matplotlib
Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.
statsmodels
Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.
matlab
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.
hypothesis-generation
Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideation use scientific-brainstorming; for automated LLM-driven hypothesis testing on datasets use hypogenic.
generate-cell-analysis-charts
Domain-specialized chart generator for cell biology video analysis outputs. Consumes structured JSON from analyze_lab_video_cell_behavior or compatible sources and produces publication-ready figures — growth curves, cell trajectory maps, phenotype distribution charts, MSD plots, wound-closure timeseries, dose-response curves, and 96-well heatmaps — using matplotlib and seaborn. Exports PNG/PDF at configurable DPI for papers, ELN entries, or XR dashboards.
hypogenic
Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.
powerlifting
Calculating powerlifting scores to determine the performance of lifters across different weight classes.
search-driving-distance
Estimate driving/taxi duration, distance, and rough cost between two cities using the bundled distance matrix CSV. Use this skill when comparing ground travel options or validating itinerary legs.
search-attractions
Retrieve attractions by city from the bundled dataset. Use this skill when surfacing points of interest or building sightseeing suggestions for a destination.
did-causal-analysis
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.
pca-decomposition
Reduce dimensionality of multivariate data using PCA with varimax rotation. Use when you have many correlated variables and need to identify underlying factors or reduce collinearity.
trend-analysis
Detect long-term trends in time series data using parametric and non-parametric methods. Use when determining if a variable shows statistically significant increase or decrease over time.
contribution-analysis
Calculate the relative contribution of different factors to a response variable using R² decomposition. Use when you need to quantify how much each factor explains the variance of an outcome.
meteorology-driver-classification
Classify environmental and meteorological variables into driver categories for attribution analysis. Use when you need to group multiple variables into meaningful factor categories.
data-viz-plots
Publication-quality matplotlib/seaborn plots: scatter, heatmap, violin, bar, line, multi-panel figures. Works with ANY LLM provider.
performance-reporter
Generate SEO/GEO dashboards: rankings, traffic, backlinks, AI visibility for stakeholders. SEO报告/绩效仪表盘
agentsociety-synthesize
Synthesize experiment results into research insights and summaries.
quant-statistics
Quantitative statistical methods: ADF unit-root / cointegration tests, GARCH volatility modeling, regression diagnostics (heteroskedasticity / autocorrelation), Bootstrap, and hypothesis testing.
technical-basic
Core technical indicator collection (trend EMA/ADX + mean-reversion BB/RSI + volume-price OBV/volume ratio), generates a composite signal via three-dimensional voting. Pure pandas implementation for any OHLCV data.
vega
Create data-driven charts with Vega-Lite (simple) and Vega (advanced). Best for bar, line, scatter, heatmap, area charts, and multi-series analytics. Use when you have numeric data arrays needing statistical visualization. Vega for radar charts and word clouds. NOT for process diagrams (use mermaid) or quick KPI cards (use infographic).
aris-paper-figure
Generate publication-quality figures and tables from experiment results. Use when user says "画图", "作图", "generate figures", "paper figures", or needs plots for a paper.
travel-health-analyzer
分析旅行健康数据、评估目的地健康风险、提供疫苗接种建议、生成多语言紧急医疗信息卡片。支持WHO/CDC数据集成的专业级旅行健康风险评估。
