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ChartAnt

by net.chartant
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Generate Histogram Chart

generate_histogram_chart
Read-onlyIdempotent

Draw a histogram of how raw numbers are distributed (response times, ages, order sizes). Data is a flat list of numbers; binNumber sets how many bins. To compare categories use generate_column_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_histogram_chart"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataYesData for histogram chart, it should be an array of numbers, such as, [78, 88, 60, 100, 95].
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.
binNumberNoNumber of intervals to define the number of intervals in a histogram, when not specified, a built-in value will be used.
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

A4.5/5.0
Behavior4/5

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

Annotations already establish this as a safe, idempotent, non-destructive read-only generation call. The description adds genuinely new behavioral information by disclosing the output artifacts: a hosted PNG link, a share page, alt text, and editable PowerPoint/Excel links — important for planning follow-up steps. It does not cover latency, chart-version side effects, or limits, which keeps it below a 5.

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 sentences, zero filler, with the core purpose and data-shape constraint front-loaded and the alternative-plus-return-format details trailing. Every clause carries selectable or invocable information.

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?

With 10 parameters, one required, and no output schema, the description covers the critical points — input shape, bin control, alternative tool, and return artifacts — which is enough to call it correctly. Optional styling parameters (palette, texture, theme, brandTheme, dimensions) are left entirely to the schema, which is reasonable given their full descriptions.

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

Parameters5/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: it clarifies that 'data' is a flat list of numbers (not grouped/series data) and restates binNumber as 'sets how many bins', repairing the schema's circular wording ('Number of intervals to define the number of intervals'). That is substantive clarification rather than repetition.

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?

The description opens with a specific verb and chart type ('Draw a histogram') and immediately defines the input shape ('how raw numbers are distributed') with concrete examples (response times, ages, order sizes). It explicitly distinguishes itself from the category-comparison sibling generate_column_chart, so an agent can select it without opening the 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?

It gives explicit routing guidance: 'To compare categories use generate_column_chart,' which is a real use-vs-alternative rule. It also constrains the input to a flat list of raw numbers, implicitly ruling out pre-aggregated/categorical data. It does not mention other distribution-oriented siblings (boxplot, violin) or when a histogram is a poor fit, so it falls just short of full when/when-not coverage.

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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