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。
Transforms Claude into a specialized prompt architect for designing, optimizing, and debugging complex AI instructions and agent behaviors.
Automates laboratory liquid handling workflows by generating and optimizing Opentrons Protocol API v2 scripts for Flex and OT-2 robots.
Builds comprehensive financial models including DCF analysis, sensitivity testing, and Monte Carlo simulations for investment and valuation decisions.
Implements industry-standard gradient boosting algorithms for high-performance machine learning on tabular and structured datasets.
Orchestrates sophisticated multi-agent systems with intelligent routing, handoffs, and collaborative workflows across AI providers.
Standardizes SLURM job output naming by mapping channel numbers to biological marker names for the KINTSUGI pipeline.
Recalibrates upcoming training sessions dynamically based on recent performance, user feedback, and safety constraints.
Translates CODEX/Akoya experiment.json metadata into the KINTSUGI ExperimentConfig format with precise field and wavelength mapping.
Automates the creation, editing, and analysis of professional spreadsheets with support for complex formulas and financial modeling standards.
Automates Google Vertex AI multimodal operations to process, analyze, and transform media content within your development environment.
Architects high-performance AI prompts using advanced complexity-based standards, attention management, and structural optimization patterns.
Designs and implements evolutionary persistent memory architectures for AI agent systems using RAG and Knowledge Graphs.
Integrates Google Gemini's advanced multimodal capabilities to process, analyze, and generate professional audio, image, and video content directly within your workflow.
Optimizes large-scale data staging on HPC environments using rsync, bash, and SLURM to ensure data integrity and script reliability.
Builds sophisticated AI agents with tool-calling capabilities and multi-provider LLM integration using a Kotlin-native framework.
Screens and analyzes stocks using quantitative multi-factor models to identify high-potential investment opportunities.
Analyzes Interactive Brokers CSV statements to uncover trading edges, identify risk management patterns, and generate professional performance reports.
Creates, modifies, and analyzes Excel spreadsheets with production-grade formulas, professional formatting, and financial modeling standards.
Optimizes mean-reversion trading strategy parameters through real-time performance analysis and pattern identification.
Identifies unusual patterns and outliers in complex datasets using advanced machine learning algorithms.
Performs hydrological modeling and streamflow forecasting using Julia-based classical and machine learning models.
Analyzes text data to identify emotional tone and classify sentiment as positive, negative, or neutral.
Converts text and long-form markdown documents into high-quality audio locally using the Kokoro-82M model optimized for Apple Silicon.
Provides a comprehensive suite of 100+ molecular featurizers for converting chemical structures into machine learning-ready numerical representations.
Optimizes LLM prompts to minimize token usage, reduce operational costs, and enhance model response quality through automated refinement.
Optimizes AI agent performance through Anthropic-based context engineering and prompt structure standards.
Guides users through a comprehensive 10-step pipeline for processing multiplex imaging data on SLURM-managed HPC clusters.
Manage, validate, and trace biological datasets using a FAIR-compliant data framework and standardized biological ontologies.
Refines and compresses LLM prompts to minimize token usage, lower operational costs, and maximize response quality.
Maximizes HPC throughput by orchestrating concurrent GPU and CPU batch processing across multiple SLURM accounts.
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