# Quantitative Visual Style Contract This file is the enforceable visual-design contract for the `scientific-visual-table-style` skill. It generalizes recurring patterns in first-party OpenAI launch pages, research pages, Deployment Safety Hub figures, system cards, and OpenAI-authored technical papers. It is not an official brand specification. Its purpose is operational consistency. ## 1. Priority order Apply constraints in this order: 1. Scientific truth and source fidelity. 2. Explicit user instructions. 3. Existing manuscript/template geometry when the user requests preservation. 4. Venue requirements and accessibility. 5. This style contract. 6. Creative alternatives. Never improve visual aesthetics by weakening evidence, hiding a baseline, changing a value, suppressing uncertainty, or overstating a conclusion. ## 2. Visual objective Every visual must answer one primary question: > What should a technically competent reader understand within five seconds? A successful visual has: - one dominant message; - an obvious entry point; - a stable reading order; - low legend and cross-reference burden; - enough detail for verification; - no decorative element competing with evidence; - consistent visual grammar across related outputs. If the five-second message is not clear, do not polish the current composition. Reconsider form, grouping, and hierarchy first. ## 3. Canvas and composition ### 3.1 Background Default to: - canvas: `#FFFFFF`; - optional warm paper fill: `#FBFBF9`; - plotting area: same as canvas; - subtle structural region only when needed: `#F5F5F2`. Do not use large gray plotting panels, card grids, drop shadows, bevels, glossy surfaces, or gradients. ### 3.2 Whitespace Whitespace is structural, not decorative. Use it to separate semantic groups and create a reading path. Default targets at manuscript size: - outside plot margin: 4–8% of width; - title-to-plot gap: 6–10 pt; - inter-panel gutter: 4–6% of total figure width; - annotation breathing room: at least one text-height around the label; - table row-group gap: 3–6 pt; - table horizontal padding: 4–7 pt per side. Avoid both extremes: - cramped marks and labels; - excessive empty space that weakens comparison or wastes manuscript area. ### 3.3 Proportions Set final dimensions before plotting. Defaults when venue dimensions are unknown: | Context | Width | Typical height | Minimum text | |---|---:|---:|---:| | Paper single column | 85 mm | 48–65 mm | 8 pt | | Paper double column | 178 mm | 82–115 mm | 8 pt | | Slide figure region | 150–300 mm | composition-dependent | 14 pt | | Web/card | 900–1600 px | 500–950 px | 12 CSS px | Prefer one-panel aspect ratios between 1.45 and 1.80. Use taller formats for long category labels or distributions. Use square formats only when x and y have symmetrical scientific meaning. ### 3.4 Alignment - Align panel plot areas, not merely outer bounding boxes. - Align table decimals and shared baselines. - Align titles, panel labels, and annotations to a deliberate grid. - Use consistent left edges across a visual series. - Keep shared axes exactly aligned. - Avoid optical misalignment caused by unequal label lengths; compensate in layout rather than shifting marks arbitrarily. ## 4. Hierarchy Use no more than four hierarchy levels: 1. claim/title; 2. focal result; 3. required comparison evidence; 4. metadata, notes, and supporting labels. The focal result may be emphasized through: - darker value; - one accent hue; - thicker line; - direct annotation; - position; - whitespace. Use at most two of these simultaneously unless the user explicitly requests stronger emphasis. Do not: - enlarge the focal bar area disproportionately; - suppress competitors below readable contrast; - use different scales for the focal method; - place a conclusion in a colored banner detached from the data. ## 5. Typography ### 5.1 Font family Use a neutral sans-serif stack: `Arial, Helvetica, Inter, Liberation Sans, DejaVu Sans, sans-serif` Do not bundle or redistribute proprietary fonts. Prefer metric-compatible system fallbacks. ### 5.2 Weight Use primarily: - regular for data, axes, and notes; - semibold for titles, table headers, and focal labels. Avoid heavy bold, ultra-light text, italics for large blocks, and mixed font families. ### 5.3 Case and language - Sentence case by default. - Preserve official model and benchmark capitalization. - Avoid all-caps section headers. - Use concise, concrete labels. - Use consistent terminology across all figures and tables. ### 5.4 Final-size type defaults For manuscript figures: - claim/title: 9.5–11 pt; - axis labels: 8.5–9.5 pt; - ticks and data labels: 8–9 pt; - annotations: 8–9 pt; - panel labels: 9–10 pt semibold; - notes inside visual: 7.5–8.5 pt only when unavoidable. For tables: - body: 8.5–9.5 pt; - header: same size or 0.25–0.5 pt larger, semibold; - footnotes: 7.5–8.5 pt; - line height: 1.25–1.40× body size. Never solve small text by increasing raster resolution. Rebuild at the actual delivery size. ### 5.5 Numerals and punctuation - Use tabular numerals where supported. - Prefer a true minus sign (`−`) over hyphen-minus for negative values. - Use an en dash for ranges and an em dash for unavailable values. - Use thin/nonbreaking spacing between value and unit where supported. - Keep decimal separators locale-consistent. ## 6. Color system ### 6.1 Operational palette | Role | Hex | Use | |---|---|---| | Primary ink | `#111111` | titles, focal neutral line, primary text | | Secondary ink | `#404040` | axes, secondary labels | | Muted text | `#6F6F6F` | notes, supporting labels | | Baseline gray | `#8D8D88` | prior model or required comparison | | Light baseline | `#B6B6B0` | external/secondary baselines | | Hairline | `#D8D8D4` | rules, separators | | Grid | `#E8E8E5` | faint major grid only | | Subtle fill | `#F5F5F2` | limited grouping/background region | | Focal teal | `#1F6F5F` | principal accent | | Focal tint | `#DDE9E5` | restrained highlight fill | | Risk/regression | `#B5473C` | errors, harm, regression, danger | | Warning | `#9A681A` | caution or threshold proximity | This palette is operational and OpenAI-inspired; it is not claimed to be official. ### 6.2 Color rules - Default to grayscale plus one accent. - Use no more than two semantic accents in one figure. - Keep the focal series at the highest chromatic or luminance contrast. - Use risk hues only for semantically adverse outcomes. - Maintain one document-level mapping from series/model to color. - Use line style, marker, position, or direct label in addition to hue. - Test in grayscale. Reject: - default Matplotlib or Tableau rainbow palettes; - high-saturation category fills; - gradients; - red/green-only distinctions; - arbitrary changes in model color across panels; - pale baseline text that becomes unreadable in print. ## 7. Lines, rules, and marks At manuscript size: | Element | Default | |---|---:| | Axis/hairline | 0.6–0.8 pt | | Table top/bottom rule | 0.75–0.9 pt | | Table header/group rule | 0.35–0.55 pt | | Baseline line | 1.0–1.2 pt | | Focal line | 1.5–1.8 pt | | Error bar | 0.7–0.9 pt | | Annotation leader | 0.6–0.8 pt | | Marker | 4–6 pt | Use solid lines for primary series. Use dashed/dotted lines for structurally different conditions, not as arbitrary decoration. Avoid marker outlines thicker than the line, large circles obscuring data, or heavy black borders around bars. ## 8. Titles, labels, and captions ### 8.1 Title Preferred title behavior: - claim-led when the evidence supports a concise conclusion; - descriptive but specific when neutrality is scientifically necessary; - one line where possible; - no terminal period for a short title; - no generic “Results,” “Comparison,” or “Performance.” Examples: - Good: `Replay hurts under abrupt source drift`. - Good: `Higher reasoning effort improves hard tasks but raises cost`. - Weak: `Results on our benchmark`. Do not overclaim causality when the plot shows association. ### 8.2 Axis labels Axis labels include: - metric name; - unit; - direction when not obvious. Examples: - `Accuracy (%) · higher is better`; - `Median latency (s) · lower is better`; - `API cost per task (USD, log scale)`. Do not repeat the same unit in every tick label if it is already in the axis title. ### 8.3 Data labels Use direct labels when: - there are at most roughly six focal series; - endpoints are spatially separated; - exact values materially improve interpretation; - legend lookup would be slower. Do not label every mark in a dense scatter. Label: - frontier points; - focal operating points; - thresholds; - major outliers; - endpoints. ### 8.4 Captions and notes A publication caption should define, in this order when applicable: 1. what is plotted; 2. task/population and sample; 3. aggregation/statistic; 4. uncertainty; 5. relevant exclusions or conditions; 6. metric direction; 7. cost/latency basis. Do not use the caption to repeat the title. Keep methodological caveats in a smaller note if the venue permits. ## 9. Axes, scales, and grids ### 9.1 Axes - Remove top and right spines by default. - Use left/bottom axes only when they aid orientation. - For direct-labeled plots, axes may be even lighter. - Use 3–6 major ticks per continuous axis as a default. - Use human-readable tick steps. - Keep the zero line slightly stronger only when zero is meaningful. ### 9.2 Bar scales Bars encode length from a common baseline. Therefore: - quantitative bars start at zero; - deviation bars may center on an explicit zero/reference line; - never crop a bar axis merely to magnify small differences; - use dots/intervals when a nonzero narrow range is scientifically important. ### 9.3 Log scales Use a log scale only when: - values span at least about two orders of magnitude; - ratios are more meaningful than differences; - the scale is clearly labeled. Do not place zero or negative values on a log axis. Do not hide the transformation in a note. ### 9.4 Grid - No grid by default for bars and simple dot plots. - Use faint major horizontal gridlines for value estimation when helpful. - Use no minor gridlines unless the plot is a technical log-scale figure that requires them. - Gridlines must be lower contrast than uncertainty and all data marks. ## 10. Legends and direct labeling Use a legend only when direct labeling would create collisions or when the same encoding is reused across many panels. Legend rules: - place in unused whitespace, not over data; - remove frame; - order entries exactly as they appear visually; - use one row or a compact vertical stack; - use short labels; - avoid repeating a full legend in every panel. For small multiples, prefer one shared legend or direct panel labels. ## 11. Annotations Annotations are allowed only when they explain: - a threshold; - a causal intervention; - a change point; - a frontier operating point; - a clinically/statistically meaningful region; - a non-obvious counterexample. Default: - one to three annotations; - 8–9 pt at manuscript size; - align text into existing whitespace; - use a thin leader only when spatial relationship is ambiguous; - use a subtle accent or primary ink, not a colored bubble. Reject: - decorative callouts; - paragraph-length prose inside the plot; - many crossing leader lines; - annotations that simply restate a labeled value. ## 12. Multi-panel composition ### 12.1 Panel count Prefer: - 1–4 panels for a main figure; - 2–6 compact facets for a repeated benchmark family; - additional panels in supplementary material if they do not support the central claim. ### 12.2 Shared structure - Share axis limits when comparison requires it. - Align zero/baseline lines. - Keep model order identical. - Keep palette and line styles identical. - Suppress repeated axis titles and legends. - Use panel labels `(a)`, `(b)`, … only when cited in text or structurally necessary. ### 12.3 Hierarchy Not every panel needs equal area. Give the primary panel more area only when: - the evidence importance genuinely differs; - the scaling does not distort comparison; - supporting panels remain readable. Avoid a “hero project” effect in which one panel dominates merely because it was easier to visualize. ## 13. Chart-specific contracts ### 13.1 Horizontal bar and dot charts Use for ranked or labeled categories. - Sort by scientific order or value; never default to alphabetical unless categories are identifiers. - Put long labels on the y-axis. - Direct-label values at bar/dot endpoints when space permits. - Use one focal accent and gray baselines. - Use dot plots instead of bars when the range does not meaningfully include zero. ### 13.2 Grouped bars Use only when both category and condition comparisons are essential. - Keep conditions to about 2–4. - Use position first, color second. - Keep group gaps larger than within-group gaps. - Add uncertainty only if valid. - Consider small multiples when there are more than four conditions. ### 13.3 Stacked bars Use for part-to-whole outcomes with 2–5 ordered categories. - Sum to 100% or a clear common total. - Keep category order semantically stable. - Put the most decision-relevant segment at a common baseline if possible. - Direct-label large segments; avoid tiny labels inside narrow segments. - Do not use stacked bars for independent metrics. ### 13.4 Line charts Use only for ordered/continuous x. - Limit to roughly 3–7 salient lines. - Direct-label endpoints where possible. - Use markers only for sparse or irregular observations. - Use a ribbon for uncertainty when it does not obscure other series. - Highlight change points only when scientifically justified. ### 13.5 Scatter plots - Use transparency or density methods only when overplotting exists. - Label focal points/frontier points, not every observation. - Add trend lines only with a stated estimator. - Use a diagonal/reference line only when it has scientific meaning. - Preserve equal aspect ratio when x and y are directly comparable. ### 13.6 Pareto/frontier plots - Use real cost, latency, energy, or memory units. - Compute nondominated points from the data. - Connect only points that belong to an ordered family, such as reasoning effort or batch size. - Mute dominated points but keep them visible. - Direct-label frontier/model families. - If x spans orders of magnitude, use a labeled log scale. - State pricing/hardware/batch assumptions. ### 13.7 Dot-and-interval / forest plots - Use a meaningful zero or baseline line. - Order rows by concept, not estimated effect, unless ranking is the claim. - Use thin intervals and a clear point estimate. - Distinguish confidence, credible, bootstrap, or standard-error intervals explicitly. - Avoid filled bars for signed effects. ### 13.8 Heatmaps - Use only when both axes form a meaningful matrix. - Use a perceptually ordered sequential or diverging scale. - Choose a meaningful center for diverging scales. - Show missing values distinctly. - Use cell labels only when final-size text remains readable. - Use sparse ticks and group separators for large matrices. - Accompany the heatmap with a colorbar whose unit and direction are explicit. ### 13.9 Distributions Choose based on the question: - ECDF: robust comparison across full distributions; - histogram: intuitive count/density shape; - box/violin: compact group comparison; - strip/swarm: small sample visibility; - ridgeline: only for many ordered distributions and sufficient vertical space. State whether the y-axis is count, density, probability, or cumulative proportion. ### 13.10 Calibration - Include the ideal diagonal. - State whether values are binned. - Show sample support or uncertainty when available. - Do not infer calibration from aggregate accuracy alone. ### 13.11 Before/after and paired comparisons - Use paired dots, dumbbells, or slopes for the same units under two conditions. - Preserve pairing visually. - Sort by baseline or change when useful. - Use arrows only when direction is unambiguous and does not clutter. - Report actual values; optional deltas are secondary. ### 13.12 Scaling and pass@k/worst-of-k curves - Define the x-axis compute/sample semantics exactly. - Use shared x-values and consistent interpolation policy. - Do not smooth sparse points without stating the method. - Use endpoint emphasis rather than markers at every point. - Show the single-sample baseline. ## 14. Table contract ### 14.1 Structure Use `booktabs` logic: - top rule; - header separator; - optional thin semantic group separators; - bottom rule; - no vertical rules; - no border around every cell. ### 14.2 Column order Default order: 1. group or benchmark label; 2. metric/condition detail; 3. baseline(s); 4. prior/family models; 5. focal/current method; 6. optional delta or cost column; 7. notes only when essential. Place the focal model at the right edge when it makes row-wise scanning easier, unless chronology or user template dictates otherwise. ### 14.3 Alignment - Labels: left. - Numeric values: decimal/right. - Short categorical statuses: centered. - Headers: align with the data beneath them. - Long method names: never centered. ### 14.4 Headers - Keep to one or two rows. - Put units in headers. - Put metric direction in a concise header note or table note. - Use spanning headers only for true semantic groups. - Use visual weight/spacing to distinguish top-level and leaf headers. ### 14.5 Precision Use the smallest precision that preserves meaningful distinctions. Default: - percentages: 0 or 1 decimal; - scores on 0–1: 2–3 decimals if the benchmark supports that precision; - costs: 2–3 significant figures; - latency: one consistent unit and 2–3 significant figures; - counts: integer; - confidence intervals: match estimate precision. Do not display more precision than measurement or evaluator variability supports. ### 14.6 Emphasis - Bold the focal method or best result only when predefined. - If many values tie statistically or numerically, mark ties honestly. - Avoid colored fills across the entire winning row. - Use a very light tint only for one focal column or one decision-critical region when necessary. - Never use stars without a defined significance legend. ### 14.7 Missing and exceptional values - unavailable/not applicable: em dash; - not evaluated: `n/e` only when defined in the note; - below threshold: `