chore(bokeh): update quality score 90 and review feedback for line-retention-cohort

Author: github-actions[bot]

plots/line-retention-cohort/implementations/bokeh.py

@@ -1,7 +1,7 @@
-"""pyplots.ai
+""" pyplots.ai
 line-retention-cohort: User Retention Curve by Cohort
 Library: bokeh 3.9.0 | Python 3.14.3
-Quality: 87/100 | Created: 2026-03-16
+Quality: 90/100 | Created: 2026-03-16
 """
 
 import numpy as np

plots/line-retention-cohort/metadata/bokeh.yaml

@@ -1,7 +1,7 @@
 library: bokeh
 specification_id: line-retention-cohort
 created: '2026-03-16T20:44:38Z'
-updated: '2026-03-16T20:56:18Z'
+updated: '2026-03-16T21:02:56Z'
 generated_by: claude-opus-4-5-20251101
 workflow_run: 23164943124
 issue: 4572
@@ -10,100 +10,102 @@ library_version: 3.9.0
 preview_url: https://storage.googleapis.com/pyplots-images/plots/line-retention-cohort/bokeh/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/line-retention-cohort/bokeh/plot_thumb.png
 preview_html: https://storage.googleapis.com/pyplots-images/plots/line-retention-cohort/bokeh/plot.html
-quality_score: 87
+quality_score: 90
 review:
   strengths:
-  - Perfect spec compliance - all required features including visual hierarchy and
-    threshold line
-  - Clean well-structured code with full reproducibility
-  - Good data storytelling through graduated visual emphasis on newer cohorts
-  - Dual output (PNG + HTML) leverages Bokeh strengths
+  - Excellent spec compliance — every requirement from the specification is implemented
+  - Strong visual hierarchy through progressive line width and opacity that emphasizes
+    newer cohorts
+  - Idiomatic Bokeh usage with ColumnDataSource, HoverTool, and dual PNG/HTML output
+  - Custom colorblind-safe palette with warm-to-cool progression
+  - Clean, well-structured code with good reproducibility
   weaknesses:
-  - Monochromatic blue palette needs more hue variation for cohort differentiation
-    and accessibility
-  - Jan 2025 line at alpha 0.55 is slightly too faint against light background
-  - HTML output missing HoverTool - Bokeh key distinctive feature
-  - No annotation or label on the 20% threshold line
-  image_description: 'The plot shows a line chart with 5 user retention curves for
-    monthly signup cohorts (Jan-May 2025). All curves start at 100% at week 0 and
-    decay over 12 weeks. The lines use a palette spanning warm amber (Jan 2025, lightest/thinnest)
-    through teal and blue to dark navy (May 2025, thickest/most opaque), creating
-    a clear visual hierarchy emphasizing newer cohorts. Circle markers sit on each
-    data point with white borders. A horizontal dashed gray line marks the 20% retention
-    threshold. The legend in the top-right shows cohort labels with sample sizes (e.g.,
-    "Jan 2025 (n=1,245)"). Title reads "line-retention-cohort · bokeh · pyplots.ai".
-    X-axis: "Weeks Since Signup", Y-axis: "Retention Rate (%)". Background is light
-    gray (#fafafa) with subtle dashed y-gridlines and no x-gridlines. Toolbar is hidden.'
+  - Legend and threshold label text could be slightly larger for better readability
+    on the large canvas
+  - Axis spines are still fully present — removing top/right spines would improve
+    visual refinement
+  - Cohort curves converge at later weeks, making individual lines harder to distinguish
+  image_description: The plot displays 5 user retention cohort curves (Jan–May 2025)
+    on a light gray background. All curves start at 100% retention at week 0 and decay
+    over 12 weeks. Colors progress from warm gold/amber (Jan 2025) through teal (Feb),
+    dark blue (Mar), purple (Apr), to dark navy (May 2025). Line widths increase and
+    opacity grows from older to newer cohorts, visually emphasizing the most recent
+    cohort. Each data point has a circular marker with a white edge. A horizontal
+    dashed gray line at 20% marks a retention threshold, labeled "20% Threshold" near
+    the right edge. The legend in the top-right corner lists all cohorts with sample
+    sizes (e.g., "Jan 2025 (n=1,245)"). Y-axis runs from 0 to ~105% with subtle dashed
+    gridlines; X-axis shows "Weeks Since Signup" from 0 to 12. Title reads "line-retention-cohort
+    · bokeh · pyplots.ai" in dark text at top-left.
   criteria_checklist:
     visual_quality:
       score: 28
       max: 30
       items:
       - id: VQ-01
         name: Text Legibility
-        score: 8
+        score: 7
         max: 8
         passed: true
         comment: All font sizes explicitly set (title 42pt, labels 32pt, ticks 24pt,
-          legend 20pt), all clearly readable
+          legend 20pt). Legend and threshold label readable but slightly small for
+          canvas size.
       - id: VQ-02
         name: No Overlap
         score: 6
         max: 6
         passed: true
-        comment: No overlapping text; legend positioned in top-right without occluding
-          data
+        comment: No text overlaps. Legend positioned clear of data.
       - id: VQ-03
         name: Element Visibility
         score: 5
         max: 6
         passed: true
-        comment: Lines and markers well-sized; Jan 2025 line at alpha=0.55 slightly
-          faint
+        comment: Lines and markers clearly visible. Curves converge at later weeks
+          making distinction harder.
       - id: VQ-04
         name: Color Accessibility
-        score: 3
+        score: 4
         max: 4
         passed: true
-        comment: Colors distinguishable but monochromatic blue palette relies on luminance
-          differences
+        comment: Gold, teal, blue, purple, navy palette avoids red-green confusion.
       - id: VQ-05
         name: Layout & Canvas
         score: 4
         max: 4
         passed: true
-        comment: Plot fills canvas well with balanced margins
+        comment: Plot fills canvas well with balanced margins.
       - id: VQ-06
         name: Axis Labels & Title
         score: 2
         max: 2
         passed: true
-        comment: Descriptive labels with units
+        comment: 'Descriptive labels with units: Weeks Since Signup, Retention Rate
+          (%).'
     design_excellence:
-      score: 13
+      score: 14
       max: 20
       items:
       - id: DE-01
         name: Aesthetic Sophistication
-        score: 5
+        score: 6
         max: 8
         passed: true
-        comment: Thoughtful hierarchy with graduated line widths, alphas, marker sizes;
-          custom background; above defaults but not publication-quality
+        comment: Custom palette with warm-to-cool progression. Intentional hierarchy
+          through line width and opacity. Above defaults but not FiveThirtyEight-level.
       - id: DE-02
         name: Visual Refinement
         score: 4
         max: 6
         passed: true
-        comment: X-grid removed, y-grid subtle dashed, custom background, toolbar
-          removed, axis styling customized
+        comment: Subtle y-grid (dashed, alpha 0.15), x-grid removed, light gray background.
+          Axis spines still fully present.
       - id: DE-03
         name: Data Storytelling
         score: 4
         max: 6
         passed: true
-        comment: Clear visual hierarchy through line width/opacity progression; 20%
-          threshold adds benchmark context
+        comment: Progressive line width/opacity emphasizes newer cohorts. 20% threshold
+          adds business context. Data shows improving retention over time.
     spec_compliance:
       score: 15
       max: 15
@@ -113,26 +115,27 @@ review:
         score: 5
         max: 5
         passed: true
-        comment: Correct line chart with retention curves
+        comment: Correct line chart showing retention curves by cohort.
       - id: SC-02
         name: Required Features
         score: 4
         max: 4
         passed: true
-        comment: All spec features present including visual hierarchy and threshold
-          line
+        comment: 'All spec requirements implemented: 100% start, distinct colors,
+          legend with sizes, gridlines, reference line.'
       - id: SC-03
         name: Data Mapping
         score: 3
         max: 3
         passed: true
-        comment: X=weeks since signup, Y=retention rate percentage
+        comment: X=weeks since signup, Y=retention rate percentage. Correct mapping.
       - id: SC-04
         name: Title & Legend
         score: 3
         max: 3
         passed: true
-        comment: Title format correct; legend labels match spec format
+        comment: Title follows spec-id · library · pyplots.ai format. Legend labels
+          use cohort (n=size) format.
     data_quality:
       score: 14
       max: 15
@@ -142,20 +145,22 @@ review:
         score: 5
         max: 6
         passed: true
-        comment: 5 cohorts with different decay rates showing improving retention
-          trend; could use more pattern variety
+        comment: 5 cohorts with varying decay rates. Good spread but could show more
+          variation in curve shapes.
       - id: DQ-02
         name: Realistic Context
         score: 5
         max: 5
         passed: true
-        comment: Monthly SaaS signup cohorts with realistic user counts
+        comment: Monthly signup cohorts for a product. Cohort sizes 1,245-1,680 are
+          plausible for mid-size SaaS.
       - id: DQ-03
         name: Appropriate Scale
         score: 4
         max: 4
         passed: true
-        comment: Cohort sizes and retention decay rates realistic for SaaS products
+        comment: Retention decays realistically from 100%. Final values 12-32% at
+          week 12 are consistent with typical retention curves.
     code_quality:
       score: 10
       max: 10
@@ -165,53 +170,56 @@ review:
         score: 3
         max: 3
         passed: true
-        comment: Clean imports-data-plot-style-save flow
+        comment: Clean Imports → Data → Plot → Save structure. No functions or classes.
       - id: CQ-02
         name: Reproducibility
         score: 2
         max: 2
         passed: true
-        comment: np.random.seed(42) set
+        comment: np.random.seed(42) set.
       - id: CQ-03
         name: Clean Imports
         score: 2
         max: 2
         passed: true
-        comment: All imports used
+        comment: All imports used including output_file/save for HTML export.
       - id: CQ-04
         name: Code Elegance
         score: 2
         max: 2
         passed: true
-        comment: Clean, Pythonic, appropriate complexity
+        comment: Clean, well-organized code with appropriate complexity.
       - id: CQ-05
         name: Output & API
         score: 1
         max: 1
         passed: true
-        comment: Saves as plot.png via export_png, also saves HTML
+        comment: Saves as plot.png via export_png. Also saves interactive HTML.
     library_mastery:
-      score: 7
+      score: 9
       max: 10
       items:
       - id: LM-01
         name: Idiomatic Usage
-        score: 4
+        score: 5
         max: 5
         passed: true
-        comment: Good use of ColumnDataSource, figure, Legend, Span models
+        comment: Excellent use of ColumnDataSource, figure API, Legend model, Span,
+          Label, HoverTool.
       - id: LM-02
         name: Distinctive Features
-        score: 3
+        score: 4
         max: 5
         passed: true
-        comment: Uses Span, manual Legend, HTML export; missing HoverTool for interactive
-          version
-  verdict: REJECTED
+        comment: HoverTool with tooltips, dual PNG+HTML output, ColumnDataSource data
+          binding, Span for reference lines.
+  verdict: APPROVED
 impl_tags:
   dependencies: []
   techniques:
+  - hover-tooltips
   - custom-legend
+  - annotations
   - html-export
   patterns:
   - data-generation
@@ -220,5 +228,5 @@ impl_tags:
   dataprep: []
   styling:
   - alpha-blending
-  - grid-styling
   - edge-highlighting
+  - grid-styling