Technical Skills

Difference-in-Differences causal analysis to identify demographic drivers of behavioral changes with p-value significance testing. Use for event effects, A/B testing, or policy evaluation.

Difference-in-Differences causal analysis to identify demographic drivers of behavioral changes with p-value significance testing. Use for event effects, A/B testing, or policy evaluation.

Difference-in-Differences causal analysis to identify demographic drivers of behavioral changes with p-value significance testing. Use for event effects, A/B testing, or policy evaluation.

Complexity-based task routing for optimal model selection and cost efficiency. Use when deciding which model tier to use, analyzing task complexity, optimizing API costs, or implementing tiered routing. Trigger keywords - "routing", "complexity", "model selection", "tier", "cost optimization", "haiku", "sonnet", "opus", "task analysis".

Comprehensive clinical laboratory data harmonization for multi-source healthcare analytics. Convert between US conventional and SI units, standardize numeric formats, and clean data quality issues. This skill should be used when you need to harmonize lab values from different sources, convert units for clinical analysis, fix formatting inconsistencies (scientific notation, decimal separators, whitespace), or prepare lab panels for research.

YouTube Data API v3 analytics toolkit. Analyze YouTube channels, videos, and search results. Use when the user asks to: check YouTube channel stats, analyze video performance, compare channels, search for videos, get subscriber counts, view engagement metrics, find trending videos, get channel uploads, or analyze YouTube competition. Requires a YouTube Data API v3 key from Google Cloud Console.

Generates standardized quality control reports by aggregating metrics from FastQC, alignment, and other tools using MultiQC. Use when summarizing QC metrics across samples, creating shareable quality reports, or building automated QC pipelines.

DuckDB CLI specialist for SQL analysis, data processing and file conversion. Use for SQL queries, CSV/Parquet/JSON analysis, database queries, or data conversion. Triggers on "duckdb", "sql", "query", "data analysis", "parquet", "convert data".

Visualize Hi-C contact matrices, TADs, loops, and genomic features using matplotlib, cooltools, and HiCExplorer. Create triangle plots, virtual 4C, and multi-track figures. Use when visualizing contact matrices or genomic features.

Extract, filter, annotate, and export differential expression results from DESeq2 or edgeR. Use for identifying significant genes, applying multiple testing corrections, adding gene annotations, and preparing results for downstream analysis. Use when filtering and exporting DE analysis results.

Perform differential expression analysis using edgeR in R/Bioconductor. Use for analyzing RNA-seq count data with the quasi-likelihood F-test framework, creating DGEList objects, normalization, dispersion estimation, and statistical testing. Use when performing DE analysis with edgeR.

Statistical testing for differentially abundant proteins between conditions. Covers limma and MSstats workflows with multiple testing correction. Use when identifying proteins with significant abundance changes between experimental groups.

Create reproducible bioinformatics analysis reports with R Markdown including code, results, and visualizations in HTML, PDF, or Word format. Use when generating analysis reports with RMarkdown.

Perform differential expression analysis of miRNAs between conditions using DESeq2 or edgeR with small RNA-specific considerations. Use when identifying miRNAs that change between treatment groups, disease states, or developmental stages.

Visualize ChIP-seq data using deepTools, Gviz, and ChIPseeker. Create heatmaps, profile plots, and genome browser tracks. Visualize signal around peaks, TSS, or custom regions. Use when visualizing ChIP-seq signal and peaks.

R 4.4+ development specialist covering tidyverse, ggplot2, Shiny, and data science patterns. Use when developing data analysis pipelines, visualizations, or Shiny applications.

Rendimiento & Optimización - Atoll Tourisme. Use when optimizing performance or profiling code.

Integrate Databuddy analytics into applications using the SDK or REST API. Use when implementing analytics tracking, feature flags, custom events, Web Vitals, error tracking, LLM observability, or querying analytics data programmatically.

Common patterns for extracting analytics data from GA4 and GSC with API handling

Query Google Analytics 4 (GA4) data via the Analytics Data API. Use when you need to pull website analytics like top pages, traffic sources, user counts, sessions, conversions, or any GA4 metrics/dimensions. Supports custom date ranges and filtering.

Expert guidance for creating and working with marimo notebooks - reactive Python notebooks that can be executed as scripts and deployed as apps. Use when the user asks to create marimo notebooks, convert Jupyter notebooks to marimo, build interactive dashboards or data apps with marimo, work with marimo's reactive programming model, debug marimo notebooks, or needs help with marimo-specific features (cells, UI elements, reactivity, SQL integration, deploying apps, etc.).

Create interactive Desmos graphs in Obsidian using desmos-graph code blocks. Use when visualizing functions, parametric curves, inequalities, or mathematical relationships with customizable styling and settings.

Benchmark indicator performance with BenchmarkDotNet. Use for Series/Buffer/Stream benchmarks, regression detection, and optimization patterns. Target 1.5x Series for StreamHub, 1.2x for BufferList.

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug develo

Validate application performance against defined budgets to identify regressions early. Use when checking page load times, bundle sizes, or API response times against thresholds. Trigger with phrases like "validate performance budget", "check performance metrics", or "detect performance regression".

Track and optimize application response times across API endpoints, database queries, and service calls. Use when monitoring performance or identifying bottlenecks. Trigger with phrases like "track response times", "monitor API performance", or "analyze latency".

Use when building Apache Spark applications, distributed data processing pipelines, or optimizing big data workloads. Invoke for DataFrame API, Spark SQL, RDD operations, performance tuning, streaming analytics.

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。

Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow). Use when building data pipelines, implementing incremental models, migrating from pandas to polars, or orchestrating multi-step transformations with testing and quality checks.

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.

Deterministic mathematical computation using SymPy. Use for ANY math operation requiring exact/verified results - basic arithmetic, algebra (simplify, expand, factor, solve equations), calculus (derivatives, integrals, limits, series), linear algebra (matrices, determinants, eigenvalues), trigonometry, number theory (primes, GCD/LCM, factorization), and statistics. Ensures mathematical accuracy by using symbolic computation rather than LLM estimation.

Optional advanced tool for complex data modeling. For simple table creation, use relational-database-tool directly with SQL statements.

Establish performance baselines and detect regressions using flamegraph analysis. Use when optimizing performance-critical code, investigating performance issues, or before creating commits with performance-sensitive changes.

Spreadsheet toolkit (.xlsx/.csv). Create/edit with formulas/formatting, analyze data, visualization, recalculate formulas, for spreadsheet processing and analysis.

This skill should be used when working with CSV files to create interactive data visualizations, generate statistical plots, analyze data distributions, create dashboards, or perform automatic data profiling. It provides comprehensive tools for exploratory data analysis using Plotly for interactive visualizations.

Perform statistical tests, hypothesis testing, correlation analysis, and multiple testing corrections using scipy and statsmodels. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).

Walk Claude through PyDESeq2-based differential expression, including ID mapping, DE testing, fold-change thresholding, and enrichment visualisation.

Guide Claude through omicverse's bulk RNA-seq DEG pipeline, from gene ID mapping and DESeq2 normalization to statistical testing, visualization, and pathway enrichment. Use when a user has bulk count matrices and needs differential expression analysis in omicverse.

Guide for writing Datasette plugins. This skill should be used when users want to create or develop plugins for Datasette, including information about plugin hooks, the cookiecutter template, database APIs, request/response handling, and plugin configuration.

Structure Claude prompts for clarity and better results using roles, explicit instructions, context, positive framing, and strategic organization. Use when crafting prompts for complex tasks, long documents, tool workflows, or code generation.