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chore(seaborn): update quality score 86 and review feedback for radar-basic
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‎plots/radar-basic/implementations/python/seaborn.py‎

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"""anyplot.ai
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""" anyplot.ai
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radar-basic: Basic Radar Chart
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Library: seaborn | Python 3.13
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Quality: 91/100 | Updated: 2026-04-29
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Library: seaborn 0.13.2 | Python 3.13.13
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Quality: 86/100 | Updated: 2026-04-29
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"""
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import os

‎plots/radar-basic/metadata/python/seaborn.yaml‎

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# Per-library metadata for seaborn implementation of radar-basic
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# Auto-generated by impl-generate.yml
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library: seaborn
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language: python
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specification_id: radar-basic
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created: '2025-12-23T18:32:28Z'
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updated: '2026-04-29T16:39:41Z'
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updated: '2026-04-29T16:46:25Z'
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generated_by: claude-sonnet
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workflow_run: 25121287681
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issue: 744
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preview_url_dark: https://storage.googleapis.com/anyplot-images/plots/radar-basic/python/seaborn/plot-dark.png
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preview_html_light: null
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preview_html_dark: null
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quality_score: null
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quality_score: 86
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review:
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strengths: []
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weaknesses: []
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strengths:
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- 'Correct Okabe-Ito palette with #009E73 first series and #D55E00 second series'
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- Full theme-adaptive chrome — both light and dark renders are readable with no
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dark-on-dark failures
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- 'All required radar chart features present: alpha-blended fills, closed polygon,
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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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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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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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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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criteria_checklist:
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visual_quality:
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score: 30
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max: 30
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items:
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- id: VQ-01
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name: Text Legibility
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score: 8
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max: 8
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passed: true
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comment: Title 26pt, category labels 20pt, tick labels 16pt, legend 18pt —
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all explicitly set, all readable in both themes
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- id: VQ-02
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name: No Overlap
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score: 6
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max: 6
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passed: true
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comment: No overlapping text elements; category labels well-spaced around
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perimeter; tick labels and axis labels remain distinct
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- id: VQ-03
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name: Element Visibility
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score: 6
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max: 6
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passed: true
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comment: Fills at alpha=0.25 show overlap; linewidth=3.5 outlines clearly
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visible; s=150 vertex markers add emphasis
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- id: VQ-04
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name: Color Accessibility
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score: 2
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max: 2
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passed: true
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comment: '#009E73 and #D55E00 are CVD-safe (Okabe-Ito); high luminance contrast
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between series'
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- id: VQ-05
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name: Layout & Canvas
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score: 4
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max: 4
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passed: true
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comment: Square 3600x3600 canvas appropriate for radar; chart fills ~70-75%
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of canvas; legend positioned at upper right without crowding data
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- id: VQ-06
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name: Axis Labels & Title
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score: 2
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max: 2
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passed: true
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comment: Title uses correct format; category labels are descriptive competency
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names
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- id: VQ-07
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name: Palette Compliance
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score: 2
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max: 2
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passed: true
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comment: 'First series #009E73 (correct), second #D55E00 (correct Okabe-Ito
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order); backgrounds #FAF8F1 light / #1A1A17 dark; data colors identical
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across themes; chrome adapts correctly'
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design_excellence:
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score: 12
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max: 20
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items:
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- id: DE-01
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name: Aesthetic Sophistication
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score: 5
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max: 8
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passed: true
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comment: Above default — Okabe-Ito palette, alpha-blended fills, vertex markers,
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styled polar spine, font hierarchy. Not yet at publication-ready level.
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- id: DE-02
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name: Visual Refinement
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score: 4
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max: 6
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passed: true
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comment: Subtle grid (alpha 0.20-0.25), styled polar spine (color+alpha=0.4),
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generous title pad=40, legend framealpha=0.95. Good refinement for radar.
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- id: DE-03
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name: Data Storytelling
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score: 3
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max: 6
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passed: true
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comment: Complementary skill profiles (Technical vs Leadership) imply a story
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but no visual hierarchy guides the viewer. Story is implicit in data shape,
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not reinforced by design.
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spec_compliance:
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score: 15
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max: 15
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items:
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- id: SC-01
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name: Plot Type
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score: 5
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max: 5
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passed: true
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comment: Correct radar/spider chart using polar projection with filled polygons
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- id: SC-02
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name: Required Features
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score: 4
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max: 4
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passed: true
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comment: Alpha ~0.25 fills, gridlines at 20/40/60/80/100, axis labels at outer
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edge, distinct colors, closed polygon, legend — all present
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- id: SC-03
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name: Data Mapping
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score: 3
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max: 3
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passed: true
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comment: 6 axes (within 4-8 range), 2 series (within 1-3 range), 0-100 scale
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as recommended
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- id: SC-04
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name: Title & Legend
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score: 3
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max: 3
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passed: true
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comment: Title 'radar-basic · seaborn · anyplot.ai' matches format; legend
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labels 'Senior Developer' and 'Team Lead' are meaningful
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data_quality:
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score: 15
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max: 15
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items:
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- id: DQ-01
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name: Feature Coverage
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score: 6
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max: 6
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passed: true
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comment: Shows two distinct polygon shapes with varied values, overlap regions
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visible, contrasting strengths across different competencies
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- id: DQ-02
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name: Realistic Context
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score: 5
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max: 5
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passed: true
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comment: Employee performance comparison is a classic, neutral, real-world
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radar chart use case from the spec's own application examples
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- id: DQ-03
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name: Appropriate Scale
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score: 4
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max: 4
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passed: true
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comment: Values 65-92 are plausible for professional performance; role-based
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patterns (Senior Dev high on Technical, Team Lead high on Leadership/Teamwork)
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are logically consistent
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code_quality:
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score: 10
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max: 10
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items:
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- id: CQ-01
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name: KISS Structure
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score: 3
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max: 3
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passed: true
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comment: 'Clean linear flow: theme tokens → data → plot → style → save; no
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functions or classes'
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- id: CQ-02
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name: Reproducibility
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score: 2
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max: 2
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passed: true
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comment: Fully deterministic hardcoded data; no random generation needed
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- id: CQ-03
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name: Clean Imports
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score: 2
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max: 2
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passed: true
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comment: os, matplotlib.pyplot, numpy, seaborn — all used
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- id: CQ-04
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name: Code Elegance
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score: 2
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max: 2
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passed: true
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comment: Clean, Pythonic; appropriate complexity; polygon-closing pattern
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is idiomatic for radar charts
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- id: CQ-05
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name: Output & API
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score: 1
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max: 1
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passed: true
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comment: Saves as plot-{THEME}.png with dpi=300 and facecolor set
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library_mastery:
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score: 4
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max: 10
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items:
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- id: LM-01
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name: Idiomatic Usage
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score: 3
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max: 5
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passed: true
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comment: sns.set_theme() with polar matplotlib is the correct seaborn pattern
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for non-native chart types, but all actual plotting uses matplotlib primitives
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(ax.fill, ax.plot, ax.scatter) — seaborn contributes styling only
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- id: LM-02
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name: Distinctive Features
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score: 1
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max: 5
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passed: false
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comment: No seaborn-distinctive plotting features used; this is essentially
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matplotlib with seaborn theming applied
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verdict: REJECTED
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impl_tags:
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dependencies: []
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techniques:
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- polar-projection
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- manual-ticks
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patterns:
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- explicit-figure
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dataprep: []
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styling:
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- alpha-blending
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- grid-styling

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