Discover Agent Skills for data science & ml. Browse 53skills for Claude, ChatGPT & Codex.
Configures and manages diverse LLM providers, streaming callbacks, and token optimization strategies for XSky-based agentic workflows.
Powers Claude with advanced visual perception to analyze images, process PDFs, and extract structured data from visual inputs.
Transforms oversized documents into structured, token-optimized hierarchical sections with extracted metadata to overcome context window limitations.
Implements persistent, high-performance memory and learning patterns for AI agents using AgentDB.
Train, deploy, and manage distributed neural networks across sandboxed E2B environments using multiple architectures and federated learning.
Empowers AI agents with adaptive learning and pattern recognition to optimize workflows and decision-making strategies through experience.
Implements high-performance adaptive learning and experience replay for AI agents using the AgentDB vector engine.
Enhances Claude's problem-solving capabilities using advanced search strategies like Beam Search and Monte Carlo Tree Search.
Produces comprehensive, well-sourced research reports using an iterative diffusion-based refinement methodology.
Detects narrative manipulation and propaganda patterns in text and URLs using the Narrative Credibility Index (NCI) Protocol.
Accesses and analyzes ES/NQ futures market data using Databento's high-fidelity platform with a cost-optimized workflow.
Crafts production-ready LLM prompts, agent definitions, and system instructions optimized for Claude and GPT models.
Optimizes LLM performance and reliability through advanced prompt engineering techniques like few-shot learning and chain-of-thought.
Extracts and normalizes multi-exchange market data, technical indicators, and social sentiment for comprehensive crypto analysis.
Calculates core financial technical indicators including MA, MACD, RSI, and Bollinger Bands for stock market analysis and quantitative trading.
Consults multiple AI models simultaneously and synthesizes their outputs using configurable strategies to improve accuracy and gather diverse perspectives.
Optimizes LLM performance through advanced prompt engineering, RAG architecture design, and agentic system orchestration.
Ensures the integrity of FTD analysis output by validating JSONL structures, TALD scale requirements, and clinical domain completeness.
Manages Retrieval-Augmented Generation (RAG) indices to enable semantic search capabilities over BigQuery datasets.
Builds production-grade MLOps pipelines by orchestrating data preparation, model training, validation, and automated deployment workflows.
Implements comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and comparative benchmarking.
Orchestrates complex LLM applications using graph-based abstractions, agentic design patterns, and modular task decomposition.
Implements high-performance adaptive learning patterns and trajectory tracking for self-learning agents using a 150x faster vector database.
Optimizes Claude's output quality using research-backed psychological framing and statistical pattern-matching techniques.
Accesses real-time prediction market data, betting odds, and trading analytics from the Kalshi platform.
Automates the initialization and lifecycle management of bioinformatics research projects with structured workflows and scientific quality standards.
Manages structured bioinformatics lab notebooks through interactive dialogue to ensure high-quality, reproducible research documentation.
Generates and refines structured scientific reports from bioinformatics lab notebooks with integrated figure support and professional PDF export.
Refines and validates bioinformatics hypotheses by transforming vague observations into specific, testable experimental strategies.
Integrates Google Gemini's multimodal capabilities to process audio, video, images, and documents directly within the Claude Code environment.
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