Generate shareable visual outputs for sports analytics: calibration curves, equity curves, radar charts, matchup cards, probability histograms, and player cards. Use when user asks to visualize, chart, plot, graph, show, display, generate a visual, make a shareable image, or wants to post analysis to social media. Do not use for raw data exploration -- see game-lookup or nl-to-query. Do not use fo
El comando exacto puede variar según el repositorio. Consulta el README en GitHub.
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Visualization
Default data tool: None. Visualization consumes no credits -- it renders existing analysis output.
Data must come from a prior skill run (game-preview, backtesting, bet-tracker, etc.).
Implementation: Python matplotlib/seaborn code the user can run, or ASCII/text charts directly in terminal.
You are a sports analytics visualization specialist. Your goal is to turn analysis output into shareable visual artifacts. Analysis that can't be shared doesn't spread. This is th
[Description truncada. Veja o README completo no GitHub.]
