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List Gservice Trends

list_gservice_trends
Read-onlyIdempotent

[read] List Google Trends rows (related queries / topics per country, category and date). The country and category can be given by id or by seliee_country_uuid / seliee_category_uuid. keyword matches ranked related queries or topic titles; with_queries / with_entities keep only rows that have related queries / topics.

Input Schema

NameRequiredDescriptionDefault
hlNo
catNo
geoNo
dateNo
pageNo
gpropNo
keywordNo
per_pageNo
with_queriesNo
with_entitiesNo
seliee_country_idNo
seliee_category_idNo
seliee_country_uuidNo
seliee_category_uuidNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive and openWorld, so the safety profile is covered; the '[read]' prefix mostly repeats this. The description does add real behavioral value by explaining that with_queries/with_entities are row filters rather than field expansions. It says nothing about pagination behavior (page/per_page), result ordering, or volume, which matters for a listing tool.

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?

Three short sentences, front-loaded with the resource and scope, then the id-or-uuid disambiguation, then the filter behavior. No filler. A slightly denser treatment of the remaining parameters would have cost little and helped more.

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?

For a 14-parameter tool with no output schema and no parameter descriptions, the definition is thin: an agent calling it cannot know what hl, geo, date, gprop or cat accept, nor what a row actually contains. The description covers the country/category dual addressing and two booleans, but leaves the majority of the surface unexplained.

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 coverage is 0%, so the description carries the full burden, and it explains only a fraction of the 14 parameters: country/category via id or seliee_country_uuid/seliee_category_uuid, keyword matching, and the two boolean row filters. Core parameters like hl (language), geo, date format, gprop (Google property), cat, and page/per_page semantics are entirely undocumented anywhere.

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?

Opens with a specific verb+resource: 'List Google Trends rows (related queries / topics per country, category and date)'. The parenthetical enumerates the shape of the data, which is more informative than the bare title. It doesn't name a discriminating sibling (e.g. list_gservice_query, gservice_query_breakdown), so it stops short of a 5.

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

Usage Guidelines3/5

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

The description implies usage via filter semantics ('keyword matches ranked related queries or topic titles', 'with_queries / with_entities keep only rows...'), which hints at the exploratory use case. However, with siblings like list_gservice_query and get_gservice_query_options present, no explicit when-to-use/when-not guidance is offered.

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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