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Generate Scatter Chart

generate_scatter_chart
Read-only

Generate a scatter chart to show the relationship between two variables, helps discover their relationship or trends, such as, the strength of correlation, data distribution patterns.

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_scatter_chart"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataYesData for scatter chart, such as, [{ x: 10, y: 15 }], when the data is grouped, the group name can be specified in the `group` field, such as, [{ x: 10, y: 15, group: 'Group A' }].
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.
axisXTitleNoSet the x-axis title of chart.
axisYTitleNoSet the y-axis title of chart.
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

B3/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, and the description adds no further behavioral detail beyond the purpose statement. It does not say what is produced (rendered image, URL, chart object), whether the chart is persisted or versioned, or anything about limits, even though sibling tools like create_living_chart and list_chart_versions suggest a stateful chart system.

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

Conciseness3/5

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

It is a single short sentence, which is appropriately sized, but the phrasing is clumsy and repetitive ("relationship between two variables, helps discover their relationship") with an awkward "such as," list. The core purpose is front-loaded, but a rewrite would earn its space better.

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

Completeness2/5

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

For a tool with 9 parameters, nested object input, and no output schema, the description is thin: it never explains the return value or how the generated chart is delivered, and gives no guidance for choosing this among 30+ chart siblings. The schema covers the inputs well, but the output and selection story remain unaddressed.

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%, so every parameter, including the nested data/group and style fields, is already documented in the schema. The description adds no parameter-level meaning such as data volume limits, how x/y map to the two variables, or when brandTheme applies, so the baseline of 3 applies.

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

Purpose4/5

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

States a specific verb and resource ("Generate a scatter chart") and adds the analytical intent ("show the relationship between two variables"), which hints at how it differs from bar/line/pie siblings. It stops short of naming or contrasting any sibling explicitly, so differentiation is inferred rather than stated.

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

Usage Guidelines3/5

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

The mention of correlation strength and distribution patterns implies when this chart type is appropriate, which is useful given the large chart-generator family. However, there is no explicit when-not guidance, no named alternative for cases like time-series or categorical comparison, and no prerequisites.

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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