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histogram_create

Generates a histogram from numeric values with configurable bins and ASCII visualization, enabling quick distribution analysis of datasets.

Instructions

Create a histogram from numeric data with configurable bins and ASCII visualization.

Input Schema

NameRequiredDescriptionDefault
binsNoNumber of bins (default 10).
valuesYesArray of numbers to histogram.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.11

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral burden. It mentions 'ASCII visualization,' which hints at output format, but doesn't clarify whether the tool is read-only, what permissions are needed, whether it modifies any state, or what the output looks like beyond ASCII. For a computation tool with no annotations, this is a significant gap.

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?

Single sentence, front-loaded with the core action and resource, and includes key features without any fluff. Every word earns its place.

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?

With no annotations, no output schema, and only a brief description, the definition is incomplete for an agent to understand the tool's behavior. It doesn't explain what 'ASCII visualization' entails (e.g., text-based bars), whether the output is a string or structured data, or any constraints (e.g., maximum number of bins). This is inadequate for a tool that produces a visual representation.

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 both parameters ('bins' and 'values') are already documented in the schema. The description repeats 'configurable bins' and 'numeric data' without adding new semantic information. Baseline 3 is appropriate when the schema fully covers parameters.

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?

Specific verb+resource: 'Create a histogram from numeric data' clearly states what the tool does. The mention of 'configurable bins and ASCII visualization' further distinguishes it from other numeric/data tools. No sibling tool has a similar purpose, so it stands out unambiguously.

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?

No explicit guidance on when to use this tool versus alternatives. Usage is implied: it's for generating histograms from numeric arrays. In the context of hundreds of siblings, there is no indication of when a histogram is appropriate (e.g., exploratory data analysis) or what alternatives exist (e.g., descriptive_stats). This is minimum viable.

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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