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Teradata

Teradata MCP Server

Official
by Teradata

qlty_missingValues

Identify columns with missing values in a Teradata table. Specify database and table name; optionally persist results as a volatile table.

Instructions

Get the column names that have missing values in a table.

Arguments: database_name - Name of the database (optional, omit if table_name is fully qualified) table_name - Table 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
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)
Behavior3/5

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

No annotations are present, so the description carries full burden. It mentions the effect of the 'persist' parameter (materializes result as volatile table), which discloses a side effect. However, it does not mention whether the tool is read-only or any other behavioral traits like performance or permissions.

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 structurally sound with a headline and bullet list, but the bullet list duplicates the schema information. It could be more concise by omitting the redundant parameter descriptions. The headline is front-loaded.

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?

Given the presence of sibling quality tools and no output schema, the description lacks completeness. It does not explain what 'missing values' means (e.g., nulls or specific values), nor does it describe the return format (e.g., list of column names). The parameter documentation is complete, but overall context is lacking.

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%, with all parameters already described in the input schema. The description's argument list is essentially a verbatim copy of the schema, adding no new meaning or context beyond what the schema provides.

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 the tool returns column names with missing values in a table, using a specific verb ('Get') and resource ('column names that have missing values'). It distinguishes from sibling tools like qlty_rowsWithMissingValues, which returns rows instead.

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 is provided on when to use this tool versus alternatives (e.g., qlty_rowsWithMissingValues). The description includes parameter details but no context about trade-offs or typical use cases.

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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