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maevelynz

G2 Product Analytics MCP

by maevelynz

compare_review_completion_by_dimension

Compare review completion rates across device, segment, country, or product category for a given period to identify performance gaps.

Instructions

Compare review completion rate across an approved dimension.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateYes
dimensionYes
start_dateYes
Behavior1/5

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

There are no annotations to disclose safety or side effects, and the description does not mention read-only behavior, data freshness, pagination, or any output details. It only restates the function without revealing behavioral characteristics, so the description fails to carry the transparency burden.

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 a single sentence with no wasted words, and it front-loads the action. However, it is terse to the point of under-specification, missing qualifiers that would make the sentence more informative.

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?

Given three required parameters, no annotations, and no output schema, the description is far too sparse. It does not explain the notion of 'completion rate', what 'approved' means, how date ranges are formatted, or what the comparison output looks like. This is inadequate for an agent to invoke the tool reliably.

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

Parameters2/5

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. It mentions 'dimension' but does not explain date formats, the meaning of 'approved', or how parameters interact. The parameter names are partially self-explanatory, but the description adds little beyond the schema's basic types and enum.

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 uses a specific verb 'Compare' with a clear object 'review completion rate' and scope 'across an approved dimension.' The schema's enum clarifies the dimension options. It is implicitly distinguished from the sibling 'compare_periods' by focusing on dimension rather than time, though this is not explicit.

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 such as compare_periods or diagnose_review_completion_change. The description does not state when it is appropriate or inappropriate to invoke, leaving the agent without decision support.

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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