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。
Corrects multi-action trading logic bugs and optimizes backtesting notebooks for Google Colab environments.
Optimizes KINTSUGI batch processing by enforcing GPU-only SLURM scheduling to achieve up to 25x speedups over CPU fallback.
Implements granular skip-existing checks in Snakemake wrapper scripts to resume interrupted HPC jobs without re-processing completed channels.
Manages large-scale scientific dataset transfers between remote Globus endpoints and high-performance computing clusters.
Generates testable, evidence-based scientific hypotheses and experimental designs across multiple research domains.
Accesses and analyzes global public statistical data through the Data Commons knowledge graph and Python API.
Integrates the Google Gemini CLI into Claude to provide large-context analysis, safe sandbox execution, and structured code modifications.
Queries the NHGRI-EBI GWAS Catalog to retrieve genetic variant-trait associations and summary statistics.
Evaluates scientific research rigor by assessing methodology, statistical validity, and bias through established frameworks like GRADE and Cochrane ROB.
Generates comprehensive, 50+ page professional market research reports with consulting-grade analysis and high-fidelity visualizations.
Facilitates programmatic access to over 61 million standardized single-cell genomics data points for advanced querying and analysis.
Access and interpret the Human Metabolome Database for metabolite identification, biomarker discovery, and clinical chemistry research.
Analyzes single-cell RNA-seq data with standardized workflows for quality control, clustering, and cell type annotation.
Accesses the BRENDA database via SOAP API to retrieve kinetic parameters, reaction equations, and organism-specific enzyme data for biochemical research.
Architects high-performance system instructions and prompt patterns to optimize Large Language Model outputs and consistency.
Combines semantic vector similarity with keyword-based retrieval to maximize search recall and accuracy in AI applications.
Implements high-performance systems and complex algorithms with absolute scientific rigor and formal correctness.
Transforms initial software concepts into comprehensive, well-architected technical designs and implementation roadmaps.
Builds low-latency, production-grade voice applications using real-time APIs, advanced synthesis, and streaming transcription services.
Performs advanced molecular analysis and manipulation using the RDKit toolkit for drug discovery and computational chemistry.
Generates publication-quality scientific diagrams and technical schematics with automated AI quality review and smart iteration.
Indexes and manages external reference documents to power Retrieval-Augmented Generation (RAG) for domain-specific AI workflows.
Generates and updates professional PyTorch-style docstrings using Sphinx and reStructuredText conventions.
Builds and deploys bioinformatics workflows using the Latch SDK and serverless cloud infrastructure.
Orchestrates complex mathematical computations by deterministically routing natural language requests to specialized CLI tools for symbolic math, logic, and geometry.
Streamlines genomics pipeline development and data management on the DNAnexus cloud platform using the dxpy Python SDK.
Connects Claude to cloud laboratory services for automated protein testing, sequence optimization, and wet-lab validation.
Searches and retrieves life sciences preprints from the bioRxiv database with advanced filtering and PDF download capabilities.
Enables development and training of Graph Neural Networks (GNNs) using the PyTorch Geometric library.
Transforms vague research interests into concrete, actionable, and tractable research questions with a systematic feasibility analysis.
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