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Green-pep

meta-ads-mcp-patched

by Green-pep

search_targeting

Find valid Meta Ads targeting IDs by searching interests, behaviors, demographics, and more. Use keyword queries to discover targeting options for ad set specs.

Instructions

Search for targeting options (interests, behaviors, demographics, etc.) by keyword. Use this to find valid targeting IDs for ad set targeting specs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSearch query (e.g. 'fitness', 'technology', 'cooking')
typeNoTargeting type filter: adinterest, adgeolocation, adeducationschool, adeducationmajor, adworkemployer, adworkposition, adlocale, etc.
limitNoNumber of results (default 25)
Behavior3/5

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

With no annotations provided, the description carries the full burden. It conveys the core behavior—searches by keyword and returns targeting IDs—but does not disclose details about response format, pagination, error behavior, or how the 'type' filter affects results. This is adequate but leaves gaps expected 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 is two sentences long, front-loaded with the action and resource, and includes a practical note about finding valid IDs. Every sentence earns its place with no fluff or repetition.

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?

This is a simple search tool, and the description covers its main purpose and use case. It lacks mention of the response structure beyond 'valid targeting IDs,' but since no output schema exists, this is a minor gap. The description is mostly complete given the tool's simplicity and high schema coverage.

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?

The schema description coverage is 100%, with each parameter (q, type, limit) having its own description. The tool description adds little beyond the schema, only mentioning 'by keyword' which aligns with q. Since the schema already documents the parameters, the baseline of 3 is appropriate.

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 the tool's purpose: 'Search for targeting options (interests, behaviors, demographics, etc.) by keyword' and explicitly notes it is used to 'find valid targeting IDs for ad set targeting specs.' This verb+resource+outcome structure distinguishes it from siblings like search_targeting_map and search_locations which have different output or focus.

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 provides a clear use case: 'Use this to find valid targeting IDs for ad set targeting specs.' This implies when to use the tool, but it does not explicitly mention alternatives or when not to use it. There is no exclusions guidance, but the context is clear enough for an agent to select it for targeting ID lookup.

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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