Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Architects and implements autonomous AI agent systems using sophisticated planning, memory, and tool-integration strategies.
Implements production-ready architectures for LLM-powered applications, including RAG pipelines, agentic workflows, and LLMOps monitoring.
Implements high-performance software and complex algorithms with uncompromising scientific rigor and formal verification.
Builds high-performance, low-latency voice AI applications and real-time conversational agents using industry-leading providers.
Predicts market movements and executes trades using sublinear algorithms and temporal advantage calculations to outpace traditional data transmission speeds.
Architects high-performance AI voice agents with optimized latency for natural, real-time human-AI conversations.
Builds production-grade AI features using robust LLM integration patterns, structured output validation, and cost-effective prompt engineering.
Analyzes and extracts structured insights from video files using AI-powered understanding and timestamped key moment identification.
Implements high-performance software and complex algorithms with absolute scientific rigor and formal verification standards.
Automates the creation, editing, and analysis of professional-grade Excel spreadsheets with industry-standard financial modeling practices.
Designs and implements robust autonomous AI agents with sophisticated tool use, planning strategies, and multi-agent orchestration capabilities.
Provides production-ready architectural patterns for building robust LLM applications, covering RAG pipelines, autonomous agents, and LLMOps observability.
Architects and implements autonomous AI agent systems featuring robust tool use, memory management, and multi-agent orchestration.
Provides production-ready architectural patterns and implementation guides for building robust LLM applications, RAG pipelines, and AI agents.
Optimizes LLM performance and reduces API costs by implementing advanced prefix caching, response caching, and Cache Augmented Generation strategies.
Optimizes AI performance and reliability through advanced prompting patterns like Few-Shot Learning and Chain-of-Thought reasoning.
Implements path-independent, auto-invalidating file processing caches using SHA-256 content hashes for maximum performance.
Implements tiered memory systems for LLMs to maintain persistent context and entity-based knowledge across interactions.
Builds production-grade, stateful AI agents using the LangGraph framework for complex, multi-actor workflows.
Implements sophisticated persistent memory systems to help AI assistants retain context and user information across multiple interactions.
Optimizes Apache Spark data processing jobs through advanced partitioning, memory management, and shuffle tuning.
Implements persistent, multi-tiered memory systems to enhance LLM context retention and entity tracking across interactions.
Validates BayesFlow neural posterior estimators using simulation-based calibration (SBC) and comprehensive diagnostic metrics.
Architects and implements high-quality, defensible AI-powered products by bridging LLM APIs with specialized domain logic and robust cost controls.
Architects robust memory systems for intelligent agents using short-term, long-term, and episodic retrieval patterns.
Streamlines the creation and debugging of data preprocessing pipelines for BayesFlow simulation-based inference.
Standardizes tensor operations using Keras 3 backend-agnostic math to ensure compatibility across PyTorch, JAX, and TensorFlow.
Enforces best practices for BayesFlow extension packages, including src-layout, dependency management, and API exports.
Empowers Claude with high-performance vector embeddings, HNSW indexing, and persistent semantic search capabilities.
Optimizes and adapts foundation models through parameter-efficient fine-tuning (PEFT), dataset preparation, and production-ready ML workflows.
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