数据与 AI技能

分析健康目标数据、识别目标模式、评估目标进度,并提供个性化目标管理建议。支持与营养、运动、睡眠等健康数据的关联分析。

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Supervised & unsupervised learning, scikit-learn, XGBoost, model evaluation, feature engineering for production ML

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Machine learning development with JAX, functional programming patterns, and high-performance computing.

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Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.

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MLflow, model versioning, experiment tracking, model registry, and production ML systems

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PyTorch deep learning development with transformers, diffusion models, and GPU optimization.

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Machine learning in Python with scikit-learn. Use for classification, regression, clustering, model evaluation, and ML pipelines.

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Run Hugging Face models in JavaScript or TypeScript with Transformers.js in Node.js or the browser.

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Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.

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This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

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Design and implement a complete ML pipeline for: $ARGUMENTS

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Diagnose and optimize Agent Skills (SKILL.md) with real session data and research-backed static analysis. Works with Claude Code, Codex, and any Agent Skills-compatible agent.

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This skill covers the principles for identifying tasks suited to LLM processing, designing effective project architectures, and iterating rapidly using agent-assisted development.

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Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

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Statsmodels is Python's premier library for statistical modeling, providing tools for estimation, inference, and diagnostics across a wide range of statistical methods.

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Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

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Matplotlib is Python's foundational visualization library for creating static, animated, and interactive plots.

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Best practices for Matplotlib data visualization, plotting, and creating publication-quality figures in Python

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Apache Airflow, dbt, Prefect, Dagster, and modern data orchestration for production data pipelines

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Data analysis best practices with pandas, numpy, matplotlib, seaborn, and Jupyter notebooks.

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Forensic root cause analyzer for Antigravity sessions. Classifies scope deltas, rework patterns, root causes, hotspots, and auto-improves prompts/health.

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Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

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Transform slow database queries into lightning-fast operations through systematic optimization, proper indexing, and query plan analysis.

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SQL query optimization, schema design, indexing strategies, and relational database mastery for production data systems

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