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iammalego

mlg-meta-mcp

by iammalego

getInterestSuggestions

Generate targeted interest suggestions from a list of seed interests to expand audience targeting for Meta Ads campaigns.

Instructions

Get interest suggestions based on a list of seed interests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results. Default: 25
interestListYesList of interest names to use as seeds for suggestions

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral burden. 'Get' and 'suggestions' imply a read-only operation, and the seed-interest dependency is clear arranged. However, it does not mention authentication requirements, rate limits, failure modes, or output characteristics, so the disclosure is minimal but not contradictory.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler. It is efficient, though it sacrifices a small amount of helpful context that could have been added, such as naming the closest sibling tool.

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 tool with fully documented parameters, the description covers the core invocation. However, the lack of annotations and output schema means the return shape, success/failure behavior, and any additional constraints are unstated, leaving some reliance on the tool name and general inference.

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 description does not need to add parameter detail. It reinforces that interestList acts as 'seed' interests, but adds no new meaning beyond the schema and does not clarify limit behavior beyond the schema default.

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 names a concrete action ('Get') and resource ('interest suggestions') and ties the output to seed interests. This is enough to distinguish it from sibling searchInterests at a basic level, though it does not explicitly name alternatives.

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?

There is no explicit guidance on when to use this tool versus a sibling like searchInterests or validateInterests. The phrase 'based on a list of seed interests' implies an input condition but does not state a use case or when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.