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Search Trends

search_trends
Read-only

Search Google Trends for a term and return the top and rising queries from the last 24 hours. Use this when the user asks about trending topics, what people are searching for, or wants to understand search interest in a topic.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
search_termYesThe term to search for (e.g. "ai agent", "remote work", "electric vehicles")
download_csvNoSet to True to download the CSV files from Google Trends and return download links. Use when the user asks for a CSV, file, download, or export.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description doesn't need to restate safety. It adds valuable context beyond annotations: the 24-hour time window and the specific output types (top and rising queries). It does not mention edge cases like empty results or rate limits, but for a read-only search tool this is adequate. No contradiction with 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?

The description is two sentences with zero waste. The core action and scope are front-loaded in the first sentence, and the usage guidance is in the second. Every word 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 tool with only 2 parameters, full schema coverage, a read-only annotation, and no output schema, the description provides the essential context: what it does, what it returns, and when to use it. It doesn't specify the exact return format (e.g., structure of top/rising queries), but given the simplicity, the agent can infer this from the tool name and description. This is complete enough for effective selection and invocation.

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%, meaning both parameters are fully documented in the schema. The description adds no additional parameter-level detail beyond what the schema provides, so a baseline of 3 is appropriate. The mention of 'top and rising queries' indirectly relates to the search term, but it's not a meaningful extension of schema semantics.

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 states a specific verb ('Search'), a specific resource ('Google Trends'), and the precise output ('top and rising queries from the last 24 hours'). This clearly distinguishes it from sibling search tools like google_news_search or search_social_posts, which target different data sources. The purpose is unambiguous.

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?

It explicitly states when to use the tool: when the user asks about trending topics, what people are searching for, or search interest in a topic. This provides clear context, though it does not name alternative tools or explicitly state when not to use it. Given its uniqueness (no sibling covers Google Trends), this is sufficient guidance.

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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