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get_trending_terms

Retrieve Google Trends data for a specified geographic location, from worldwide to country, state, or US metro area.

Instructions

Returns google trends for a specific geo location.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geoNoGeographic target for trending terms. Supports four levels of granularity: - Worldwide: empty string '' - Country: ISO 3166-1 alpha-2 code, e.g. 'US', 'GB', 'CA' - Subdivision (state/province/region): ISO 3166-2 format 'CC-XX' or 'CC-XXX', e.g. 'US-CA' (California), 'BE-BRU' (Brussels) - US metro area: bare Nielsen DMA code (numeric string), e.g. '807' (San Francisco Bay Area), '501' (New York City)US
full_dataNoReturn full data for each trend including related news stories.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of disclosing behavior. It only says 'returns' data and gives no details about rate limits, whether the call is read-only, possible empty results, or how full_data affects behavior. This is a minimal disclosure that does not sufficiently cover behavioral traits.

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 a single concise, front-loaded sentence with no filler. It communicates the core operation immediately and earns its place.

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

Completeness3/5

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

The tool is simple, has only two optional and well-documented parameters, and an output schema exists, so return shape is covered. However, the description lacks sibling differentiation and behavioral caveats, leaving an agent with enough to invoke it but not enough to confidently choose it among many similar trend tools.

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 the baseline is 3; the schema already documents geo granularity and full_data. The description adds only the idea of a 'specific geo location', which aligns with the geo parameter but does not compensate for or add anything beyond the schema.

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?

The description states a clear verb and resource: it returns Google trends for a specific geo location. However, it does not distinguish this tool from similarly named siblings like get_trends, get_top_trends, or get_ranked_trends, so an agent cannot easily tell why get_trending_terms is the right choice.

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 phrase 'for a specific geo location' implies this tool is for geo-scoped trend retrieval, but no explicit guidance is given about when to use it over alternatives like get_trends or get_trending_by_region. There are no when-not-to-use conditions or sibling references.

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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