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dhawalshah

meta-ads-mcp

get_targeting_sentence_lines

Get a human-readable explanation of ad set targeting from an ad set ID, returning audience targeting as easy-to-understand sentence lines.

Instructions

Get a human-readable description of an ad set's targeting configuration. Args: adset_id: The ID of the ad set. Returns: A dictionary containing sentence_lines — a plain-English breakdown of the targeting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
adset_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does describe the return shape and content: 'a dictionary containing sentence_lines — a plain-English breakdown of the targeting.' However, it does not mention authentication, error behavior, side effects, or explicitly confirm a read-only operation.

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 compact and well-structured: a one-sentence summary followed by brief Args and Returns sections. Every line contributes useful information, and there is no filler 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?

For a simple one-parameter read tool, the description covers the input and the return value sufficiently, especially since an output schema exists. It lacks broader context about when to choose this tool over siblings and omits error/edge-case details, but these are relatively minor for a getter of this complexity.

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 only declares adset_id as a required string with no description. The tool description adds a minimal semantic gloss — 'The ID of the ad set' — which compensates somewhat for the 0% schema coverage, but it provides no format, source, or usage detail beyond what the parameter name already implies.

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 states a specific verb and resource: 'Get a human-readable description of an ad set's targeting configuration.' It clearly describes what the tool does and hints at a unique output format (sentence_lines), though it does not explicitly distinguish itself from sibling tools like get_targeting_suggestions.

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 guidance on when to use this tool versus alternatives such as get_targeting_suggestions or search_targeting_options. No context, exclusions, or selection criteria are provided, so an agent must infer appropriate usage from the name and description alone.

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