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gridlines at 20/40/60/80/100, vertex markers, legend'
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- Perfect spec compliance and data quality — employee performance scenario is realistic,
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neutral, and tells a complementary skills story
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- Clean KISS code structure with all font sizes explicitly set and deterministic
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data
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- 'Perfect spec compliance: all required radar chart features (filled polygons,
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gridlines, polygon closure, multi-series legend) present and correct'
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- 'Excellent data quality: contrasting employee profiles (Senior Developer vs Team
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Lead) create a natural, informative narrative ideal for radar charts'
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- 'Full theme adaptation: both light and dark renders pass all chrome checks — backgrounds
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are #FAF8F1 / #1A1A17, text flips correctly, data colors stay constant'
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- 'Correct Okabe-Ito palette with #009E73 as first series and #D55E00 as second'
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- Clean KISS code structure with explicitly set font sizes at all levels (title=26pt,
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axes=20pt, ticks=16pt, legend=18pt)
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weaknesses:
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- Design storytelling is implicit — the contrasting Senior Developer/Team Lead profiles
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suggest a story but no visual hierarchy or emphasis guides the viewer to the insight
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(DE-03 weak)
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- Seaborn library mastery is limited by the plot type — sns.set_theme() is the only
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seaborn API used; all actual plotting relies on matplotlib polar primitives (ax.fill,
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ax.plot, ax.scatter), which limits LM-01/LM-02
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- Aesthetic sophistication is above default but not publication-ready — vertex markers
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and Okabe-Ito palette are good choices but the overall composition lacks a distinctive
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design signature (DE-01 at 5/8)
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- 'Code/image discrepancy: current seaborn.py only implements the radar chart but
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plot_images/ show a combined radar+bar chart with different data values — images
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appear to be from a previous run and should be regenerated'
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- Library mastery is limited because seaborn's high-level plotting API (sns.barplot,
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etc.) is not used for the primary visualization — radar charts require matplotlib's
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polar projection directly, so seaborn contributes mainly via sns.set_theme()
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- Radial tick labels (20/40/60/80/100) are rendered inside the radar near gridlines,
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making them slightly hard to read — repositioning with ax.set_rlabel_position()
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to an uncluttered angle would improve legibility
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image_description: |-
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Light render (plot-light.png):
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Background: Warm off-white consistent with #FAF8F1 — NOT pure white, correctly theme-matched.
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Chrome: Title "radar-basic · seaborn · anyplot.ai" at 26pt in dark ink — clearly readable. Category labels (Communication, Technical Skills, Teamwork, Leadership, Problem Solving, Creativity) at 20pt in dark ink around the radar perimeter — all readable. Radial tick labels (20, 40, 60, 80, 100) at 16pt in INK_SOFT color — readable, positioned along one spoke.
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Data: Two filled polygons — Senior Developer in #009E73 (bluish green, first Okabe-Ito) and Team Lead in #D55E00 (vermillion, second Okabe-Ito). Both with alpha=0.25 fill and solid outlines at linewidth=3.5. Vertex markers (s=150) mark each data point. The green polygon shows Technical Skills and Problem Solving dominance; the orange shows Teamwork and Leadership dominance.
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Legibility verdict: PASS — all text clearly readable against warm off-white background.
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Background: Warm off-white (#FAF8F1) — correct, not pure white.
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Chrome: Title "radar-basic · seaborn · anyplot.ai" in dark ink — readable. Spoke labels (Communication, Technical Skills, Teamwork, Leadership, Problem Solving, Creativity) in dark ink around perimeter — readable. Radial tick labels (20/40/60/80/100) in INK_SOFT grey — readable though close to gridlines. Legend frame uses ELEVATED_BG (#FFFDF6) — readable.
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Data: First series (Senior Developer) = #009E73 (brand green) ✓. Second series (Team Lead) = #D55E00 (vermillion, Okabe-Ito position 2) ✓. Both series rendered as filled transparent polygons (alpha=0.25) with thick lines (3.5) and scatter markers. A companion horizontal bar chart ("Score Breakdown") appears on the right half of the canvas.
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Note: Bar chart data values in the image (e.g. Creativity=92 for Senior Developer) differ from current seaborn.py (Creativity=82). Images appear to be from a previous render.
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Legibility verdict: PASS
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Dark render (plot-dark.png):
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Background: Warm near-black consistent with #1A1A17 — NOT pure black, correctly theme-matched.
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Chrome: Title uses light ink (#F0EFE8) — readable against dark background. Category labels switch to light text — readable. Radial tick labels use #B8B7B0 (INK_SOFT dark) — visible against dark surface. No dark-on-dark failures detected.
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Data: Both #009E73 (green) and #D55E00 (orange) polygons are identical in color to light render — only chrome flips. Brand green #009E73 remains clearly visible on the dark surface.
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Legibility verdict: PASS — no dark-on-dark failures, all text reads well on near-black background.
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Background: Warm near-black (#1A1A17) — correct, not pure black.
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Chrome: Title and all labels rendered in light ink (#F0EFE8-ish) — clearly readable against the dark background. No dark-on-dark failures observed. Grid lines are subtle and visible. Legend frame uses ELEVATED_BG (#242420) dark elevated surface — correct.
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Data: Data colors are identical to the light render — Senior Developer is still #009E73 (green) and Team Lead is still #D55E00 (orange). Only chrome flips between themes. Brand green #009E73 is clearly visible on the dark background.
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