Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Implements adaptive learning and meta-cognitive capabilities to help AI agents optimize strategies through experience and pattern recognition.
Instantiates sophisticated multi-agent architectures to handle complex reasoning, research, and implementation tasks.
Implements high-performance semantic vector search and intelligent document retrieval for RAG-based Claude Code workflows.
Manages persistent AI agent memory and reasoning patterns using high-performance vector storage and learning algorithms.
Designs and implements robust Retrieval-Augmented Generation (RAG) architectures using OpenClaw-native execution patterns.
Architects and implements production-grade Retrieval-Augmented Generation systems using specialized engineering guidance and explicit verification.
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production applications.
Combines vector similarity and keyword-based search to improve retrieval accuracy in RAG systems and search engines.
Implement high-performance similarity search and vector retrieval patterns across multiple database providers.
Calculates comprehensive financial risk metrics including VaR, CVaR, Sharpe, and Sortino ratios for quantitative portfolio management.
Guides users through the complete lifecycle of LLM fine-tuning, from initial goal setting to selecting optimal training strategies and models.
Orchestrates end-to-end MLOps pipelines from data ingestion and preparation to model training, validation, and production deployment.
Analyzes and extracts insights from images, videos, audio, and PDF documents using Gemini 3 Pro's native multimodal capabilities.
Processes and analyzes multimodal inputs including images, video, audio, and PDFs using the Gemini 3 Pro model.
Optimizes embedding model selection and chunking strategies to enhance semantic search and RAG application performance.
Transforms raw analytics into persuasive business narratives through structured storytelling, visualization techniques, and executive-ready frameworks.
Optimizes Apache Spark jobs through advanced partitioning, memory management, and shuffle performance tuning.
Refines confidence in hypotheses and technical decisions by systematically weighting prior beliefs against new evidence.
Automates the creation of FiftyOne datasets from local media files and executes machine learning model inference pipelines.
Optimizes LangGraph application performance by iteratively refining prompts and node-level processing logic based on quantitative evaluation criteria.
Implements comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Enables seamless SQL querying and exploration of biological data within the KBase/BERDL data lake via MCP.
Architects and optimizes high-performance Retrieval-Augmented Generation systems and vector search pipelines.
Optimizes trading strategy execution by removing redundant heuristic pattern filters that conflict with Reinforcement Learning model signals.
Generates high-fidelity videos and synchronized audio using Google Veo 3.1 via the Vertex AI API.
Optimizes segmentation, feature extraction, and spatial analysis workflows for high-dimensional multiplex immunofluorescence imaging data.
Optimizes Python dataclasses for memory efficiency, immutability, and validation using advanced PEP 557 patterns.
Eliminates HOLD bias in reinforcement learning trading models by calibrating reward functions and slippage penalties.
Automates the recording of actual trading results against predicted signals to enable accurate performance metrics and model retraining.
Trains Reinforcement Learning models across multiple market timeframes with automated data resampling and professional market alignment.
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