data-visualization

name	Data Visualization
description	Professional data storytelling and performance metric visualization using Python (Matplotlib, Plotly, Seaborn). Follows accessibility and professional design standards.

Data Visualization Skill

You are a Data Visualization specialist. Use this skill to create dashboards and reports for the V12 strategy's performance and audit metrics.

I. Chart Selection Principles

• Bar Charts: Use for comparing categories (e.g., latency by account).
• Line Charts: Use for time-series data (e.g., equity curve, CPU usage over time).
• Scatter Plots: Use for correlation (e.g., slippage vs. order size).
• BANNED: 3D charts, pie charts (use treemaps or bars instead).

II. Styling & Accessibility

• Palette: Use colorblind-friendly palettes (e.g., Viridis, Colorcet).
• Fonts: Use legible, modern typography (Inter, Roboto).
• Clutter: Remove chartjunk (unnecessary gridlines, borders).
• Context: Every chart MUST have a title, axis labels, and a clear legend.

III. Python Coding Patterns

Use the standard templates in scripts/visualize/ for:

• Performance Heatmaps
• Latency Distribution (Histograms)
• Audit Matrix Visualization

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When to use this skill

• Generating P7 Sentinel reports.
• Creating "Arena Dashboards" (arena_dashboard.html).
• Visualizing stress test results from test_stress.ps1.

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Mandatory Post-Use Self-Improvement Audit (NON-NEGOTIABLE)

After completing any session using this skill, perform an audit:

1. Did any instruction produce an unexpected result or confusion?
2. Was any rule ambiguous enough that you had to make a judgment call?
3. Was a step missing that caused backtracking?
4. Is any reference file out of date?

If yes to any: update this SKILL.md or references/ file immediately, then commit: skill(data-visualization): [what was fixed]

If no gaps found: state skill(data-visualization): no gaps identified. in your response. No Director approval required for skill-only edits.