chore(letsplot): update quality score 85 and review feedback for line-retention-cohort

Author: github-actions[bot]

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

@@ -1,7 +1,7 @@
-"""pyplots.ai
+""" pyplots.ai
 line-retention-cohort: User Retention Curve by Cohort
-Library: letsplot | Python 3.13
-Quality: pending | Created: 2026-03-16
+Library: letsplot 4.9.0 | Python 3.14.3
+Quality: 85/100 | Created: 2026-03-16
 """
 
 import numpy as np

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

@@ -1,10 +1,7 @@
-# Per-library metadata for letsplot implementation of line-retention-cohort
-# Auto-generated by impl-generate.yml
-
 library: letsplot
 specification_id: line-retention-cohort
 created: '2026-03-16T20:44:20Z'
-updated: '2026-03-16T20:44:20Z'
+updated: '2026-03-16T20:48:18Z'
 generated_by: claude-opus-4-5-20251101
 workflow_run: 23164943466
 issue: 4572
@@ -13,7 +10,213 @@ library_version: 4.9.0
 preview_url: https://storage.googleapis.com/pyplots-images/plots/line-retention-cohort/letsplot/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/line-retention-cohort/letsplot/plot_thumb.png
 preview_html: https://storage.googleapis.com/pyplots-images/plots/line-retention-cohort/letsplot/plot.html
-quality_score: null
+quality_score: 85
 review:
-  strengths: []
-  weaknesses: []
+  strengths:
+  - Perfect spec compliance — all required features present including reference line,
+    cohort sizes in legend, and lighter colors for older cohorts
+  - Effective data storytelling through monochromatic color gradient that naturally
+    conveys temporal ordering
+  - Clean, well-structured code following KISS principles with proper reproducibility
+  weaknesses:
+  - Monochromatic blue palette makes it harder to distinguish individual cohorts —
+    especially the middle three lines
+  - Library mastery does not leverage letsplot-specific interactive features (tooltips
+    for HTML output, geom_text for endpoint labels)
+  - Could push design further with endpoint value annotations or a more varied colorblind-friendly
+    palette
+  image_description: The plot displays 5 retention curves (Jan–May 2025) on a clean
+    minimal background. Lines use a monochromatic blue palette graduating from light
+    blue (Jan 2025, oldest) to dark navy (May 2025, newest). All curves start at 100%
+    at week 0 and decay over 12 weeks, with newer cohorts retaining better. Points
+    are marked on each line. A horizontal gray dashed reference line sits at 20%.
+    The title reads "line-retention-cohort · letsplot · pyplots.ai" centered at top.
+    X-axis is labeled "Weeks Since Signup" (0–12, even ticks), Y-axis "Retained Users
+    (%)" (0–100, gridlines at 20% intervals). Legend on the right shows cohort names
+    with sample sizes (e.g., "Jan 2025 (n=1,245)"). Subtle gray major gridlines, no
+    minor gridlines. Overall layout is well-proportioned with good canvas utilization.
+  criteria_checklist:
+    visual_quality:
+      score: 27
+      max: 30
+      items:
+      - id: VQ-01
+        name: Text Legibility
+        score: 7
+        max: 8
+        passed: true
+        comment: All font sizes explicitly set (title=28, axis_title=22, axis_text=18,
+          legend=16), all clearly readable
+      - id: VQ-02
+        name: No Overlap
+        score: 6
+        max: 6
+        passed: true
+        comment: No overlapping elements anywhere
+      - id: VQ-03
+        name: Element Visibility
+        score: 5
+        max: 6
+        passed: true
+        comment: Lines and points well-visible; some convergence in similar blue shades
+      - id: VQ-04
+        name: Color Accessibility
+        score: 3
+        max: 4
+        passed: true
+        comment: Monochromatic blue palette distinguishable by lightness but not ideal
+          for all viewers
+      - id: VQ-05
+        name: Layout & Canvas
+        score: 4
+        max: 4
+        passed: true
+        comment: Excellent proportions, plot fills canvas well
+      - id: VQ-06
+        name: Axis Labels & Title
+        score: 2
+        max: 2
+        passed: true
+        comment: Descriptive labels with units
+    design_excellence:
+      score: 13
+      max: 20
+      items:
+      - id: DE-01
+        name: Aesthetic Sophistication
+        score: 5
+        max: 8
+        passed: true
+        comment: Custom monochromatic blue palette with intentional gradient; above
+          defaults but not publication-level
+      - id: DE-02
+        name: Visual Refinement
+        score: 4
+        max: 6
+        passed: true
+        comment: theme_minimal, subtle grid, minor grid removed, legend title blank
+      - id: DE-03
+        name: Data Storytelling
+        score: 4
+        max: 6
+        passed: true
+        comment: Color gradient guides viewer to improving retention trend; 20% threshold
+          adds benchmark context
+    spec_compliance:
+      score: 15
+      max: 15
+      items:
+      - id: SC-01
+        name: Plot Type
+        score: 5
+        max: 5
+        passed: true
+        comment: Correct line chart with multiple cohort curves
+      - id: SC-02
+        name: Required Features
+        score: 4
+        max: 4
+        passed: true
+        comment: 'All spec features present: 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 percentage
+      - id: SC-04
+        name: Title & Legend
+        score: 3
+        max: 3
+        passed: true
+        comment: Title format correct, legend labels match spec format
+    data_quality:
+      score: 14
+      max: 15
+      items:
+      - id: DQ-01
+        name: Feature Coverage
+        score: 5
+        max: 6
+        passed: true
+        comment: 5 cohorts with varying decay rates; could show more varied curve
+          shapes
+      - id: DQ-02
+        name: Realistic Context
+        score: 5
+        max: 5
+        passed: true
+        comment: Monthly signup cohorts with realistic user counts, standard product
+          analytics scenario
+      - id: DQ-03
+        name: Appropriate Scale
+        score: 4
+        max: 4
+        passed: true
+        comment: Realistic exponential decay, plausible cohort sizes, industry-standard
+          tracking window
+    code_quality:
+      score: 10
+      max: 10
+      items:
+      - id: CQ-01
+        name: KISS Structure
+        score: 3
+        max: 3
+        passed: true
+        comment: Clean imports-data-plot-save flow
+      - id: CQ-02
+        name: Reproducibility
+        score: 2
+        max: 2
+        passed: true
+        comment: np.random.seed(42) set
+      - id: CQ-03
+        name: Clean Imports
+        score: 2
+        max: 2
+        passed: true
+        comment: All imports used
+      - id: CQ-04
+        name: Code Elegance
+        score: 2
+        max: 2
+        passed: true
+        comment: Clean, appropriate complexity
+      - id: CQ-05
+        name: Output & API
+        score: 1
+        max: 1
+        passed: true
+        comment: Saves as plot.png with ggsave, current API
+    library_mastery:
+      score: 6
+      max: 10
+      items:
+      - id: LM-01
+        name: Idiomatic Usage
+        score: 4
+        max: 5
+        passed: true
+        comment: Good ggplot2-style grammar usage
+      - id: LM-02
+        name: Distinctive Features
+        score: 2
+        max: 5
+        passed: false
+        comment: Uses ggsize and ggsave with scale but lacks more distinctive letsplot
+          features
+  verdict: REJECTED
+impl_tags:
+  dependencies: []
+  techniques:
+  - layer-composition
+  - html-export
+  patterns:
+  - data-generation
+  - iteration-over-groups
+  dataprep: []
+  styling:
+  - alpha-blending
+  - grid-styling