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generate_histogram_chart

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Create histogram charts to visualize data distribution patterns, identify frequency concentrations, and detect outliers within numerical datasets.

Instructions

Generate a histogram chart to show the frequency of data points within a certain range. It can observe data distribution, such as, normal and skewed distributions, and identify data concentration areas and extreme points.

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

Name	Required	Description	Default
`data`	Yes	Data for histogram chart, it should be an array of numbers, such as, [78, 88, 60, 100, 95].
`binNumber`	No	Number of intervals to define the number of intervals in a histogram, when not specified, a built-in value will be used.
`style`	No	Style configuration for the chart with a JSON object, optional.
`theme`	No	Set the theme for the chart, optional, default is 'default'.	default
`width`	No	Set the width of chart, default is 600.
`height`	No	Set the height of chart, default is 400.
`title`	No	Set the title of chart.
`axisXTitle`	No	Set the x-axis title of chart.
`axisYTitle`	No	Set the y-axis title of chart.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv1.0.0Jan 3, 2026

changedInput schema / properties / style / description

Previous value: -"Custom style configuration for the chart."New value: +"Style configuration for the chart with a JSON object, optional."

First observedAug 15, 2025

TDQS

B3.2/5.0

Behavior3/5

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

Annotations provide readOnlyHint=true, indicating this is a safe read operation that doesn't modify data. The description adds some behavioral context by mentioning what the chart can 'observe' (e.g., normal/skewed distributions) and 'identify' (concentration areas, extreme points), which helps the agent understand the analytical value. However, it doesn't disclose other behavioral traits like whether it generates an image file, returns a URL, or has any rate limits or authentication needs beyond what annotations cover.

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

Conciseness4/5

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

The description is appropriately concise at two sentences, with the first sentence stating the core purpose and the second elaborating on analytical benefits. There's no wasted text or redundancy. However, it could be slightly more front-loaded by immediately distinguishing from siblings, which would improve structure further.

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?

Given the tool's moderate complexity (9 parameters, nested objects) and rich schema coverage (100%), the description is adequate but has gaps. It explains the purpose and analytical value but doesn't cover output format (no output schema exists), performance considerations, or sibling differentiation. With annotations covering safety, the description provides basic context but could be more complete for a chart generation tool.

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 the schema already documents all 9 parameters thoroughly with descriptions, defaults, and enums. The description adds no parameter-specific information beyond what's in the schema. According to the rules, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the description, which applies here.

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?

The description clearly states the tool's purpose: 'Generate a histogram chart to show the frequency of data points within a certain range.' It specifies the verb ('generate') and resource ('histogram chart'), and mentions what the chart visualizes (frequency distribution). However, it doesn't explicitly differentiate from sibling tools like 'generate_bar_chart' or 'generate_column_chart' that might also show frequency distributions, which prevents a perfect score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It mentions that histograms can 'observe data distribution' and 'identify data concentration areas and extreme points,' but doesn't specify when a histogram is preferable over other chart types like box plots or violin charts for similar purposes. There are no explicit when/when-not statements or named alternatives.

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