spss-studio-mcp

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Spss Chart Bar

spss_chart_bar

Create a publication-ready bar chart comparing a categorical variable with the mean or sum of a continuous variable, then export it as PNG or TIFF for reports.

Instructions

Export a publication-ready bar chart (PNG/TIFF) of a categorical variable against the mean (or sum) of a continuous variable, via GGRAPH + OMS IMAGE.

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": {
      "category": "<category>",
      "value": "<value>"
    },
    "name": "spss_chart_bar"
  }
}

Input Schema

Name	Required	Default
`dpi`	No
`stat`	No	mean
`title`	No
`value`	Yes
`x_label`	No
`y_label`	No
`category`	Yes
`width_px`	No
`data_file`	No
`height_px`	No
`image_format`	No	PNG

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 12, 2026

TDQS

C2.7/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the output medium (PNG/TIFF image file) and the engine (GGRAPH + OMS IMAGE), but says nothing about where the output is written, whether data must be pre-loaded, permissions, or overwrite behavior, and none of the 11 sizing/formatting parameters are characterized.

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?

A single well-formed sentence with the outcome front-loaded ('Export a publication-ready bar chart'), followed by the variable mapping and output formats. Nothing is padded, though the implementation aside ('GGRAPH + OMS IMAGE') is of marginal value to an agent.

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 an 11-parameter tool with zero schema documentation and no annotations, the description is thin. The output schema covers return values, but nothing tells the agent which dataset is charted (data_file semantics), how sizing works, or why one would pick this chart over its siblings.

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

Parameters2/5

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

Schema description coverage is 0% across 11 parameters, so the description must compensate and largely does not. It clarifies the 'stat' semantics (mean or sum) and the image formats (PNG/TIFF) plus the category/value roles, but leaves dpi, width_px, height_px, title, x_label, y_label, and data_file entirely unexplained.

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 states a specific verb ('Export') and resource ('bar chart') with a clear analytical scope: a categorical variable against the mean or sum of a continuous variable. It implicitly distinguishes itself from other chart siblings (histogram, scatter, bar_error) by naming the categorical-vs-continuous mapping, though it never names an alternative explicitly.

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?

There is no guidance on when to choose this tool over spss_chart_bar_error, spss_chart_histogram, or spss_chart_area, and no prerequisites (e.g. data must already be loaded). The agent must infer selection from the chart type alone.

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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