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Teradata MCP Server

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by Teradata

plot_pie_chart

Generate a pie chart from a Teradata table by specifying labels and a numeric column to display proportional distribution.

Instructions

Function to generate a pie chart plot for labels and columns. Columns mentioned in labels are used as labels and column is used to plot.

PARAMETERS: table_name: Required Argument. Specifies the name of the table to generate the donut plot. Types: str

labels:
    Required Argument.
    Specifies the labels to be used for the line plot.
    Types: str

column:
    Required Argument.
    Specifies the column to be used for generating the line plot.
    Types: str

RETURNS: dict

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_nameYes Required Argument. Specifies the name of the table to generate the donut plot. Types: str
labelsYes Required Argument. Specifies the labels to be used for the line plot. Types: str
columnYes Required Argument. Specifies the column to be used for generating the line plot. Types: str
Behavior2/5

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

No annotations are provided, so the description must disclose behaviors. It does not explain side effects (e.g., file creation), required permissions, data validity requirements, or the output structure beyond 'dict'. The description is vague about what the tool actually does.

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

Conciseness3/5

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

The description is somewhat verbose with repeated 'Required Argument.' and redundant parameter listings that mirror the schema. It could be more concise, but it is structured with clear sections. It is acceptable but not efficient.

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

Completeness1/5

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

Without an output schema, the description should explain the return value (e.g., format, location). It only says 'dict' without details. The conflicting terms (pie chart vs donut plot vs line plot) indicate incomplete or careless documentation, making it insufficient for a plotting tool.

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

Parameters1/5

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

While schema coverage is 100%, the parameter descriptions contain inconsistencies and errors. The schema for 'table_name' mentions 'donut plot' instead of 'pie chart', and 'labels' and 'column' refer to 'line plot' instead of 'pie chart'. This confusion undermines the meaning and could mislead the agent.

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 it generates a pie chart and distinguishes it from sibling chart types like line, polar, and radar. However, the phrase 'Columns mentioned in labels are used as labels and column is used to plot' is somewhat ambiguous and could be clearer.

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?

No guidance on when to use this tool versus alternatives (e.g., line chart, polar chart). No prerequisites or exclusions are mentioned, leaving the agent without decision-making context.

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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