chore(plotnine): update quality score 88 and review feedback for heatmap-cohort-retention

Author: github-actions[bot]

plots/heatmap-cohort-retention/implementations/plotnine.py

@@ -1,7 +1,7 @@
-"""pyplots.ai
+""" pyplots.ai
 heatmap-cohort-retention: Cohort Retention Heatmap
 Library: plotnine 0.15.3 | Python 3.14.3
-Quality: 85/100 | Created: 2026-03-16
+Quality: 88/100 | Created: 2026-03-16
 """
 
 import numpy as np

plots/heatmap-cohort-retention/metadata/plotnine.yaml

@@ -1,7 +1,7 @@
 library: plotnine
 specification_id: heatmap-cohort-retention
 created: '2026-03-16T20:45:25Z'
-updated: '2026-03-16T20:57:00Z'
+updated: '2026-03-16T21:04:52Z'
 generated_by: claude-opus-4-5-20251101
 workflow_run: 23165008156
 issue: 4570
@@ -10,34 +10,34 @@ library_version: 0.15.3
 preview_url: https://storage.googleapis.com/pyplots-images/plots/heatmap-cohort-retention/plotnine/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/heatmap-cohort-retention/plotnine/plot_thumb.png
 preview_html: null
-quality_score: 85
+quality_score: 88
 review:
   strengths:
-  - Perfect spec compliance with all required features (triangular shape, cell annotations,
-    cohort sizes, color bar)
-  - Clean well-structured code following KISS principles with proper reproducibility
-  - Custom color palette with thoughtful text color contrast (white on dark, dark
-    on light cells)
-  - 'Good visual refinement: grid removed, tile borders, custom background'
+  - Excellent spec compliance — all required features implemented perfectly (triangular
+    shape, cell annotations, cohort sizes, colorbar)
+  - Strong data storytelling with retention improvement annotation and insightful
+    subtitle
+  - Custom 3-stop color palette (cream to teal to navy) is visually distinctive and
+    cohesive
+  - Conditional text coloring (white on dark, dark on light) ensures readability throughout
+  - Clean well-structured code following KISS principles
   weaknesses:
-  - Best Month 3 annotation is weak storytelling — 50% is not compelling and annotation
-    floats disconnectedly
-  - Subtitle claims improving retention trends but data barely shows this (trend_bonus
-    too small)
-  - 8-stop color gradient creates muddy mid-range transitions
-  - Cell text size slightly small for optimal readability
-  image_description: 'The plot displays a triangular cohort retention heatmap with
-    10 monthly cohorts (Jan 2024 – Oct 2024) on the y-axis and months since signup
-    (Month 0 – Month 9) on the x-axis. Each cell contains a bold retention percentage.
-    The color gradient transitions from warm amber/cream (low retention, ~11%) through
-    teal to deep navy (high retention, 100%). White tile borders separate cells cleanly.
-    The triangular shape correctly emerges with earlier cohorts having more columns.
-    Cohort sizes (e.g., n=1,200) appear in parentheses alongside cohort labels. A
-    "Retention %" color bar legend is positioned on the right. An annotation "Best
-    Month 3: Feb 2024 50%" floats in the empty triangle area. Title follows the required
-    format: "heatmap-cohort-retention · plotnine · pyplots.ai". Subtitle reads "Monthly
-    cohort retention — later cohorts show improving retention trends" in italic. Background
-    is light gray.'
+  - Color palette not perceptually uniform — consider viridis or cividis for more
+    even gradation
+  - X-axis label rotation at 45 degrees slightly awkward — shorter labels or horizontal
+    orientation would be cleaner
+  image_description: The plot displays a triangular cohort retention heatmap with
+    10 monthly cohorts (Jan 2024 – Oct 2024) on the y-axis, each labeled with cohort
+    size (e.g., "Jan 2024 (n=1,200)"). The x-axis shows "Month 0" through "Month 9"
+    rotated at 45 degrees. Cells use a 3-stop sequential color gradient from cream/light
+    yellow (low retention) through teal to deep navy (high retention). Each cell contains
+    bold white or dark text showing the retention percentage. The triangular shape
+    is correct — Jan 2024 has 10 columns, Oct 2024 has 1. Period 0 is 100% for all
+    cohorts. A colorbar legend labeled "Retention %" appears on the right. An annotation
+    in the empty lower-right area reads "Month 4 retention improved +8pp from Jan→Jun
+    2024". The title follows the required format "heatmap-cohort-retention · plotnine
+    · pyplots.ai". Background is a subtle off-white (#fafafa). Overall layout is clean
+    and professional.
   criteria_checklist:
     visual_quality:
       score: 27
@@ -48,64 +48,68 @@ review:
         score: 7
         max: 8
         passed: true
-        comment: All font sizes explicitly set. Cell text size 11 could be slightly
-          larger (12-13).
+        comment: All font sizes explicitly set (title 26pt, subtitle 18pt, axis text
+          16pt, cell text 13pt bold). All readable; cell text slightly small but clear.
       - id: VQ-02
         name: No Overlap
         score: 6
         max: 6
         passed: true
-        comment: No overlapping text anywhere.
+        comment: No overlapping text anywhere. Annotation placed in empty triangular
+          area.
       - id: VQ-03
         name: Element Visibility
         score: 6
         max: 6
         passed: true
-        comment: All tiles clearly visible with strong color differentiation.
+        comment: All tiles clearly visible with good color differentiation across
+          the retention range.
       - id: VQ-04
         name: Color Accessibility
         score: 3
         max: 4
         passed: true
-        comment: Custom gradient is distinguishable but not a standard colorblind-safe
-          palette.
+        comment: Sequential cream-teal-navy gradient is colorblind-friendly but not
+          perceptually uniform.
       - id: VQ-05
         name: Layout & Canvas
         score: 3
         max: 4
         passed: true
-        comment: Good proportions. Empty triangle area and floating annotation create
-          slight imbalance.
+        comment: Good 16:9 proportions, nothing cut off. X-axis labels rotated 45
+          degrees slightly awkward.
       - id: VQ-06
         name: Axis Labels & Title
         score: 2
         max: 2
         passed: true
-        comment: Descriptive labels with context.
+        comment: Months Since Signup is descriptive, y-axis shows cohort labels with
+          sizes.
     design_excellence:
-      score: 12
+      score: 14
       max: 20
       items:
       - id: DE-01
         name: Aesthetic Sophistication
-        score: 5
+        score: 6
         max: 8
         passed: true
-        comment: Custom palette and tile borders above defaults, but multi-stop gradient
-          creates muddy mid-range.
+        comment: Custom 3-stop color palette, conditional text coloring, cohesive
+          design clearly above defaults.
       - id: DE-02
         name: Visual Refinement
         score: 4
         max: 6
         passed: true
-        comment: Grid removed, custom background, italic subtitle, white tile borders.
+        comment: Panel grid removed, custom tile borders, subtle off-white background,
+          clean whitespace.
       - id: DE-03
         name: Data Storytelling
-        score: 3
+        score: 4
         max: 6
         passed: true
-        comment: Subtitle and annotation add narrative but Best Month 3 at 50% is
-          uncompelling.
+        comment: Annotation comparing Jan vs Jun retention creates focal point. Subtitle
+          communicates key insight.
     spec_compliance:
       score: 15
       max: 15
@@ -121,42 +125,45 @@ review:
         score: 4
         max: 4
         passed: true
-        comment: 'All features present: triangular shape, cell annotations, cohort
-          sizes, color bar.'
+        comment: 'All spec features present: triangular shape, retention percentages
+          in cells, cohort sizes, colorbar, sequential colormap.'
       - id: SC-03
         name: Data Mapping
         score: 3
         max: 3
         passed: true
-        comment: Correct mapping of periods, cohorts, and retention rate.
+        comment: X=periods, Y=cohorts, fill=retention_rate. All correct.
       - id: SC-04
         name: Title & Legend
         score: 3
         max: 3
         passed: true
-        comment: Correct title format and color bar legend.
+        comment: Title matches required format. Colorbar legend labeled Retention
+          %.
     data_quality:
-      score: 14
+      score: 15
       max: 15
       items:
       - id: DQ-01
         name: Feature Coverage
-        score: 5
+        score: 6
         max: 6
         passed: true
-        comment: Shows all aspects but improving trend claim barely visible in data.
+        comment: 'Shows all aspects: triangular shape, exponential decay, cohort variation,
+          period 0 = 100%, improving trend.'
       - id: DQ-02
         name: Realistic Context
         score: 5
         max: 5
         passed: true
-        comment: Realistic SaaS cohort retention scenario.
+        comment: SaaS monthly cohort retention with realistic user counts and decay
+          patterns. Neutral business domain.
       - id: DQ-03
         name: Appropriate Scale
         score: 4
         max: 4
         passed: true
-        comment: Sensible values with exponential decay.
+        comment: 10 cohorts, sizes 980-1450, realistic exponential decay with noise.
     code_quality:
       score: 10
       max: 10
@@ -166,7 +173,7 @@ review:
         score: 3
         max: 3
         passed: true
-        comment: Linear script structure.
+        comment: 'Flat script: imports, data, plot, save. No functions or classes.'
       - id: CQ-02
         name: Reproducibility
         score: 2
@@ -178,19 +185,19 @@ review:
         score: 2
         max: 2
         passed: true
-        comment: All imports used.
+        comment: All imports are used.
       - id: CQ-04
         name: Code Elegance
         score: 2
         max: 2
         passed: true
-        comment: Clean, well-organized, no fake UI.
+        comment: Clean, appropriate complexity. No fake UI or over-engineering.
       - id: CQ-05
         name: Output & API
         score: 1
         max: 1
         passed: true
-        comment: Saves as plot.png with current API.
+        comment: Saves as plot.png with current plotnine API.
     library_mastery:
       score: 7
       max: 10
@@ -200,15 +207,16 @@ review:
         score: 4
         max: 5
         passed: true
-        comment: Good grammar of graphics usage with proper layering and scales.
+        comment: 'Good grammar of graphics composition: aes, geom_tile, geom_text,
+          scale_fill_gradientn, theme_minimal with customization.'
       - id: LM-02
         name: Distinctive Features
         score: 3
         max: 5
         passed: true
-        comment: Uses scale_fill_gradientn, scale_color_identity, annotate. Grammar
-          of graphics composition is distinctly plotnine.
-  verdict: REJECTED
+        comment: Uses scale_fill_gradientn, scale_color_identity for conditional text
+          colors, pd.Categorical ordering, annotate layer.
+  verdict: APPROVED
 impl_tags:
   dependencies: []
   techniques: