feat(d3): implement radar-multi

[github-actions]

Implementation: radar-multi - javascript/d3

Implements the javascript/d3 version of radar-multi.

File: plots/radar-multi/implementations/javascript/d3.js

Parent Issue: #2026

---

🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

Light render (plot-light.png): Warm off-white background (#FAF8F1-like, not pure white). Bold dark title "radar-multi · javascript · d3 · anyplot.ai" centered at top; six category axis labels (Communication, Technical Skill, Leadership, Creativity, Problem Solving, Teamwork) in dark ink around the outer edge; hexagonal gridlines at 20/40/60/80/100 in a subtle stroke, with ring value labels sitting on small haloed boxes so they stay readable where polygons overlap. Three filled, alpha-blended polygons (Alicia Chen = green #009E73, Marcus Reyes = lavender #C475FD, Priya Nair = blue #4467A3) each have a genuinely distinct shape. Centered legend below the chart. All text is clearly readable against the light background.

Dark render (plot-dark.png): Warm near-black background (#1A1A17-like, not pure black). Same title, axis labels, gridlines, ring labels, and legend, now rendered in light ink against the dark surface — no dark-on-dark instances found; the haloed ring-label boxes stay legible even sitting on top of the translucent color fills. Data colors are identical to the light render (green/lavender/blue) — confirms only chrome flipped between themes. All text is clearly readable against the dark background.

Both renders pass the theme-readability check.

Score: 85/100

Category	Score	Max
Visual Quality	28	30
Design Excellence	12	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	9	10
Library Mastery	6	10
Total	85	100

Visual Quality (28/30)

• VQ-01: Text Legibility (7/8)
• VQ-02: No Overlap (6/6)
• VQ-03: Element Visibility (6/6)
• VQ-04: Color Accessibility (2/2)
• VQ-05: Layout & Canvas (3/4) - margin=170 plus title/legend reserves leave notable corner whitespace on the square canvas
• VQ-06: Axis Labels & Title (2/2)
• VQ-07: Palette Compliance (2/2)

Design Excellence (12/20)

• DE-01: Aesthetic Sophistication (5/8) - Above default (haloed ring labels, rounded legend swatches) but not fully publication-ready
• DE-02: Visual Refinement (4/6) - Subtle grid, good alpha/markers, but corner whitespace keeps it short of perfect
• DE-03: Data Storytelling (3/6) - Color contrast enables comparison but no focal point or emphasis calls out an insight

Spec Compliance (15/15)

• SC-01: Plot Type (5/5)
• SC-02: Required Features (4/4)
• SC-03: Data Mapping (3/3)
• SC-04: Title & Legend (3/3)

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6)
• DQ-02: Realistic Context (5/5)
• DQ-03: Appropriate Scale (4/4)

Code Quality (9/10)

• CQ-01: KISS Structure (2/3)
• CQ-02: Reproducibility (2/2)
• CQ-03: Clean Imports (2/2)
• CQ-04: Code Elegance (2/2)
• CQ-05: Output & API (1/1)

Library Mastery (6/10)

• LM-01: Idiomatic Usage (3/5) - Correct use of d3.lineRadial/scaleLinear, but only the legend uses the .data().join() pattern
• LM-02: Distinctive Features (3/5) - d3.lineRadial + curveLinearClosed is a genuine D3-specific radial shape generator

Score Caps Applied

• None

Strengths

• Correct Imprint palette in canonical order (green #009E73, lavender #C475FD, blue #4467A3), identical across light and dark renders, with theme-correct backgrounds and chrome
• Ring value labels (20/40/60/80/100) use haloed background boxes so they stay legible even where overlapping translucent polygons cross them
• Realistic, neutral quarterly-review competency dataset with genuinely differentiated shapes per person, satisfying the spec's comparison-clarity intent
• All spec notes honored: filled polygons at alpha 0.22, closed via curveLinearClosed, both fill and stroke, gridlines at the specified 20-unit interval, outer-edge axis labels, legend identifying each series

Weaknesses

• Only the legend uses D3's idiomatic .data().join() pattern — grid rings, axis spokes/labels, series polygons, and per-point circles are all built with manual forEach + .append() loops. Convert these to selection.data(...).join(...) for stronger Library Mastery.
• No visual emphasis or focal point highlights a standout competency or overall leader — consider a subtle callout, size/opacity emphasis, or ranked ordering to guide the viewer toward an insight.
• Substantial unused whitespace in all four corners of the square canvas from margin=170 plus titleH/legendH reserves — reduce the margin or grow the radius to better fill the 2400×2400 canvas.
• angleFor/pointFor helper functions are reasonable for the radial trig but a stricter KISS read would minimize the helper surface.

Issues Found

1. LM-01 MEDIUM: Manual forEach+.append() loops used for grid rings, axis spokes/labels, series polygons, and point circles instead of D3 data joins
   • Fix: Rewrite these sections using selection.data(...).join(...) (e.g., gridGroup.selectAll("polygon").data(levels).join("polygon")) to demonstrate idiomatic D3 data-binding
2. DE-03 LOW: No visual hierarchy or emphasis beyond color contrast
   • Fix: Add a subtle focal point — e.g., bold the top scorer per axis, or reorder the legend/annotate the standout competency
3. VQ-05 LOW: Notable whitespace in the four canvas corners
   • Fix: Reduce margin from 170 or shrink titleH/legendH slightly so the radar polygon fills more of the 2400×2400 canvas

AI Feedback for Next Attempt

Good spec compliance and data quality — keep those. To improve: (1) convert the grid/spokes/labels/polygons/circles to true D3 .data().join() data-binding instead of forEach+append loops, (2) tighten the layout (smaller margin / larger radius) to reduce corner whitespace on the square canvas, and (3) add a subtle visual focal point (e.g., highlighting the top score per axis) to give the chart a clearer story beyond raw comparison.

Verdict: REJECTED