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get_targeting_suggestions

Generate related interests, behaviors, and demographics for Meta ad targeting from your existing criteria to broaden or refine audiences.

Instructions

Get targeting suggestions based on existing targeting criteria. Meta suggests related interests, behaviors, and demographics.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "targeting_list": "<targeting_list>"
    },
    "name": "get_targeting_suggestions"
  }
}

Input Schema

NameRequiredDescriptionDefault
account_idNoAd account ID to query (e.g. 'act_123' or '123'). Falls back to META_AD_ACCOUNT_ID env var if omitted.
targeting_listYesJSON string of current targeting criteria to get suggestions for

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.6.1
    • addedInput schema / properties / account_id
      Added value: +{
      +  "description": "Ad account ID to query (e.g. 'act_123' or '123'). Falls back to META_AD_ACCOUNT_ID env var if omitted.",
      +  "type": "string"
      +}
  2. First observedv1.2.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does add meaningful behavior by saying Meta suggests related interests, behaviors, and demographics from existing criteria. However, it does not disclose permission requirements, rate limits, result size, or return structure, so transparency is only adequate.

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?

Two sentences, front-loaded with the core action and followed by a brief explanation of what Meta returns. There is no redundant or filler language.

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?

For a simple two-parameter read tool with complete schema coverage, the description is adequate: it explains the conceptual output and the basis for suggestions. However, with no output schema and no annotations, it could say more about result shape and how this differs from sibling targeting-search 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 schema already documents both parameters, including account_id fallback behavior and targeting_list as a JSON string. The description reinforces that suggestions are based on existing targeting criteria but adds no further parameter-level detail.

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 gives a specific verb and resource: it gets targeting suggestions based on existing targeting criteria, and it clarifies the output categories as related interests, behaviors, and demographics. It is clear on its own, but it does not explicitly distinguish itself from sibling targeting tools such as search_targeting or search_targeting_map.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It implies usage when existing targeting criteria are available, but it does not state when to use this tool versus alternatives like search_targeting, search_targeting_map, or get_reach_estimate. There are no exclusions or prerequisites beyond the schema requirement for targeting_list.

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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