diff --git a/plots/band-basic/implementations/altair.py b/plots/band-basic/implementations/altair.py
index ddee174975..aa8eadd4d3 100644
--- a/plots/band-basic/implementations/altair.py
+++ b/plots/band-basic/implementations/altair.py
@@ -1,7 +1,7 @@
 """ pyplots.ai
 band-basic: Basic Band Plot
-Library: altair 6.0.0 | Python 3.13.11
-Quality: 92/100 | Created: 2025-12-23
+Library: altair 6.0.0 | Python 3.14
+Quality: 94/100 | Updated: 2026-02-23
 """
 
 import altair as alt
@@ -9,33 +9,106 @@
 import pandas as pd
 
 
-# Data - Time series with 95% confidence interval
+# Data - Oscilloscope voltage measurement with growing uncertainty
 np.random.seed(42)
 x = np.linspace(0, 10, 100)
 y_center = 2 * np.sin(x) + 0.5 * x  # Central trend (sinusoidal + linear growth)
 
-# Confidence band widens over time (realistic uncertainty growth)
+# Confidence band widens over time (realistic sensor drift uncertainty)
 uncertainty = 0.5 + 0.15 * x
 y_lower = y_center - 1.96 * uncertainty
 y_upper = y_center + 1.96 * uncertainty
+y_inner_lower = y_center - 0.674 * uncertainty  # 50% CI inner band
+y_inner_upper = y_center + 0.674 * uncertainty
 
-df = pd.DataFrame({"x": x, "y_center": y_center, "y_lower": y_lower, "y_upper": y_upper})
+df = pd.DataFrame(
+    {
+        "x": x,
+        "y_center": y_center,
+        "y_lower": y_lower,
+        "y_upper": y_upper,
+        "y_inner_lower": y_inner_lower,
+        "y_inner_upper": y_inner_upper,
+    }
+)
+
+# Annotation data — callout at x≈9.0 s where uncertainty is wide and clearly visible
+ann_row = df.iloc[90]  # x ≈ 9.09
+ann_df = pd.DataFrame(
+    {
+        "x": [ann_row["x"]],
+        "y_upper": [ann_row["y_upper"]],
+        "y_lower": [ann_row["y_lower"]],
+        "y_mid": [(ann_row["y_upper"] + ann_row["y_lower"]) / 2],
+        "label": [f"95% CI: ±{(ann_row['y_upper'] - ann_row['y_lower']) / 2:.1f} mV"],
+    }
+)
 
-# Band (area between y_lower and y_upper)
-band = (
+# Nearest-point selection for interactive HTML export
+nearest = alt.selection_point(nearest=True, on="pointerover", fields=["x"], empty=False)
+
+# 95% confidence band (outer) — teal-shifted blue for visual depth against inner band
+band_outer = (
     alt.Chart(df)
-    .mark_area(opacity=0.3, color="#306998")
-    .encode(x=alt.X("x:Q", title="Time (s)"), y=alt.Y("y_lower:Q", title="Signal Amplitude"), y2=alt.Y2("y_upper:Q"))
+    .mark_area(opacity=0.25, color="#4a8db7", interpolate="monotone")
+    .encode(
+        x=alt.X("x:Q", title="Time (s)"), y=alt.Y("y_lower:Q", title="Oscilloscope Signal (mV)"), y2=alt.Y2("y_upper:Q")
+    )
 )
 
-# Central trend line
-line = alt.Chart(df).mark_line(strokeWidth=4, color="#306998").encode(x="x:Q", y="y_center:Q")
+# 50% confidence band (inner) — deeper saturated blue for layered contrast
+band_inner = (
+    alt.Chart(df)
+    .mark_area(opacity=0.3, color="#306998", interpolate="monotone")
+    .encode(x="x:Q", y="y_inner_lower:Q", y2="y_inner_upper:Q")
+)
+
+# Central trend line (dark navy for strong focal contrast)
+line = alt.Chart(df).mark_line(strokeWidth=2.5, color="#1a3a5c", interpolate="monotone").encode(x="x:Q", y="y_center:Q")
+
+# Annotation: vertical bracket showing uncertainty span
+ann_rule = (
+    alt.Chart(ann_df)
+    .mark_rule(color="#c0392b", strokeWidth=1.5, strokeDash=[6, 3])
+    .encode(x="x:Q", y="y_lower:Q", y2="y_upper:Q")
+)
+
+ann_text = (
+    alt.Chart(ann_df)
+    .mark_text(align="left", dx=10, fontSize=16, fontWeight="bold", color="#c0392b")
+    .encode(x="x:Q", y="y_mid:Q", text="label:N")
+)
+
+# Interactive tooltip points (visible only on hover in HTML)
+tooltip_points = (
+    alt.Chart(df)
+    .mark_point(color="#1a3a5c", size=80)
+    .encode(
+        x="x:Q",
+        y="y_center:Q",
+        opacity=alt.condition(nearest, alt.value(1), alt.value(0)),
+        tooltip=[
+            alt.Tooltip("x:Q", title="Time (s)", format=".1f"),
+            alt.Tooltip("y_center:Q", title="Signal (mV)", format=".2f"),
+            alt.Tooltip("y_lower:Q", title="95% CI Lower", format=".2f"),
+            alt.Tooltip("y_upper:Q", title="95% CI Upper", format=".2f"),
+        ],
+    )
+    .add_params(nearest)
+)
+
+# Vertical guide rule (visible only on hover in HTML)
+guide_rule = (
+    alt.Chart(df)
+    .mark_rule(color="#999999", strokeDash=[4, 4])
+    .encode(x="x:Q", opacity=alt.condition(nearest, alt.value(0.5), alt.value(0)))
+)
 
-# Combine band and line
+# Combine layers
 chart = (
-    (band + line)
+    (band_outer + band_inner + line + ann_rule + ann_text + tooltip_points + guide_rule)
     .properties(width=1600, height=900, title=alt.Title("band-basic · altair · pyplots.ai", fontSize=28))
-    .configure_axis(labelFontSize=18, titleFontSize=22, gridOpacity=0.3)
+    .configure_axis(labelFontSize=18, titleFontSize=22, gridOpacity=0.15, gridColor="#cccccc")
     .configure_view(strokeWidth=0)
 )
 
diff --git a/plots/band-basic/metadata/altair.yaml b/plots/band-basic/metadata/altair.yaml
index 43cbe1b1fa..23207d8adb 100644
--- a/plots/band-basic/metadata/altair.yaml
+++ b/plots/band-basic/metadata/altair.yaml
@@ -1,166 +1,182 @@
 library: altair
 specification_id: band-basic
 created: '2025-12-23T09:10:02Z'
-updated: '2025-12-23T09:12:07Z'
-generated_by: claude-opus-4-5-20251101
+updated: '2026-02-23T14:27:15Z'
+generated_by: claude-opus-4-6
 workflow_run: 20456385370
 issue: 0
-python_version: 3.13.11
+python_version: '3.14'
 library_version: 6.0.0
 preview_url: https://storage.googleapis.com/pyplots-images/plots/band-basic/altair/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/band-basic/altair/plot_thumb.png
 preview_html: https://storage.googleapis.com/pyplots-images/plots/band-basic/altair/plot.html
-quality_score: 92
+quality_score: 94
 impl_tags:
   dependencies: []
   techniques:
-  - html-export
+  - annotations
   - layer-composition
+  - hover-tooltips
+  - html-export
   patterns:
   - data-generation
   dataprep: []
   styling:
   - alpha-blending
+  - grid-styling
 review:
   strengths:
-  - Excellent use of Altair declarative grammar with mark_area and y/y2 encoding for
-    the band
-  - Clean layered composition combining band and line charts
-  - Realistic uncertainty growth pattern (band widens over time) demonstrates practical
-    use case
-  - Proper 95% confidence interval calculation using 1.96 * uncertainty
-  - Good visual hierarchy with semi-transparent band (opacity=0.3) and prominent center
-    line (strokeWidth=4)
-  - Correct output format with both PNG and HTML for Altair
+  - Cohesive monochromatic blue palette with three intentional tones creates visual
+    depth and professional polish
+  - Dual confidence bands (50% + 95% CI) exceed spec requirements and add analytical
+    value
+  - Growing uncertainty narrative is immediately apparent and reinforced by the red
+    annotation callout
+  - Interactive features (tooltips, hover guide) work in HTML export without polluting
+    static PNG output
+  - All text sizes explicitly set with appropriate hierarchy (28/22/18/16pt)
   weaknesses:
-  - Y-axis label Signal Amplitude lacks units (should include units like mV)
-  - No legend or annotation explaining what the band represents (e.g. 95% CI)
-  image_description: The plot displays a band plot with a light blue semi-transparent
-    confidence band between two boundary lines, with a solid dark blue central trend
-    line running through the middle. The band shows a sinusoidal pattern with linear
-    upward growth, with amplitude ranging from approximately -3 to 10 on the y-axis.
-    The x-axis shows "Time (s)" from 0.0 to 10.0, and the y-axis shows "Signal Amplitude".
-    The confidence band appropriately widens over time (from ~1.0 at t=0 to ~3.5 at
-    t=10), demonstrating realistic uncertainty growth. The title "band-basic · altair
-    · pyplots.ai" is displayed at the top. The plot has a clean white background with
-    subtle gray gridlines.
+  - Axis line/tick styling remains at Altair defaults rather than being refined (DE-02)
+  - Interactive features (selection, tooltips) are invisible in the static PNG — only
+    benefit the HTML export (LM-02)
+  image_description: 'The plot displays a band chart with an oscilloscope signal theme
+    over a 0-10 second time range. A dark navy center line traces a sinusoidal wave
+    with upward linear drift (approximately 2*sin(x) + 0.5x), ranging from about -2.5
+    mV to 6 mV. Two semi-transparent blue confidence bands surround it: a lighter
+    outer band (95% CI, teal-blue at 0.25 opacity) and a darker inner band (50% CI,
+    deeper blue at 0.3 opacity). Both bands visibly widen from left to right, illustrating
+    growing uncertainty over time. At x approximately 9.1 seconds, a red dashed vertical
+    rule spans the full 95% CI width, with bold red annotation text "95% CI: +/-3.7
+    mV" offset to the right. The title reads "band-basic - altair - pyplots.ai" in
+    large font at the top. Axes are labeled "Time (s)" (x-axis) and "Oscilloscope
+    Signal (mV)" (y-axis). Grid lines are very subtle with light gray color. The view
+    border is removed. The layout fills the 4800x2700 canvas well with balanced margins.'
   criteria_checklist:
     visual_quality:
-      score: 37
-      max: 40
+      score: 30
+      max: 30
       items:
       - id: VQ-01
         name: Text Legibility
-        score: 10
-        max: 10
+        score: 8
+        max: 8
         passed: true
-        comment: Title at 28pt, axis labels at 22pt, tick labels at 18pt - all perfectly
-          readable
+        comment: 'All font sizes explicitly set: title 28pt, axis titles 22pt, tick
+          labels 18pt, annotation 16pt bold. All perfectly readable.'
       - id: VQ-02
         name: No Overlap
-        score: 8
-        max: 8
+        score: 6
+        max: 6
         passed: true
-        comment: No overlapping text elements
+        comment: No overlapping text elements. Annotation positioned with dx=10 to
+          avoid collision.
       - id: VQ-03
         name: Element Visibility
-        score: 8
-        max: 8
+        score: 6
+        max: 6
         passed: true
-        comment: Band opacity (0.3) allows visibility, line width (4) makes central
-          trend clear
+        comment: Center line clearly visible against bands. Bands distinguishable
+          via different blue tones and opacity. Smooth monotone interpolation.
       - id: VQ-04
         name: Color Accessibility
-        score: 5
-        max: 5
+        score: 4
+        max: 4
         passed: true
-        comment: Single color scheme (#306998 blue) with good contrast
+        comment: Monochromatic blue scheme is colorblind-safe. Red accent for annotation
+          only, good contrast.
       - id: VQ-05
-        name: Layout Balance
-        score: 5
-        max: 5
+        name: Layout & Canvas
+        score: 4
+        max: 4
         passed: true
-        comment: Good proportions, 16:9 aspect ratio, no cut-off content
+        comment: 4800x2700 canvas well utilized with balanced margins.
       - id: VQ-06
-        name: Axis Labels
-        score: 1
+        name: Axis Labels & Title
+        score: 2
         max: 2
         passed: true
-        comment: Y-axis "Signal Amplitude" is descriptive but lacks units
-      - id: VQ-07
-        name: Grid & Legend
-        score: 0
-        max: 2
+        comment: Time (s) and Oscilloscope Signal (mV) both descriptive with units.
+    design_excellence:
+      score: 15
+      max: 20
+      items:
+      - id: DE-01
+        name: Aesthetic Sophistication
+        score: 6
+        max: 8
+        passed: true
+        comment: Cohesive monochromatic blue palette with three intentional tones
+          creating visual depth. Red accent for annotation provides strong contrast.
+          Clearly above defaults.
+      - id: DE-02
+        name: Visual Refinement
+        score: 4
+        max: 6
+        passed: true
+        comment: Subtle grid (0.15 opacity), view border removed. Axis line styling
+          remains at Altair defaults.
+      - id: DE-03
+        name: Data Storytelling
+        score: 5
+        max: 6
         passed: true
-        comment: Grid is subtle (alpha 0.3) but no legend explaining what the band
-          represents
+        comment: Widening band communicates growing uncertainty. Dual-band approach
+          adds depth. Red annotation creates focal point.
     spec_compliance:
-      score: 25
-      max: 25
+      score: 15
+      max: 15
       items:
       - id: SC-01
         name: Plot Type
-        score: 8
-        max: 8
-        passed: true
-        comment: Correct band/area plot with central trend line
-      - id: SC-02
-        name: Data Mapping
         score: 5
         max: 5
         passed: true
-        comment: x mapped to time, y_lower/y_upper define band, y_center defines trend
-          line
-      - id: SC-03
+        comment: Correct band plot with filled region between boundary lines.
+      - id: SC-02
         name: Required Features
-        score: 5
-        max: 5
+        score: 4
+        max: 4
         passed: true
-        comment: Has band with semi-transparent fill, central trend line in contrasting
-          style, smooth interpolation
-      - id: SC-04
-        name: Data Range
+        comment: Semi-transparent fill, contrasting center line, smooth interpolation.
+          Exceeds spec with inner 50% CI band.
+      - id: SC-03
+        name: Data Mapping
         score: 3
         max: 3
         passed: true
-        comment: All data points visible within axes
-      - id: SC-05
-        name: Legend Accuracy
-        score: 2
-        max: 2
-        passed: true
-        comment: N/A for single-color band plot (no legend needed for basic version)
-      - id: SC-06
-        name: Title Format
-        score: 2
-        max: 2
+        comment: X/Y correctly mapped, 100 data points within range, axes show full
+          data extent.
+      - id: SC-04
+        name: Title & Legend
+        score: 3
+        max: 3
         passed: true
-        comment: 'Correct format: "band-basic · altair · pyplots.ai"'
+        comment: Title matches required format. No legend needed for single-series
+          band plot.
     data_quality:
-      score: 18
-      max: 20
+      score: 15
+      max: 15
       items:
       - id: DQ-01
         name: Feature Coverage
-        score: 7
-        max: 8
+        score: 6
+        max: 6
         passed: true
-        comment: Shows widening uncertainty over time, sinusoidal pattern with linear
-          growth - demonstrates most band plot features but could show additional
-          scenarios
+        comment: Shows widening uncertainty, sinusoidal + linear trend, dual CI bands,
+          and annotated callout.
       - id: DQ-02
         name: Realistic Context
-        score: 7
-        max: 7
+        score: 5
+        max: 5
         passed: true
-        comment: Time series with 95% confidence interval - plausible scientific/engineering
-          scenario
+        comment: Oscilloscope voltage measurement with sensor drift uncertainty. Neutral
+          scientific context.
       - id: DQ-03
         name: Appropriate Scale
         score: 4
-        max: 5
+        max: 4
         passed: true
-        comment: Values are reasonable for signal amplitude but units are abstract
+        comment: Millivolt range and 0-10s timespan realistic for oscilloscope measurements.
     code_quality:
       score: 10
       max: 10
@@ -170,40 +186,50 @@ review:
         score: 3
         max: 3
         passed: true
-        comment: Clean imports → data → plot → save structure, no functions/classes
+        comment: 'Linear flow: imports, data, plot layers, combine, save. No functions
+          or classes.'
       - id: CQ-02
         name: Reproducibility
-        score: 3
-        max: 3
+        score: 2
+        max: 2
         passed: true
-        comment: np.random.seed(42) ensures reproducibility
+        comment: Deterministic data generation with np.linspace and np.sin.
       - id: CQ-03
         name: Clean Imports
         score: 2
         max: 2
         passed: true
-        comment: Only altair, numpy, pandas imported - all used
+        comment: All three imports (altair, numpy, pandas) are used.
       - id: CQ-04
-        name: No Deprecated API
-        score: 1
-        max: 1
+        name: Code Elegance
+        score: 2
+        max: 2
         passed: true
-        comment: Uses current Altair API
+        comment: Clean, well-structured. Interactive features are legitimate Altair
+          capabilities.
       - id: CQ-05
-        name: Output Correct
+        name: Output & API
         score: 1
         max: 1
         passed: true
-        comment: Saves as plot.png and plot.html
-    library_features:
-      score: 5
-      max: 5
+        comment: Saves plot.png with scale_factor=3.0. Uses current Altair 6.x API.
+    library_mastery:
+      score: 9
+      max: 10
       items:
-      - id: LF-01
-        name: Distinctive Features
+      - id: LM-01
+        name: Idiomatic Usage
         score: 5
         max: 5
         passed: true
-        comment: Excellent use of Altair's declarative approach with mark_area, y/y2
-          encoding for bands, layered composition (band + line), configure_* for styling
+        comment: 'Declarative grammar: mark_area, mark_line, mark_rule, mark_text,
+          mark_point. Proper encoding with type shorthand. Layer composition with
+          + operator.'
+      - id: LM-02
+        name: Distinctive Features
+        score: 4
+        max: 5
+        passed: true
+        comment: alt.selection_point with nearest, alt.condition for conditional encoding,
+          rich tooltips, HTML export. Core visualization uses standard marks.
   verdict: APPROVED