data science & ml向けのClaudeスキルを発見してください。61個のスキルを閲覧し、AIワークフローに最適な機能を見つけましょう。
Designs and builds custom agents, skill frameworks, and Model Context Protocol (MCP) integrations using specialized personas and expert knowledge patterns.
Orchestrates specialized AI sub-agents to solve complex engineering problems through parallel task delegation.
Designs and implements sophisticated multi-agent workflows using modular orchestration patterns, hierarchical delegation, and deterministic tool coordination.
Enhances LLM performance and reliability through advanced techniques like Chain-of-Thought, structured outputs, and few-shot learning.
Standardizes repository workflows for AGILab development, environment management, and AI engineering application deployment.
Automates the setup, validation, and execution of phylogenetic ancestral range reconstruction using BioGeoBEARS in R.
Configures and manages high-performance 3D visualization servers for robotics and generative AI applications.
Provides standardized boilerplate and implementation patterns for 3D robotics and GenAI visualization using the Vuer toolkit.
Provides a comprehensive reference for rendering 3D primitives, meshes, and robotic models using the Vuer toolkit.
Manages real-time interactions, session APIs, and event streaming for Vuer-based 3D visualizations.
Models and simulates autopoietic systems using arena theory and GF(3) conservation rules for adaptive learning.
Simplifies real-time 3D visualization for robotics and AI applications using the Vuer toolkit and Python.
Provides structured patterns and guidance for building high-performance, production-grade AI agent systems through advanced context management.
Conducts systematic 7-step patent prior art searches and patentability assessments using BigQuery and CPC classifications.
Predicts stock price direction and magnitude following 8-K earnings releases using strictly point-in-time financial data.
Connects Claude to Vuer servers for real-time 3D visualization and event handling in robotics and GenAI projects.
Guides the design and implementation of distributed agent systems to maximize context efficiency and task parallelization.
Builds production-grade machine learning pipelines and models using industry-standard libraries and engineering best practices.
Synthesizes complex findings from multiple sources into coherent, actionable conclusions with uncertainty quantification.
Orchestrates specialized AI agents to conduct systematic, multi-disciplinary research and synthesis on complex topics.
Refactors, cleans, and optimizes Jupyter notebooks to improve code readability, maintainability, and reproducibility.
Maps contributor interaction networks across GitHub to discover shared boundaries between research and developer communities.
Conducts rigorous evaluations of claims, evidence, and logical arguments to detect bias and validate research methodologies.
Evaluates methodological quality and potential bias in research studies using standardized frameworks like RoB 2 and ROBINS-I.
Evaluates the robustness of research findings by testing how results change under different analytical assumptions and data conditions.
Implements rigorous randomization procedures for experimental research and unbiased participant allocation.
Facilitates the creation of methodologically sound research studies following NIH rigor standards and experimental best practices.
Prepares submission-ready research manuscripts by automating formatting, reporting guideline compliance, and journal selection workflows.
Conducts quantitative synthesis of research data by pooling effect sizes across multiple studies to derive summary conclusions.
Guides the selection, assumption checking, and interpretation of statistical hypothesis tests for rigorous research data analysis.
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