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AKzar1el

TrendPulse - Google News & Trends

by AKzar1el
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_related_topics

Read-only

Discover top and rising Google Trends topic entities related to a seed keyword to expand your topic research and identify emerging interests.

Instructions

Return top and rising Google Trends topic entities related to one seed keyword. Use this for entity or topic expansion; use get_related_queries for literal search queries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
catNoCategory ID (default: 0 for all).
geoNoGeographic region code (e.g. 'US').US
gpropNoGoogle property filter.
keywordYesSearch keyword to analyze.
timeframeNoTimeframe for search volume analysis (e.g., 'today 12-m').today 12-m

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.2.30
    • addedInput schema / properties / keyword / minLength
      Added value: +1
    • addedInput schema / properties / keyword / pattern
      Added value: +".*\\S.*"
  2. Changed2 schema fields changedv0.2.22
    • changedInput schema / properties / gprop / description
      Previous value: -"Google property filter (e.g., '', 'youtube', 'news', 'images', 'froogle')."New value: +"Google property filter."
    • addedInput schema / properties / gprop / enum
      Added value: +[
+  "",
+  "youtube",
+  "news",
+  "images",
+  "froogle"
+]
  3. First observed

TDQS

A4.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds useful context about the result nature ('top and rising' topic entities), but it does not disclose other behavioral traits such as whether results are limited, exhaustive, or paginated. With annotations covering safety, this is adequate but not exceptional.

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?

Two efficient sentences with no filler. The core purpose is front-loaded, and the alternative-tool routing is placed in the second sentence. Every word contributes to selection or invocation.

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

Completeness5/5

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

Given the annotations cover safety, the schema fully documents all parameters, and an output schema exists, the description is complete for an agent to call this tool correctly. It also provides the necessary sibling differentiation without requiring the agent to inspect other tool definitions.

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 the schema documents all five parameters. The description adds meaningful value by clarifying that the tool accepts 'one seed keyword', a constraint not explicitly stated in the schema's parameter descriptions. This helps agents avoid passing multiple keywords or a query-style string.

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 uses a specific verb ('Return') and a precise resource ('Google Trends topic entities' related to a seed keyword), and it explicitly distinguishes itself from get_related_queries. An agent can immediately understand what this tool does and how it differs from the closest sibling.

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

Usage Guidelines5/5

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

The description provides an explicit usage directive: use this tool for entity or topic expansion and use get_related_queries for literal search queries. This directly guides tool selection against the most relevant alternative, leaving no ambiguity.

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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