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Green-pep

meta-ads-mcp-patched

by Green-pep

search_locations

Search for countries, regions, cities, and zip codes to target in Meta Ads. Filter by location type and query to get matching geographic areas.

Instructions

Search for geographic locations (countries, regions, cities, zip codes) for ad targeting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSearch query (e.g. 'New York', 'California', 'United States')
limitNoNumber of results (default 25)
location_typesNoComma-separated location types: country, region, city, zip, geo_market, electoral_district
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Search' without indicating read-only nature, error handling, response format, or any side effects. This minimal disclosure is insufficient for the agent to understand the tool's behavior beyond the obvious.

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, front-loaded sentence that directly states the tool's purpose. It contains zero wasted words and is appropriately sized for a simple search tool.

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?

The tool has no output schema and no annotations, so the description needs to compensate by explaining return values or potential limitations. It does not mention what the search results look like, how many results are returned (beyond the schema's default), or any restrictions on query format. This leaves the agent without critical operational context.

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 schema already provides detailed descriptions for all three parameters. The overall description adds only the purpose ('for ad targeting') but does not add any new meaning to the parameters themselves, matching the baseline of 3.

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 clearly states the action ('Search') and the resource ('geographic locations') with specific examples (countries, regions, cities, zip codes). It conveys a specific purpose ('for ad targeting'), but it does not explicitly differentiate from sibling tools like search_targeting or search_targeting_map, so it falls 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 phrase 'for ad targeting' implies the context of use, giving some guidance on when this tool is relevant. However, there is no mention of alternatives or exclusions, such as 'use search_targeting for broader criteria', so it only provides implied usage context rather than explicit 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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