Add single-line visual headers to 66 command files across 10 plugins: - clarity-assist (2 commands): 💬 - claude-config-maintainer (5 commands): ⚙️ - cmdb-assistant (11 commands): 🖥️ - code-sentinel (3 commands): 🔒 - contract-validator (5 commands): ✅ - data-platform (10 commands): 📊 - doc-guardian (5 commands): 📝 - git-flow (8 commands): 🔀 - pr-review (7 commands): 🔍 - viz-platform (10 commands): 🎨 Each command now displays a consistent header at execution start: ┌────────────────────────────────────────────────────────────────┐ │ [icon] PLUGIN-NAME · Command Description │ └────────────────────────────────────────────────────────────────┘ Addresses #275 (other plugin commands visual output) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
99 lines
2.6 KiB
Markdown
99 lines
2.6 KiB
Markdown
---
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description: Create a Plotly chart with theme integration
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---
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# Create Chart
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## Visual Output
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When executing this command, display the plugin header:
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```
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┌──────────────────────────────────────────────────────────────────┐
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│ 🎨 VIZ-PLATFORM · Chart Builder │
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└──────────────────────────────────────────────────────────────────┘
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```
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Then proceed with the chart creation.
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Create a Plotly chart with automatic theme token application.
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## Usage
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```
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/chart {type}
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```
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## Arguments
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- `type` (required): Chart type - one of: line, bar, scatter, pie, area, histogram, box, heatmap, sunburst, treemap
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## Examples
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```
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/chart line
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/chart bar
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/chart scatter
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/chart pie
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```
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## Tool Mapping
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This command uses the `chart_create` MCP tool:
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```python
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chart_create(
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chart_type="line",
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data_ref="df_sales", # Reference to loaded DataFrame
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x="date", # X-axis column
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y="revenue", # Y-axis column
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color=None, # Optional: column for color grouping
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title="Sales Over Time", # Optional: chart title
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theme=None # Optional: theme name to apply
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)
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```
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## Workflow
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1. **User invokes**: `/chart line`
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2. **Agent asks**: Which DataFrame to use? (list available with `list_data` from data-platform)
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3. **Agent asks**: Which columns for X and Y axes?
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4. **Agent asks**: Any grouping/color column?
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5. **Agent creates**: Chart with `chart_create` tool
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6. **Agent returns**: Plotly figure JSON ready for rendering
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## Chart Types
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| Type | Best For |
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|------|----------|
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| `line` | Time series, trends |
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| `bar` | Comparisons, categories |
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| `scatter` | Correlations, distributions |
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| `pie` | Part-to-whole relationships |
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| `area` | Cumulative trends |
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| `histogram` | Frequency distributions |
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| `box` | Statistical distributions |
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| `heatmap` | Matrix correlations |
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| `sunburst` | Hierarchical data |
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| `treemap` | Hierarchical proportions |
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## Theme Integration
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Charts automatically inherit colors from the active theme:
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- Primary color for main data
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- Color palette for multi-series
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- Font family and sizes
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- Background colors
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Override with explicit theme:
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```python
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chart_create(chart_type="bar", ..., theme="my-dark-theme")
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```
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## Output
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Returns Plotly figure JSON that can be:
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- Rendered in a Dash app
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- Saved as HTML/PNG
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- Embedded in a layout component
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