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pralayasimha23

meta-ads-mcp

search_geo_locations

Search for geographic targeting locations by query. Retrieve matching countries, regions, cities, zip codes, geo markets, or electoral districts with hierarchy information for ad targeting.

Instructions

Search for geographic targeting locations.

Args:
    query: Search term for locations (e.g., "New York", "California", "Japan")
    access_token: Meta API access token (optional - will use cached token if not provided)
    location_types: Types of locations to search. Options: ['country', 'region', 'city', 'zip', 
                   'geo_market', 'electoral_district']. If not specified, searches all types.
    limit: Maximum number of results to return (default: 25)

Returns:
    JSON string containing location data with key, name, type, and geographic hierarchy information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
access_tokenNo
location_typesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses access_token caching behavior, returns a JSON string with location data, and implies a read-only search operation. While it doesn't mention rate limits or pagination, it provides solid transparency for a search tool.

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 uses a clean, structured Args/Returns format. Every line earns its place, listing parameters and return value without any filler or redundancy.

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

Completeness5/5

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

The description covers the tool's purpose, all parameters, token handling, and return structure. Given the tool's simple search nature and no annotations, this is complete enough for an agent to select and invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, but the description fully compensates by explaining each parameter: query, access_token, location_types (including available options), and limit with default. This adds complete semantic meaning beyond the bare schema types.

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 clearly states 'Search for geographic targeting locations' with a specific verb and resource. This distinguishes it from sibling search tools like search_interests and search_behaviors, making the tool's scope 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?

The description clearly indicates this is for geographical targeting locations, which gives clear context for when to use it. However, it does not explicitly mention alternatives or exclusion criteria, only implying the use case through the resource type.

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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