Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Conducts rigorous academic research and generates theoretical proposals with strong mathematical foundations.
Converts research papers into NeurIPS LaTeX format and automates the document compilation process.
Architects high-performance Retrieval-Augmented Generation systems using advanced embedding, chunking, and search strategies.
Analyzes AI experiment results and expert debates to determine whether a project should pivot or proceed.
Challenges mainstream assumptions and identifies project blind spots by uncovering counter-evidence through deep academic and web research.
Provides rigorous, conference-grade peer reviews for machine learning research papers targeting NeurIPS and ICML standards.
Conducts deep comparative research against State-of-the-Art (SOTA) works to define and position project contributions.
Generates engineering-focused research proposals by validating academic literature against practical implementation constraints.
Orchestrates machine learning experiments by monitoring GPU availability and dynamically dispatching tasks to remote infrastructure.
Conducts systematic literature reviews by synthesizing data from arXiv, Google Scholar, bioRxiv, and general web searches.
Orchestrates and executes machine learning experiments on remote servers using local Claude or Codex agents.
Trains autonomous agents using nine reinforcement learning algorithms to optimize decision-making and agent behavior through experience.
Implements high-performance adaptive learning and memory distillation for AI agents using AgentDB's optimized vector database.
Facilitates rigorous experimental design and ensures data reproducibility by integrating academic research tools into AI workflows.
Creates sophisticated, interactive data visualizations and custom SVG charts using the D3.js library.
Streamlines AI-native application development by providing expert patterns for Weaviate vector search, RAG pipelines, and multi-tenancy.
Integrates real-time web search and grounded AI responses into applications using the Perplexity Sonar API.
Simplifies the development of AI-powered applications using the OpenAI SDK and the GPT-5 model family.
Builds stateful, multi-agent applications and cyclic AI workflows using LangGraph for complex orchestration and persistent state management.
Migrates codebases and prompts from earlier Claude models to Opus 4.5 by automating model string updates and behavioral adjustments.
Analyzes raw interaction logs to extract recurring behavioral patterns and refine AI decision-making.
Conducts data-driven market research, competitive analysis, and investor due diligence with verified source attribution.
Generates and optimizes high-performance prompts for Claude, GPT, and other LLMs using research-backed engineering techniques.
Analyzes fitness training data to provide professional running coaching feedback based on the Bakken Norwegian Model.
Optimizes LLM performance through structured system prompts, few-shot learning, and rigorous evaluation patterns.
Standardizes tensor mathematics for BayesFlow extensions using Keras 3's backend-agnostic operations to ensure compatibility across PyTorch, JAX, and TensorFlow.
Enables Claude to analyze, transcribe, and generate multimedia content including audio, images, videos, and documents through the Gemini API.
Integrates nine advanced reinforcement learning algorithms into Claude to build self-optimizing autonomous agents that learn from experience.
Architects sophisticated multi-agent systems using proven design patterns, orchestration strategies, and performance evaluation frameworks.
Develops, tests, and deploys healthcare AI models using clinical data and specialized medical coding systems.
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