Anthropic Skills

Translates Splunk SPL queries to Axiom APL. Provides command mappings, function equivalents, and syntax transformations. Use when migrating from Splunk, converting SPL queries, or learning APL equivalents of SPL patterns.

Designs and builds Axiom dashboards via API. Covers chart types, APL patterns, SmartFilters, layout, and configuration options. Use when creating dashboards, migrating from Splunk, or configuring chart options.

Write SQL queries, optimize database performance, design schemas, and debug SQL issues. Use for database operations, query optimization, and schema design.

Parse, analyze, transform, and manipulate CSV files. Use for data processing, cleaning, and CSV operations.

Work with Excel spreadsheets (XLSX/XLS/CSV) - read data, create spreadsheets, convert formats, analyze data, and generate reports. Use when the user asks to work with Excel files or spreadsheet data.

This skill should be used when the user asks to "model trends with limited data", "three-valued logic analysis", "scenario generation", "transitional graphs", "qualitative trend analysis", "uncertain data analysis", "minimal-information modeling", or needs guidance on trend-based modeling using INC/DEC/CONST logic, scenario planning with limited quantitative data, or generating transitional scenario graphs.

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 optimizing application performance.

This skill should be used when the user asks to "identify trends", "analyze market trends", "trend forecasting", "macro trends", "micro trends", "emerging patterns", "future projections", "industry trends", or needs guidance on trend identification, pattern recognition, or market forecasting methodologies.

Expert guide to the auto-generated GraphQL API (Queries, Mutations, Aggregations).

Make informed technology decisions with structured frameworks, decision matrices, and recommendations based on constraints.

Guide to building Custom Views, Dashboards, and Action Buttons.

D3.jsベースの主題図作成ライブラリの使用ガイド。レイヤー選択、パラメータ設定、ベストプラクティス。地図作成、GeoJSON可視化について。

Database querying and analysis using SQLAlchemy 2.0+ with support for PostgreSQL, MySQL, SQLite, and SQL Server. Use when tasks require: (1) Querying databases via SQL, (2) Reading data into DataFrames for analysis, (3) Performing database operations with proper transaction handling. Environment variable with connection string must be set (check resources/RESOURCES.md for available databases and schemas).

Expert-level Power BI, DAX, M language, data modeling, Power Query, report design, and paginated reports

Extract metadata from SPSS .sav files as JSON using pyreadstat

Эксперт по отчетности Facebook Ads. Используй для формирования дневных/недельных отчетов, сравнения периодов и анализа трендов.

Fetches and processes NBA player and team statistics. Use when the user wants to analyze basketball data for the sports picker model.

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MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter

Create professional financial charts and visualizations using Python/Plotly. Use when building Sankey diagrams (income statement flows, revenue breakdowns), waterfall charts (profit walkdowns, revenue bridges), bar charts (margin comparisons, segment breakdowns), or line charts (trend analysis, multi-company comparisons). Triggers on chart creation requests, financial visualization needs, or data presentation tasks.

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Create Domino Launchers - parameterized web forms for self-service job execution. Enable business users to run analyses, generate reports, and trigger batch predictions without coding. Covers parameter types, email notifications, result delivery, and access control. Use when building self-service data products or enabling non-technical users.

Statistical analysis methods, hypothesis testing, and probability for data analytics

View cost dashboard and spending analytics (project)

Master Excel for data analysis with pivot tables, formulas, Power Query, and advanced Excel techniques.

Data visualization design, tools, and storytelling for impactful analytics presentations

MANDATORY tracking protocol for multi-model validation. Creates structured tracking tables BEFORE launching models, tracks progress during execution, and ensures complete results presentation. Use when running 2+ external AI models in parallel. Trigger keywords - "multi-model", "parallel review", "external models", "consensus", "model tracking".

Analyze event datasets (logs) and intervals over time using OPAL timechart. Use when you need to visualize trends, track metrics over time, or create time-series charts. Covers timechart for temporal binning, bin duration options (1h, 5m, 1d), options(bins:N) for controlling bin count, and understanding temporal output columns (_c_valid_from, _c_valid_to, _c_bucket). Returns multiple rows per group for time-series visualization. For single summaries, see aggregating-event-datasets skill.

Aggregate and summarize event datasets (logs) using OPAL statsby. Use when you need to count, sum, or calculate statistics across log events. Covers make_col for derived columns, statsby for aggregation, group_by for grouping, aggregation functions (count, sum, avg, percentile), and topk for top N results. Returns single summary row per group across entire time range. For time-series trends, see time-series-analysis skill.

Data analysis expert for SQL queries, BigQuery operations, and data insights. Use proactively for data analysis tasks and queries.

Generate, validate, and refine Mermaid diagrams (flowcharts, sequence diagrams, class diagrams, state diagrams, Gantt charts, ERD, component diagrams). Use when creating visualizations, documenting workflows, system architectures, or data flows. Includes syntax validation and best practices guidance.

Use when analyzing sales performance, customer metrics, inventory health, or generating forecasts.

Analyzes ICU clinical data using the Common Longitudinal ICU data Format (CLIF) and clifpy Python library. Loads and filters CLIF tables (vitals, labs, medications, respiratory support, microbiology) by hospitalization_id and category columns. Computes clinical scores including SOFA, Charlson Comorbidity Index (CCI), and Elixhauser. Creates wide datasets and performs data transformations. Use when working with ICU data, CLIF format, clifpy, clinical scoring, ventilator data, sepsis research, or

生成专业金融图表（K线图、技术指标图）。适用于数据可视化、技术分析展示、报告生成等场景。支持多种图表类型（basic、comprehensive）和自定义样式（深色、浅色主题）。

基于每周六截止的年度累计CSV数据，精确计算车险业务16个核心KPI指标。接受原始CSV数据，执行聚合和计算，输出完整的KPI结果。当用户提到"计算KPI"、"KPI计算"、"赔付率"、"边际贡献"、"指标"时使用。

Эксперт A/B тестирования. Используй для статистических тестов, экспериментов и ML-оптимизации.

Establish neutral baseline metrics for unbiased assessment.

Generate Mermaid diagrams including flowcharts, sequence diagrams, and class diagrams. Use when creating visual diagrams in documentation.

Process Excel files with data manipulation, formula generation, and chart creation. Use when working with spreadsheets or Excel data.

Fast in-process analytical database for SQL queries on DataFrames, CSV, Parquet, JSON files, and more. Use when user wants to perform SQL analytics on data files or Python DataFrames (pandas, Polars), run complex aggregations, joins, or window functions, or query external data sources without loading into memory. Best for analytical workloads, OLAP queries, and data exploration.