAI.

LangGraph Functional API

Builds production-ready AI workflows using Python decorators for task orchestration and parallel execution.

LangGraph Conditional Routing

Implements dynamic workflow branching and retry logic for AI agentic systems using LangGraph patterns.