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Trending now

get_trending_now
Read-only

Lists the searches surging right now in a country, for questions about what is spiking without a term being named, and for news and real-time context.

The backend parameter selects the source: "rpc" returns around 50 entries with growth percentages and a relative volume index; "rss" returns 10 entries together with the news articles behind each one; "auto" tries rpc and falls back to rss.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return.
regionNoCountry code such as "US", "GB", "TH"; a sub-region such as "US-CA"; or a US metro code such as "807". Empty string means worldwide.
backendNoSource to use. "rpc" returns ~50 items with growth percentages; "rss" returns 10 with the news articles behind each trend; "auto" tries rpc then falls back to rss.

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and openWorldHint, and the description adds substantial behavioral detail: the backend parameter behavior with exact entry counts, output contents (growth percentages, relative volume index, news articles), and the fallback logic for 'auto'. This goes well beyond the structured 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, front-loaded with the core purpose and followed by a concise technical detail about the backend parameter. No unnecessary words; every sentence 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?

The description covers the core purpose, usage context, and backend variations, which is adequate for a simple list tool with no output schema. Minor gaps remain: it does not explain how 'limit' interacts with the fixed counts of rpc/rss, nor detail the exact output structure, but these are not critical for correct invocation.

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%, covering all three parameters. The description adds meaningful semantics for the 'backend' parameter by explaining the output differences between rpc, rss, and auto, which is not fully captured in the schema. The descriptions for limit and region are sufficient in the schema, so no additional compensation is needed.

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 action ('Lists the searches surging right now in a country') and scope, and explicitly distinguishes from term-based tools by noting it works 'without a term being named' and targets 'news and real-time context'. This clearly separates it from sibling tools like get_interest_over_time or get_related_queries.

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?

The description gives explicit when-to-use guidance: 'for questions about what is spiking without a term being named, and for news and real-time context.' It implies when not to use (when a specific term is already known) but does not name alternative tools or provide exclusions, so it falls just short of a 5.

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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TDQS

A4.3/5.0
Disambiguation4/5

Each tool targets a distinct Google Trends data type—regional, temporal, related queries, trending now, topic resolution—so agents can usually tell them apart. However, research_trend overlaps with three of the get_* tools by combining their outputs, so it could be selected instead of a specific tool if the agent wants just one slice. Search topics is clearly separate.

Naming Consistency4/5

Four tools consistently use the get_verb_noun pattern (get_interest_over_time, etc.), but research_trend and search_topics deviate with different verbs while still keeping snake_case verb_noun. The pattern is readable but not perfectly uniform.

Tool Count5/5

Six tools is an appropriate number for a Google Trends server, covering the main interest endpoints plus a convenience aggregator and a topic resolver. Not too many, not too few.

Completeness4/5

The server covers the core Google Trends features: time series, regional breakdown, related queries, trending now, and topic resolution. A notable gap is the absence of a related_topics endpoint (topics related to a keyword), which complements related queries. Overall, the surface is fairly complete for typical trend research tasks.