Skip to main content
Glama
AKzar1el

TrendPulse - Google News & Trends

by AKzar1el
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_related_queries

Read-only

Discover top and rising search queries related to a seed keyword to expand keyword targeting and optimize content strategy.

Instructions

Return top and rising literal search queries related to one seed keyword. Use this for query expansion; use get_related_topics for topic entities or get_suggestions for autocomplete candidates.

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
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds meaningful behavioral context: it specifies that the output consists of 'literal' search queries and distinguishes 'top and rising' from other query types, which helps the agent understand what kind of data to expect. It does not mention pagination or result limits, but that is a minor gap given the annotations.

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 sentences with zero redundancy. The first sentence front-loads the purpose and output type, and the second immediately gives usage guidance and alternatives. Every word contributes value.

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?

The tool has a simple signature (5 params, 1 required) and an output schema exists (indicated by has output schema: true), so the description does not need to explain return values. Annotations cover safety and openness. The description provides sufficient context for an agent to call it correctly without additional information.

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 every parameter is already documented in the input schema. The description adds no extra meaning about parameters—only the term 'seed keyword' which maps to the 'keyword' property but provides no additional format or constraint details. Baseline 3 is appropriate.

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 verb 'return' and the resource 'top and rising literal search queries related to one seed keyword'. It also explicitly names sibling tools (get_related_topics, get_suggestions) and differentiates its purpose from them, so an agent can select it without ambiguity.

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?

It explicitly states when to use this tool ('for query expansion') and provides clear alternatives with conditions ('use get_related_topics for topic entities or get_suggestions for autocomplete candidates'). This is direct, unambiguous routing guidance.

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

Deploy Server

Other Tools