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ChartAnt

by net.chartant
OverviewDiscussionsAdmin

Generate Boxplot Chart

generate_boxplot_chart
Read-onlyIdempotent

Draw a box plot: median, quartiles and outliers of the values in each category, to compare distributions. Data [{category, value, group?}] with one row per observation. For the shape of the distribution use generate_violin_chart. Returns a hosted PNG link, a share page, alt text and editable PowerPoint/Excel links.

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_boxplot_chart"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataYesData for boxplot chart, such as, [{ category: '分类一', value: 10 }] or [{ category: '分类二', value: 20, group: '组别一' }].
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

A4/5.0
Behavior3/5

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

The annotations already disclose readOnlyHint, idempotentHint and destructiveHint, so safety is covered. The description adds genuinely useful behavior beyond them: the return artifacts (hosted PNG link, share page, alt text, editable PowerPoint/Excel links). It says nothing about authentication, rate limits, or whether generated charts are persisted — minor gaps for a hosted-artifact tool.

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?

Three tight sentences with no waste: what it draws, what shape the data must take, where to go for an alternative, and what comes back. The purpose and data contract are front-loaded before the routing advice.

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

Completeness4/5

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

For a 9-parameter tool with a nested style object and no output schema, the description covers both the input contract and the returned artifacts, which is what an agent needs to call it and report results. It leaves the large styling surface (palette, texture, theme, brandTheme) entirely to the schema, which is reasonable given full coverage.

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 coverage is 100%, so the parameters are already documented and the baseline is 3. The description adds one real semantic point the schema does not state: "one row per observation" (long format granularity) and the optional group field's role in splitting boxes. It does not touch style, theme, dimensions or brandTheme, leaving that to the schema.

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?

A specific verb ("Draw") plus resource ("box plot"), and it immediately names the statistical content shown (median, quartiles, outliers) and the goal (compare distributions). This is enough to distinguish it from the other generate_*_chart siblings without opening a schema.

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?

Explicitly routes an alternative use case to a named sibling: "For the shape of the distribution use generate_violin_chart." That gives clear when-to-use-vs-alternative guidance, though it offers no other exclusions (e.g. when a histogram or bar chart would be preferable for simple counts).

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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