diff --git a/plots/bar-basic/implementations/plotly.py b/plots/bar-basic/implementations/plotly.py
index fa23798ed0..443e6a8b99 100644
--- a/plots/bar-basic/implementations/plotly.py
+++ b/plots/bar-basic/implementations/plotly.py
@@ -1,16 +1,19 @@
 """ pyplots.ai
 bar-basic: Basic Bar Chart
-Library: plotly 6.5.0 | Python 3.13.11
-Quality: 100/100 | Created: 2025-12-13
+Library: plotly 6.5.2 | Python 3.14
+Quality: 92/100 | Created: 2026-02-14
 """
 
 import plotly.graph_objects as go
 
 
-# Data
+# Data — product sales by department, sorted descending
 categories = ["Electronics", "Clothing", "Home & Garden", "Sports", "Books", "Toys", "Automotive", "Health"]
 values = [45200, 38700, 31500, 27800, 24300, 21600, 18900, 15400]
 
+# Highlight the top performer with a distinct shade
+bar_colors = ["#1A4971"] + ["#306998"] * (len(categories) - 1)
+
 # Create figure
 fig = go.Figure()
 
@@ -18,26 +21,73 @@
     go.Bar(
         x=categories,
         y=values,
-        marker_color="#306998",
+        marker={"color": bar_colors, "line": {"color": "rgba(0,0,0,0.08)", "width": 1}},
         text=values,
         textposition="outside",
-        texttemplate="%{text:,.0f}",
-        textfont={"size": 32},
+        texttemplate="$%{text:,.0f}",
+        textfont={"size": 20, "color": "#444444"},
+        hovertemplate="<b>%{x}</b><br>Sales: $%{y:,.0f}<extra></extra>",
     )
 )
 
+# Annotation: highlight the leading category with an insight callout
+fig.add_annotation(
+    x="Electronics",
+    y=45200,
+    text="<b>Top seller</b><br>17% ahead of #2",
+    showarrow=True,
+    arrowhead=2,
+    arrowsize=1.2,
+    arrowwidth=2,
+    arrowcolor="#1A4971",
+    ax=100,
+    ay=-75,
+    font={"size": 18, "color": "#1A4971"},
+    align="left",
+    bordercolor="#1A4971",
+    borderwidth=1.5,
+    borderpad=6,
+    bgcolor="rgba(255,255,255,0.85)",
+)
+
+# Subtle average reference line
+avg_value = sum(values) / len(values)
+fig.add_hline(
+    y=avg_value,
+    line={"color": "rgba(0,0,0,0.25)", "width": 1.5, "dash": "dot"},
+    annotation={
+        "text": f"Avg ${avg_value:,.0f}",
+        "font": {"size": 16, "color": "#666666"},
+        "showarrow": False,
+        "xanchor": "left",
+    },
+)
+
 # Layout
 fig.update_layout(
-    title={"text": "bar-basic · plotly · pyplots.ai", "font": {"size": 40}, "x": 0.5, "xanchor": "center"},
-    xaxis={"title": {"text": "Product Category", "font": {"size": 40}}, "tickfont": {"size": 32}},
+    title={
+        "text": "bar-basic · plotly · pyplots.ai",
+        "font": {"size": 28, "color": "#222222"},
+        "x": 0.5,
+        "xanchor": "center",
+    },
+    xaxis={
+        "title": {"text": "Product Category", "font": {"size": 22, "color": "#333333"}},
+        "tickfont": {"size": 18, "color": "#444444"},
+    },
     yaxis={
-        "title": {"text": "Sales ($)", "font": {"size": 40}},
-        "tickfont": {"size": 32},
-        "gridcolor": "rgba(0,0,0,0.1)",
+        "title": {"text": "Sales ($)", "font": {"size": 22, "color": "#333333"}},
+        "tickfont": {"size": 18, "color": "#444444"},
+        "tickprefix": "$",
+        "tickformat": ",.0f",
+        "gridcolor": "rgba(0,0,0,0.07)",
+        "zeroline": False,
     },
     template="plotly_white",
     bargap=0.3,
-    margin={"t": 120, "b": 80, "l": 100, "r": 50},
+    margin={"t": 100, "b": 80, "l": 100, "r": 120},
+    plot_bgcolor="white",
+    showlegend=False,
 )
 
 # Save
diff --git a/plots/bar-basic/metadata/plotly.yaml b/plots/bar-basic/metadata/plotly.yaml
index 3860648bbf..eb18e60844 100644
--- a/plots/bar-basic/metadata/plotly.yaml
+++ b/plots/bar-basic/metadata/plotly.yaml
@@ -1,26 +1,235 @@
 library: plotly
 specification_id: bar-basic
 created: 2025-12-13 23:14:18+00:00
-updated: 2025-12-13 23:14:18+00:00
-generated_by: claude-opus-4-5-20251101
+updated: '2026-02-14T14:55:26Z'
+generated_by: claude-opus-4-6
 workflow_run: 20199224291
 issue: 612
-python_version: 3.13.11
-library_version: 6.5.0
+python_version: '3.14'
+library_version: 6.5.2
 preview_url: https://storage.googleapis.com/pyplots-images/plots/bar-basic/plotly/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/bar-basic/plotly/plot_thumb.png
 preview_html: https://storage.googleapis.com/pyplots-images/plots/bar-basic/plotly/plot.html
-quality_score: 100
+quality_score: 92
 impl_tags:
   dependencies: []
   techniques:
+  - annotations
   - html-export
-  patterns:
-  - explicit-figure
+  patterns: []
   dataprep: []
-  styling: []
+  styling:
+  - edge-highlighting
+  - grid-styling
 review:
-  strengths: []
-  weaknesses: []
+  strengths:
+  - 'Excellent data storytelling with the Top seller annotation providing contextual
+    insight (17% ahead of #2) and the average reference line giving statistical context'
+  - All font sizes explicitly set and well-calibrated for 4800x2700 output — perfectly
+    readable
+  - Clean, idiomatic Plotly code with good use of library-specific features (hovertemplate,
+    texttemplate, add_hline with annotation)
+  - Thoughtful visual hierarchy with subtle darker shade for top performer and minimal
+    bar outlines
+  - Dual output (PNG + interactive HTML) leverages Plotly interactive strengths
+  weaknesses:
+  - The Top seller annotation box overlaps/crowds the $45,200 value label on the Electronics
+    bar, creating visual clutter at the most important data point
+  - The color contrast between the highlighted top bar (#1A4971) and regular bars
+    (#306998) is quite subtle — could be more visually distinct to reinforce the storytelling
+  - The average line annotation is pushed to the far right margin — could be positioned
+    more prominently
   improvements: []
   verdict: APPROVED
+  image_description: 'The plot displays a vertical bar chart titled "bar-basic · plotly
+    · pyplots.ai" centered at the top. Eight bars represent product sales by department,
+    sorted in descending order from left to right: Electronics ($45,200), Clothing
+    ($38,700), Home & Garden ($31,500), Sports ($27,800), Books ($24,300), Toys ($21,600),
+    Automotive ($18,900), and Health ($15,400). Dollar-formatted value labels appear
+    above each bar. The top-performing Electronics bar is rendered in a slightly darker
+    navy blue (#1A4971) while the remaining bars use a medium blue (#306998). A "Top
+    seller / 17% ahead of #2" annotation with an arrow points to the Electronics bar.
+    A dotted horizontal reference line marks the average at $27,925 with a label on
+    the far right. The background is white with very subtle horizontal gridlines.
+    The x-axis is labeled "Product Category" and the y-axis "Sales ($)" with dollar-formatted
+    tick marks. Overall layout is clean and well-proportioned.'
+  criteria_checklist:
+    visual_quality:
+      score: 28
+      max: 30
+      items:
+      - id: VQ-01
+        name: Text Legibility
+        score: 8
+        max: 8
+        passed: true
+        comment: 'All font sizes explicitly set: title 28pt, axis labels 22pt, tick
+          labels 18pt, bar text 20pt. All perfectly readable at 4800x2700.'
+      - id: VQ-02
+        name: No Overlap
+        score: 4
+        max: 6
+        passed: false
+        comment: The Top seller annotation box and the $45,200 value label on the
+          Electronics bar create visual clutter; the annotation arrow and value text
+          compete for the same space.
+      - id: VQ-03
+        name: Element Visibility
+        score: 6
+        max: 6
+        passed: true
+        comment: Bars well-sized with appropriate bargap (0.3), all elements clearly
+          visible.
+      - id: VQ-04
+        name: Color Accessibility
+        score: 4
+        max: 4
+        passed: true
+        comment: Single-hue blue palette is inherently colorblind-safe. No red-green
+          differentiation.
+      - id: VQ-05
+        name: Layout Balance
+        score: 4
+        max: 4
+        passed: true
+        comment: Good canvas utilization with balanced margins. Plot fills appropriate
+          portion of canvas.
+      - id: VQ-06
+        name: Axis Labels & Title
+        score: 2
+        max: 2
+        passed: true
+        comment: Product Category and Sales ($) are descriptive with units.
+    design_excellence:
+      score: 16
+      max: 20
+      items:
+      - id: DE-01
+        name: Aesthetic Sophistication
+        score: 6
+        max: 8
+        passed: true
+        comment: Custom color palette with intentional hierarchy, subtle bar outlines,
+          clean plotly_white template. Clearly above defaults, strong design.
+      - id: DE-02
+        name: Visual Refinement
+        score: 5
+        max: 6
+        passed: true
+        comment: Subtle gridlines (rgba 0.07), clean template, generous whitespace,
+          polished margins. Average line label pushed to far right edge.
+      - id: DE-03
+        name: Data Storytelling
+        score: 5
+        max: 6
+        passed: true
+        comment: 'Top seller annotation with contextual insight (17% ahead of #2),
+          average reference line for context. Good narrative elements.'
+    spec_compliance:
+      score: 15
+      max: 15
+      items:
+      - id: SC-01
+        name: Plot Type
+        score: 5
+        max: 5
+        passed: true
+        comment: Correct vertical bar chart.
+      - id: SC-02
+        name: Required Features
+        score: 4
+        max: 4
+        passed: true
+        comment: Consistent bar widths, value labels above bars, single color with
+          highlight, adequate spacing. All spec notes addressed.
+      - id: SC-03
+        name: Data Mapping
+        score: 3
+        max: 3
+        passed: true
+        comment: Categories on x-axis, values on y-axis, correct mapping.
+      - id: SC-04
+        name: Title & Legend
+        score: 3
+        max: 3
+        passed: true
+        comment: Title format bar-basic · plotly · pyplots.ai correct. No legend needed
+          for single series.
+    data_quality:
+      score: 14
+      max: 15
+      items:
+      - id: DQ-01
+        name: Feature Coverage
+        score: 5
+        max: 6
+        passed: true
+        comment: 8 categories with clear variation, sorted descending. Good range
+          ($15K-$45K). Could show more extreme variation.
+      - id: DQ-02
+        name: Realistic Context
+        score: 5
+        max: 5
+        passed: true
+        comment: Product sales by department is a real, neutral business scenario.
+      - id: DQ-03
+        name: Appropriate Scale
+        score: 4
+        max: 4
+        passed: true
+        comment: Sales figures $15K-$45K are realistic for department-level retail
+          sales.
+    code_quality:
+      score: 10
+      max: 10
+      items:
+      - id: CQ-01
+        name: KISS Structure
+        score: 3
+        max: 3
+        passed: true
+        comment: 'Clean flat structure: import, data, figure, annotation, layout,
+          save.'
+      - id: CQ-02
+        name: Reproducibility
+        score: 2
+        max: 2
+        passed: true
+        comment: Deterministic hardcoded data, no randomness needed.
+      - id: CQ-03
+        name: Clean Imports
+        score: 2
+        max: 2
+        passed: true
+        comment: Only plotly.graph_objects imported and used.
+      - id: CQ-04
+        name: Code Elegance
+        score: 2
+        max: 2
+        passed: true
+        comment: Clean, well-organized, appropriate complexity.
+      - id: CQ-05
+        name: Output & API
+        score: 1
+        max: 1
+        passed: true
+        comment: Saves as plot.png (1600x900, scale=3) and plot.html. No deprecated
+          APIs.
+    library_mastery:
+      score: 9
+      max: 10
+      items:
+      - id: LM-01
+        name: Idiomatic Usage
+        score: 5
+        max: 5
+        passed: true
+        comment: 'Expert use of graph_objects API: go.Bar, add_trace, update_layout,
+          add_annotation, add_hline with annotation dict.'
+      - id: LM-02
+        name: Distinctive Features
+        score: 4
+        max: 5
+        passed: true
+        comment: 'Uses Plotly-specific features: hovertemplate, texttemplate, add_hline
+          with embedded annotation, dual output (PNG + HTML).'