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Found 788 Skills
Teaches the agent to produce D3 charts and interactive data visualizations. Useful for editorial dashboards, reports, and explanatory graphics.
Use when you need to choose the right visualization for your data and question, then create a narrated report that highlights insights and recommends actions. Invoke when analyzing data for patterns (trends, comparisons, distributions, relationships, compositions), building dashboards or reports, presenting metrics to stakeholders, monitoring KPIs, exploring datasets for insights, communicating findings from analysis, or when user mentions "visualize this", "what chart should I use", "create a dashboard", "analyze this data", "show trends", "compare these metrics", "report on", "what does this data tell us", or needs to turn data into actionable insights. Apply to business analytics (revenue, growth, churn, funnel, cohort, segmentation), product metrics (usage, adoption, retention, feature performance, A/B tests), marketing analytics (campaign ROI, attribution, funnel, customer acquisition), financial reporting (P&L, budget, forecast, variance), operational metrics (uptime, performance, capacity, SLA), sales analytics (pipeline, forecast, territory, quota attainment), HR metrics (headcount, turnover, engagement, DEI), and any scenario where data needs to become a clear, actionable story with the right visual form.
Create interactive chart visualizations (bar, line, pie) from data.
Creates and configures Home Assistant graph visualizations using history-graph, statistics-graph, mini-graph-card, and apexcharts-card with time ranges, aggregations, and multi-sensor support. Use when displaying sensor data over time, creating trend charts, comparing historical data, or building energy/climate/air quality dashboards.
Generate audio visualization videos using each::sense AI. Create waveforms, spectrum analyzers, particle effects, 3D visualizations, and beat-synced animations from audio files.
Generate G2 v5 chart code. Use this when users request G2 charts, bar charts, line charts, pie charts, scatter plots, area charts, or any data visualization implemented with the G2 library.
Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.
Create production-quality data visualizations including charts, dashboards, and infographics. Use when the user asks to visualize data, create charts, build dashboards, make infographics, plot statistics, or transform datasets into visual representations. Supports React/Recharts artifacts, static images (PNG/PDF via Python), and interactive HTML. Triggers include "visualize this data", "create a chart", "build a dashboard", "make a graph", "plot this", "infographic", or any request to represent data visually.
MDV — Markdown superset for documents, dashboards, and slides with embedded charts, KPI stats, and data visualizations exported to HTML or PDF.
Build PyGraphistry visualizations with bindings, encodings, layout controls, static export, and privacy-aware sharing. Use for color/size/icon/badge styling, layout tuning, map/static output, and plot link sharing workflows.
Generate D3.js visualizations including charts, graphs, and interactive data visualizations. Use when creating data visualizations with D3.js.
Data visualization for Python: Matplotlib, Seaborn, Plotly, Altair, hvPlot/HoloViz, and Bokeh. Use when creating exploratory charts, interactive dashboards, publication-quality figures, or choosing the right library for your data and audience.