smithery.ai

chart-visualization

This skill should be used when the user wants to visualize data. It intelligently selects the most suitable chart type from 26 available options, extracts parameters based on detailed specifications, and generates a chart image using a Python script.

First seen Mar 21, 2026

Installation

$ npx skills add https://smithery.ai

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,078 B
  • docs SUMMARY.md 277 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 2 installs

SKILL.md

Chart Visualization Skill

This skill provides a comprehensive workflow for transforming data into visual charts. It handles chart selection, parameter extraction, and image generation.

Workflow

To visualize data, follow these steps:

1. Intelligent Chart Selection

Analyze the user's data features to determine the most appropriate chart type. Use the following guidelines (and consult references/ for detailed specs):

  • Time Series: Use generatelinechart (trends) or generateareachart (accumulated trends). Use generatedualaxes_chart for two different scales.
  • Comparisons: Use generatebarchart (categorical) or generatecolumnchart. Use generatehistogramchart for frequency distributions.
  • Part-to-Whole: Use generatepiechart or generatetreemapchart (hierarchical).
  • Relationships & Flow: Use generatescatterchart (correlation), generatesankeychart (flow), or generatevennchart (overlap).
  • Maps: Use generatedistrictmap (regions), generatepinmap (points), or generatepathmap (routes).
  • Hierarchies & Trees: Use generateorganizationchart or generatemindmap.
  • Specialized:

- generateradarchart: Multi-dimensional comparison. - generatefunnelchart: Process stages. - generateliquidchart: Percentage/Progress. - generatewordcloudchart: Text frequency. - generateboxplotchart or generateviolinchart: Statistical distribution. - generatenetworkgraph: Complex node-edge relationships. - generatefishbonediagram: Cause-effect analysis. - generateflowdiagram: Process flow. - generatespreadsheet: Tabular data or pivot tables for structured data display and cross-tabulation.

2. Parameter Extraction

Once a chart type is selected, read the corresponding file in the references/ directory (e.g., references/generatelinechart.md) to identify the required and optional fields. Extract the data from the user's input and map it to the expected args format.

3. Chart Generation

Invoke the scripts/generate.py script with a JSON payload.

Payload Format:

{
  "tool": "generate_chart_type_name",
  "args": {
    "data": [...],
    "title": "...",
    "theme": "...",
    "style": { ... }
  }
}

Execution Command:

python ./scripts/generate.py '<payload_json>'

4. Result Return

The script will output the URL of the generated chart image. Return the following to the user:

  • The image URL.
  • The complete args (specification) used for generation.

Reference Material

Detailed specifications for each chart type are located in the references/ directory. Consult these files to ensure the args passed to the script match the expected schema.