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ChartAnt

by net.chartant
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Generate Word Cloud Chart

generate_word_cloud_chart
Read-only

Generate a word cloud chart to show word frequency or weight through text size variation, such as, analyzing common words in social media, reviews, or feedback.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "data": "<data>"
    },
    "name": "generate_word_cloud_chart"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataYesData for word cloud chart, it should be an array of objects, each object contains a `text` field and a `value` field, such as, [{ value: 4.272, text: '形成' }].
styleNoStyle configuration for the chart with a JSON object, optional.
themeNoSet the theme for the chart, optional, default is 'default'.default
titleNoSet the title of chart.
widthNoSet the width of chart, default is 600.
heightNoSet the height of chart, default is 400.
brandThemeNoName of a brand theme saved on the user's account (their colours and footer), only when the user asks for their theme. Or "colorblind" for colours that people with colour-vision deficiency can tell apart (anyone can use it).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, so safety is covered. The description adds useful semantic context about what the chart communicates, but it does not state what the tool returns (image, chart object, version ID), whether the chart is saved, or how brand themes affect the generated output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no redundant setup; the examples earn their place by clarifying use cases. The minor comma in 'such as,' does not obstruct readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 7-parameter chart generator with nested style options, the description gives purpose and usage but omits return behavior and whether the generated chart is persisted. The schema carries parameter detail and annotations cover read-only safety, but missing output expectations leave a gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the schema fully documents data, style, theme, title, width, height, and brandTheme. The description adds no parameter-specific guidance beyond the general text-size concept, so the baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Generate') and resource ('word cloud chart'), then explains the visual encoding (text size reflects frequency/weight) and gives use cases. The word-cloud chart type itself clearly differentiates it from the other generate_* chart siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear when-to-use context with concrete examples: social media, reviews, and feedback analysis. It does not explicitly name alternatives or state when not to use it, but the chart type is distinctive enough that the intended use is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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