orchestrate-tufte-vdqi

name	orchestrate-tufte-vdqi
description	Router for the Tufte data-visualization toolkit. Use whenever someone has a chart or data-visualization request and you are not sure which Tufte skill to use — it decides between assessing an existing graphic, producing a new one, or fixing a cluttered/misleading one, and chains them when needed.

Orchestrate Tufte VDQI

You are the router. Read the request, decide the intent, and invoke the right skill. You are doing this by understanding, not by matching keywords — the previous version was a brittle keyword function and it is gone.

The toolkit (three skills + one VDQI-sourced reference)

• assess-graphical-excellence — evaluate an existing graphic against the nine criteria, name the chartjunk species present (moiré / dreaded grid / duck / decoration), compute the lie factor and compare it to VDQI's catalogue (NYT MPG 14.8, TIME barrel 59.4, etc.), check whether the data deserves a different genre (table for ≤20 numbers, small multiples for many series, range frame instead of bordered scatter), and emit prioritised fixes tagged with remedy (B1–B7), genre to switch to (C1–C10), anti-pattern resemblance, and exemplar to emulate. The default when intent is unclear.
• render-tufte-chart — produce an actual chart file. Ships per-genre scripts: render_line_svg.py (time-series C10), small_multiples.py (C5), quartile_plot.py (C1), range_frame.py (C2, optional C3 dot-dash marginals), plus wrap_html.py for a tufte-css HTML page. The only skill that outputs a chart.
• references/tufte-principles.md (mirrored into both skills) — the canonical Tufte knowledge, source-grounded to VDQI with page citations: Part A nine criteria with numeric anchors, Part B seven remedies, Part C ten chart genres with construction recipes, Part D chartjunk taxonomy, Part E named-failure catalogue (13 dissected real-world graphics with metrics), Part F named-exemplar catalogue (14 praised graphics with copyable moves), Part G compact quantitative defaults.

Routing

• Evaluate / critique ("is this chart any good?", "what's wrong with this?", "is this misleading?") → assess-graphical-excellence.
• Design / build / produce ("make me a Tufte chart of…", "design a clean time-series", "produce the chart") → render-tufte-chart. If the data is currency across multiple years, deflate it first (remedy B7) before rendering.
• Fix / declutter an existing chart ("clean this up", "too cluttered") → chain: assess-graphical-excellence to diagnose and list remedies, then render-tufte-chart to rebuild honoring them. The assessment's remedy tags (B1–B7) are the instructions render follows.
• Unsure → start with assess-graphical-excellence.

Why this shape

Earlier this toolkit had ten skills. Benchmarking showed most encoded a single Tufte idea the model already applies, so separate routing targets only added latency and risk. Assessment and rendering are the two actions that genuinely benefit from a skill. The depth that makes the skills non-generic lives in the principles reference — specifically Parts C–F, the source-grounded genre playbook, chartjunk taxonomy, named-failure library, and named-exemplar library quoted from VDQI by page. Without those, the skills regress to "Claude paraphrasing Tufte from memory"; with them, the model has Tufte's specific vocabulary and worked numbers to reach for.