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Teradata MCP Server

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by Teradata

qlty_distinctCategories

Retrieve distinct values from a specified column in a Teradata table. Optionally materialize the result as a volatile table for further analysis.

Instructions

Get the distinct categories from a column in a table.

Arguments: database_name - Name of the database (optional, omit if table_name is fully qualified) table_name - Table name to analyze column_name - Column name to analyze persist - If True, materializes result as a volatile table and returns table name

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_nameYesTable name to analyze
column_nameYesColumn name to analyze
persistNoIf True, materializes result as a volatile table and returns table name
database_nameNoName of the database (optional, omit if table_name is fully qualified)
Behavior4/5

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

With no annotations, the description carries the full burden. It explains that database_name is optional if table_name is fully qualified, and describes the persist parameter's effect (materializes as volatile table and returns table name). However, it does not mention whether the tool is read-only or other potential side effects.

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 relatively concise with a clear list of arguments. Each sentence serves a purpose, though it could be slightly more streamlined.

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?

The tool has no output schema, and the description only partially explains the return value (when persist is True). For the normal case (persist=False), the return format is not specified. Additional details about error handling or limitations would improve completeness.

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

Parameters4/5

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

Schema description coverage is 100%, so baseline is 3. The description adds value by explaining the optionality of database_name and the behavior of persist, which goes beyond the schema definitions.

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 clearly states 'Get the distinct categories from a column in a table.' It specifies a specific verb ('Get') and resource ('distinct categories'), distinguishing it from sibling tools like qlty_columnSummary or qlty_missingValues.

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 only states the function's purpose without specifying context, prerequisites, or when not to use it.

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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