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teradata-gcfr-mcp-server

by Pibbers

gcfr_data_trend_loads

Track daily load volume trends to spot unusual changes in total rows loaded per business date.

Instructions

Show daily load volume trends — total rows loaded per business date.

Use this to spot unusual volume changes. date_from and date_to default to yesterday and today respectively.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
date_toNo
date_fromNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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 default parameter behavior for date_from and date_to, and the verb 'Show' implies a read-only operation, but it does not specify date format, inclusivity, timezone handling, or how invalid inputs behave.

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

Conciseness5/5

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

The description is three tight sentences with no fluff: the first defines what it does, the second gives the use case, and the third explains parameter defaults. Every sentence earns its place.

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

Completeness4/5

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

For a read-only trend tool with two optional parameters and an output schema, the description covers the core behavior and default range. It could be more complete by explicitly distinguishing it from sibling tools like gcfr_data_trend_transforms or gcfr_load_stats, but it is otherwise sufficient.

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 0%, so the description must compensate for parameter meaning. It adds the default values for date_from and date_to, but it does not clarify expected date formats or whether the range is inclusive, leaving some interpretation to 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 a specific verb and resource: 'Show daily load volume trends — total rows loaded per business date.' It is clear this tool aggregates load volumes by business date and can be distinguished from the sibling transform trend tool by the word 'loads,' though it does not explicitly name alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a clear use case: 'Use this to spot unusual volume changes.' It does not explicitly state when not to use this tool or name an alternative, but the stated purpose is concrete enough to guide selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.