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Teradata MCP Server

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by Teradata

dba_flowControl

Retrieves Teradata flow control metrics for a date range. Optionally materializes the result as a volatile table for further use.

Instructions

Get the Teradata flow control metrics for a specified date range.

Arguments: start_date - The start date for the query range in YYYY-MM-DD format. end_date - The end date for the query range in YYYY-MM-DD format. persist - If True, materializes result as a volatile table and returns table name

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
start_dateYesThe start date for the query range in YYYY-MM-DD format.
end_dateYesThe end date for the query range in YYYY-MM-DD format.
persistNoIf True, materializes result as a volatile table and returns table name
Behavior2/5

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

With no annotations, the description bears full responsibility for behavioral disclosure. It reveals that persist=True materializes a volatile table and returns its name, but does not specify default return format, authorization needs, rate limits, or potential side effects like data volume.

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 structured with a header and bullet list, making it readable. However, it repeats parameter descriptions that exist identically in the schema, wasting space. It could be more concise by removing duplicates.

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 no output schema, the description covers one return scenario (persist=True) but omits the default return format (presumably direct metric results). It lacks explanation of what 'flow control metrics' entail and how they differ from sibling tools, leaving gaps for an AI agent.

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 each parameter is already fully documented. The description redundantly lists parameters with the same text, adding no new meaning. A baseline of 3 is appropriate as it provides a clean summary but no extra insight.

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 clearly states the tool retrieves 'Teradata flow control metrics' for a date range, using a specific verb 'Get'. However, among many dba_* siblings, it does not differentiate what makes flow control distinct from other metrics tools.

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 like dba_resusageSummary or dba_featureUsage. The description does not mention prerequisites, context of use, or exclusions.

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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