xlsx
全面的电子表格创建、编辑和分析功能,支持公式、格式化、数据分析和可视化。当 Claude 需要处理电子表格(.xlsx、.xlsm、.csv、.tsv 等)时使用,包括:(1) 创建带有公式和格式的新电子表格,(2) 读取或分析数据,(3) 修改现...
Discover tools data analysis skills, compare source repositories and read the instructions for each workflow.
全面的电子表格创建、编辑和分析功能,支持公式、格式化、数据分析和可视化。当 Claude 需要处理电子表格(.xlsx、.xlsm、.csv、.tsv 等)时使用,包括:(1) 创建带有公式和格式的新电子表格,(2) 读取或分析数据,(3) 修改现...
Comprehensive data visualization skill covering visual execution and technical implementation. Includes perceptual foundations, chart selection, layout algorithms, and library guidance. Load on-demand when buil...
Advanced test reporting, quality dashboards, predictive analytics, trend analysis, and executive reporting for QE metrics. Use when communicating quality status, tracking trends, or making data-driven decisions...
Strategic test data generation, management, and privacy compliance. Use when creating test data, handling PII, ensuring GDPR/CCPA compliance, or scaling data generation for realistic testing scenarios.
Measure quality effectively with actionable metrics. Use when establishing quality dashboards, defining KPIs, or evaluating test effectiveness.
Guides performance optimization, profiling techniques, and bottleneck identification. Use when improving application speed, reducing resource usage, or diagnosing performance issues.
全面的AB测试分析工具,支持实验设计、统计检验、用户分群分析和可视化报告生成。用于分析产品改版、营销活动、功能优化等AB测试结果,提供统计显著性检验和深度洞察。
智能推荐系统分析工具,提供多种推荐算法实现、评估框架和可视化分析。使用时需要用户行为数据、商品信息或评分数据,支持协同过滤、矩阵分解等推荐算法,生成个性化推荐结果和评估报告。
Perform multi-touch attribution analysis using Markov chains, Shapley values, and custom attribution models. Use when you need to analyze marketing channel effectiveness, calculate conversion attribution, optim...
Perform RFM (Recency, Frequency, Monetary) customer segmentation analysis on e-commerce data. Use when you need to analyze customer value, identify VIP customers, or create marketing segments. Automatically cle...
Analyze user conversion funnels, calculate step-by-step conversion rates, create interactive visualizations, and identify optimization opportunities. Use when working with multi-step user journey data, conversi...
Perform comprehensive regression analysis and predictive modeling using linear regression, decision trees, and random forests. Use when you need to predict continuous values like housing prices, sales forecasts...
自动化数据探索和可视化工具,提供从数据加载到专业报告生成的完整EDA解决方案。支持多种图表类型、智能数据诊断、建模评估和HTML报告生成。适用于医疗、金融、电商等领域的数据分析项目。
Generate realistic synthetic data using Faker and Spark, with non-linear distributions, integrity constraints, and save to Databricks. Use when creating test data, demo datasets, or synthetic tables.
Create beautiful infographics based on the given text content. Use this when users request creating infographics.
Patterns for data loading, exploration, and statistical analysis
Patterns for data loading, exploration, and statistical analysis
Manage architectural decisions and insights in memory.jsonl. Use when you need to document strategic decisions, lessons learned, or architectural insights.
Generate safe, read-only PostgreSQL queries from natural language. Use when users need to query blog_small, ecommerce_medium, or saas_crm_large databases. Supports query generation, execution, and result analys...
Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability...
Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or...
Professional data visualization creation using D3.js with support for interactive charts, custom visualizations, animations, and responsive design. Use for: (1) Creating custom interactive charts, (2) Building...
Create charts, graphs, and visualizations from data. Use when the user needs to visualize data, create charts, or generate reports with graphics.
Pattern for aggregating insights across multiple tasks to enable data-driven evolution.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.