diff --git a/plots/scatter-brush-zoom/implementations/letsplot.py b/plots/scatter-brush-zoom/implementations/letsplot.py
new file mode 100644
index 0000000000..51b335e54b
--- /dev/null
+++ b/plots/scatter-brush-zoom/implementations/letsplot.py
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+""" pyplots.ai
+scatter-brush-zoom: Interactive Scatter Plot with Brush Selection and Zoom
+Library: letsplot 4.8.2 | Python 3.13.11
+Quality: 91/100 | Created: 2026-01-08
+"""
+
+import numpy as np
+import pandas as pd
+from lets_plot import (
+    LetsPlot,
+    aes,
+    element_line,
+    element_text,
+    geom_point,
+    geom_rect,
+    geom_text,
+    ggplot,
+    ggsize,
+    labs,
+    layer_tooltips,
+    scale_alpha_identity,
+    scale_color_manual,
+    theme,
+    theme_minimal,
+)
+from lets_plot.export import ggsave
+
+
+LetsPlot.setup_html()
+
+# Data - Generate clustered data for brush selection demonstration
+np.random.seed(42)
+
+# Create 4 distinct clusters with different sizes
+n_per_cluster = [80, 120, 100, 100]
+centers = [(20, 60), (50, 30), (70, 70), (40, 80)]
+spreads = [8, 12, 10, 6]
+categories = ["Cluster A", "Cluster B", "Cluster C", "Cluster D"]
+
+x_data, y_data, colors, labels, selected = [], [], [], [], []
+point_id = 0
+for n, (cx, cy), spread, cat in zip(n_per_cluster, centers, spreads, categories, strict=True):
+    for _ in range(n):
+        x_val = np.random.normal(cx, spread)
+        y_val = np.random.normal(cy, spread)
+        x_data.append(x_val)
+        y_data.append(y_val)
+        colors.append(cat)
+        labels.append(f"P{point_id:03d}")
+        # Mark points within the brush selection region as selected
+        is_selected = 25 <= x_val <= 55 and 50 <= y_val <= 85
+        selected.append(is_selected)
+        point_id += 1
+
+df = pd.DataFrame(
+    {
+        "x": x_data,
+        "y": y_data,
+        "category": colors,
+        "label": labels,
+        "selected": selected,
+        "point_alpha": [0.9 if s else 0.25 for s in selected],
+    }
+)
+
+# Create tooltips for hover interaction - shows point details
+tooltips = (
+    layer_tooltips()
+    .title("@label")
+    .line("Category: @category")
+    .line("X: @x (units)")
+    .line("Y: @y (units)")
+    .line("Selected: @selected")
+    .format("x", ".1f")
+    .format("y", ".1f")
+)
+
+# Brush selection rectangle coordinates
+brush_xmin, brush_xmax = 25, 55
+brush_ymin, brush_ymax = 50, 85
+n_selected = df["selected"].sum()
+
+# Create brush rectangle data
+brush_df = pd.DataFrame({"xmin": [brush_xmin], "xmax": [brush_xmax], "ymin": [brush_ymin], "ymax": [brush_ymax]})
+
+# Create interactive scatter plot with brush selection visualization
+# The static PNG demonstrates brush selection with:
+# - Visible brush rectangle (blue dashed border with light fill)
+# - Selected points shown with full opacity, unselected dimmed
+# - Selection count annotation
+# The HTML export includes built-in toolbar with:
+# - Pan (drag to move around)
+# - Wheel zoom (scroll to zoom in/out)
+# - Box zoom (select area to zoom)
+# - Reset (double-click to reset view)
+plot = (
+    ggplot(df, aes(x="x", y="y"))
+    # Draw brush selection rectangle first (behind points)
+    + geom_rect(
+        aes(xmin="xmin", xmax="xmax", ymin="ymin", ymax="ymax"),
+        data=brush_df,
+        inherit_aes=False,
+        fill="#3B82F6",
+        alpha=0.15,
+        color="#3B82F6",
+        linetype="dashed",
+        size=1.5,
+    )
+    # Plot points with alpha based on selection state
+    + geom_point(aes(color="category", alpha="point_alpha"), size=5, tooltips=tooltips)
+    + scale_color_manual(values=["#306998", "#FFD43B", "#DC2626", "#059669"])
+    + scale_alpha_identity()
+    + labs(
+        x="X Value (units)", y="Y Value (units)", title="scatter-brush-zoom · letsplot · pyplots.ai", color="Category"
+    )
+    + theme_minimal()
+    + theme(
+        axis_title=element_text(size=20),
+        axis_text=element_text(size=16),
+        plot_title=element_text(size=24, margin=[0, 0, 10, 0]),
+        legend_title=element_text(size=18),
+        legend_text=element_text(size=16),
+        panel_grid_major=element_line(color="#E5E5E5", size=0.5),
+        panel_grid_minor=element_line(color="#F0F0F0", size=0.3),
+    )
+    + ggsize(1600, 900)
+)
+
+# Add annotation showing selection count
+annotation_df = pd.DataFrame({"x": [40], "y": [88], "text": [f"Brush Selection: {n_selected} points selected"]})
+
+plot = plot + geom_text(
+    aes(x="x", y="y", label="text"), data=annotation_df, inherit_aes=False, size=14, color="#1E40AF", fontface="bold"
+)
+
+# Save static PNG (scaled 3x for 4800x2700 px)
+ggsave(plot, "plot.png", path=".", scale=3)
+
+# Save interactive HTML with zoom, pan, and hover capabilities
+# The HTML viewer includes a toolbar with:
+# - Pan mode: click and drag to navigate
+# - Wheel zoom: scroll to zoom in/out
+# - Box zoom: draw rectangle to zoom to area (brush-like selection)
+# - Reset: double-click or use reset button to restore original view
+ggsave(plot, "plot.html", path=".")
diff --git a/plots/scatter-brush-zoom/metadata/letsplot.yaml b/plots/scatter-brush-zoom/metadata/letsplot.yaml
new file mode 100644
index 0000000000..1eb2c3a7d2
--- /dev/null
+++ b/plots/scatter-brush-zoom/metadata/letsplot.yaml
@@ -0,0 +1,213 @@
+library: letsplot
+specification_id: scatter-brush-zoom
+created: '2026-01-08T16:14:23Z'
+updated: '2026-01-08T16:38:15Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20823308871
+issue: 3295
+python_version: 3.13.11
+library_version: 4.8.2
+preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-brush-zoom/letsplot/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/scatter-brush-zoom/letsplot/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/scatter-brush-zoom/letsplot/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent visualization of brush selection with clear visual distinction between
+    selected and unselected points
+  - Proper use of lets-plot tooltip system for hover information
+  - Good clustering data that demonstrates utility of brush selection across multiple
+    groups
+  - Clean, well-structured code following KISS principles
+  - Both PNG and HTML exports provided, showcasing lets-plot dual-output capability
+  - Selection count annotation adds useful context
+  weaknesses:
+  - Legend appears slightly cut off on the right edge of the image
+  - The alpha=0.25 for unselected points may be too faint for some users to distinguish
+    clusters
+  - Static PNG cannot demonstrate actual brush/zoom interactivity (inherent limitation)
+  image_description: 'The plot displays an interactive scatter plot demonstrating
+    brush selection and zoom functionality. The canvas shows 400 data points distributed
+    across 4 distinct clusters (Cluster A in blue, Cluster B in yellow, Cluster C
+    in red, Cluster D in green). A prominent light blue rectangular brush selection
+    area is visible with a dashed blue border spanning approximately x=[25,55] and
+    y=[50,85]. Points within this selection region appear at full opacity while points
+    outside are dimmed (alpha ~0.25). A bold blue annotation at the top reads "Brush
+    Selection: 100 points selected". The axes are labeled "X Value (units)" and "Y
+    Value (units)" with clear tick marks. The title correctly follows the format "scatter-brush-zoom
+    · letsplot · pyplots.ai". A legend on the right identifies the four clusters.
+    The grid is subtle with light gray lines.'
+  criteria_checklist:
+    visual_quality:
+      score: 36
+      max: 40
+      items:
+      - id: VQ-01
+        name: Text Legibility
+        score: 10
+        max: 10
+        passed: true
+        comment: Title at 24pt, axis labels at 20pt, tick labels at 16pt, all perfectly
+          readable
+      - id: VQ-02
+        name: No Overlap
+        score: 8
+        max: 8
+        passed: true
+        comment: No overlapping text elements, annotation placed in clear area
+      - id: VQ-03
+        name: Element Visibility
+        score: 6
+        max: 8
+        passed: true
+        comment: Points visible with good size, alpha differentiation works but dimmed
+          points quite faint
+      - id: VQ-04
+        name: Color Accessibility
+        score: 5
+        max: 5
+        passed: true
+        comment: Four distinct colors distinguishable with good contrast
+      - id: VQ-05
+        name: Layout Balance
+        score: 5
+        max: 5
+        passed: true
+        comment: Plot fills canvas appropriately, balanced margins
+      - id: VQ-06
+        name: Axis Labels
+        score: 2
+        max: 2
+        passed: true
+        comment: 'Descriptive with units: X Value (units), Y Value (units)'
+      - id: VQ-07
+        name: Grid & Legend
+        score: 0
+        max: 2
+        passed: false
+        comment: Legend appears cut off on right edge of image
+    spec_compliance:
+      score: 23
+      max: 25
+      items:
+      - id: SC-01
+        name: Plot Type
+        score: 8
+        max: 8
+        passed: true
+        comment: Correct scatter plot with brush selection visualization
+      - id: SC-02
+        name: Data Mapping
+        score: 5
+        max: 5
+        passed: true
+        comment: X/Y correctly mapped to numeric axes
+      - id: SC-03
+        name: Required Features
+        score: 4
+        max: 5
+        passed: true
+        comment: Brush rectangle, selected points highlighted, selection count shown;
+          static image cannot show interactivity
+      - id: SC-04
+        name: Data Range
+        score: 3
+        max: 3
+        passed: true
+        comment: All data points visible within axes range
+      - id: SC-05
+        name: Legend Accuracy
+        score: 2
+        max: 2
+        passed: true
+        comment: Legend correctly identifies all four clusters
+      - id: SC-06
+        name: Title Format
+        score: 1
+        max: 2
+        passed: true
+        comment: Correct format but uses middle dot separator
+    data_quality:
+      score: 19
+      max: 20
+      items:
+      - id: DQ-01
+        name: Feature Coverage
+        score: 8
+        max: 8
+        passed: true
+        comment: Shows 4 distinct clusters with varying sizes, demonstrates selection
+          across multiple clusters
+      - id: DQ-02
+        name: Realistic Context
+        score: 6
+        max: 7
+        passed: true
+        comment: Generic clustered data scenario plausible for exploratory analysis
+      - id: DQ-03
+        name: Appropriate Scale
+        score: 5
+        max: 5
+        passed: true
+        comment: Values in reasonable numeric range (0-100)
+    code_quality:
+      score: 9
+      max: 10
+      items:
+      - id: CQ-01
+        name: KISS Structure
+        score: 3
+        max: 3
+        passed: true
+        comment: 'Clean script structure: imports, data generation, plot creation,
+          save'
+      - id: CQ-02
+        name: Reproducibility
+        score: 3
+        max: 3
+        passed: true
+        comment: Uses np.random.seed(42)
+      - id: CQ-03
+        name: Clean Imports
+        score: 2
+        max: 2
+        passed: true
+        comment: All imports are used
+      - id: CQ-04
+        name: No Deprecated API
+        score: 1
+        max: 1
+        passed: true
+        comment: Uses current lets_plot API
+      - id: CQ-05
+        name: Output Correct
+        score: 0
+        max: 1
+        passed: false
+        comment: Saves both plot.png and plot.html
+    library_features:
+      score: 4
+      max: 5
+      items:
+      - id: LF-01
+        name: Distinctive Features
+        score: 4
+        max: 5
+        passed: true
+        comment: Good use of layer_tooltips, geom_rect, scale_alpha_identity, HTML
+          export with zoom/pan toolbar
+  verdict: APPROVED
+impl_tags:
+  dependencies: []
+  techniques:
+  - annotations
+  - hover-tooltips
+  - html-export
+  - layer-composition
+  patterns:
+  - data-generation
+  - iteration-over-groups
+  dataprep: []
+  styling:
+  - alpha-blending
+  - grid-styling