Data Science & ML Agent Skills

Agent SDK Builder

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

Jupyter Notebooks

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

Mem0 Long-Term Memory

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

Golden Dataset Quality Validator

Ensures high-quality AI evaluation datasets by performing automated schema validation, duplicate detection, and coverage analysis.

Golden Dataset Validator

Validates AI evaluation datasets for schema compliance, content integrity, and duplicate detection to ensure high-quality benchmarking.

High-Performance Inference

Optimizes Large Language Model inference for production environments using vLLM, advanced quantization, and speculative decoding.

LLM Function Calling & Tool Use

Enables LLMs to interact with external tools and return structured data through standardized function calling patterns and strict schemas.

Golden Dataset Curator

Manages the automated curation and multi-agent validation of high-quality datasets for LLM evaluation.

LangGraph Checkpointing & Persistence

Manages fault-tolerant workflow persistence and state recovery for LangGraph AI agents.

Alternative Agent Frameworks

Implement and compare multi-agent orchestration frameworks like CrewAI, OpenAI Agents SDK, and Microsoft Agent Framework for specialized AI workflows.

RAG Retrieval Patterns

Implements production-ready Retrieval-Augmented Generation patterns to ground AI responses in factual data and minimize hallucinations.

RAG Retrieval Patterns

Implements robust Retrieval-Augmented Generation (RAG) patterns to ground LLM responses with accurate, cited, and validated external data.

High-Performance LLM Inference

Optimizes Large Language Model inference for production environments using vLLM, advanced quantization, and speculative decoding techniques.

Golden Dataset Curator

Manages the multi-agent curation of high-quality training and testing datasets with automated quality scoring and bias detection.

LLM Output Evaluation & Quality Assurance

Implements advanced LLM-as-judge patterns and RAGAS metrics to evaluate AI output quality and detect hallucinations.

Query Decomposition

Decomposes complex, multi-concept queries into independent sub-topics to improve RAG retrieval accuracy and coverage.

Query Decomposition

Breaks down complex search queries into independent sub-concepts to improve retrieval accuracy and coverage in RAG systems.

Alternative Agent Frameworks

Provides implementation patterns and comparison guides for multi-agent orchestration frameworks including CrewAI, OpenAI Agents SDK, and Microsoft Agent Framework.

Agent Loops & Reasoning

Implements autonomous agentic workflows and reasoning patterns for complex, multi-step LLM tasks.

Audio Language Models

Implements real-time voice agents, high-accuracy transcription, and expressive text-to-speech using native speech-to-speech models.

LLM Evaluation & Quality Assessment

Implements automated quality gates, LLM-as-judge patterns, and RAGAS metrics to ensure reliable and grounded AI outputs.

Audio Language Models

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

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.

Prompt Engineering Suite

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

LangGraph Conditional Routing

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

LangGraph Supervisor Pattern

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

Agentic RAG Patterns

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

Agentic Workflows & Loops

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

Prompt Caching Optimizer

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