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create_lookalike_audience

Destructive

Create a lookalike audience from one of your custom audiences (source needs at least ~100 people). ratio 1 = the closest 1% of the country. Pro. WRITES live.

Input Schema

NameRequiredDescriptionDefault
nameNo
countryYes2-letter country code, e.g. IN.
ratio_percentNo1-10. Default 1.
meta_account_idYes
source_audience_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false and destructiveHint=true; the description reinforces this with 'WRITES live', making the live mutation unmistakable. It adds context not in the annotations — the Pro plan gate and the minimum source-audience size — but says nothing about reversibility, propagation delay for lookalike builds, or failure modes.

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?

Four short clauses, front-loaded with the action and its constraint; nothing is redundant. The fragments 'Pro.' and 'WRITES live.' are terse to the point of being cryptic, costing a little readability.

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 5-parameter mutation with no output schema and only 40% parameter coverage, the description covers the essentials an agent needs to avoid a failed call (Pro plan, 100-person source, mutation warning). It stops short of explaining what is returned (e.g., new audience id), how long creation takes, or the meaning of meta_account_id.

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 coverage is 40%, so the description needs to compensate. It usefully defines ratio ('1 = the closest 1% of the country') and ties source_audience_id to a minimum-size requirement, but leaves meta_account_id, the optional name/default-naming behavior, and valid ratio range largely unaddressed in prose.

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?

States a specific verb and resource ('Create a lookalike audience') and pins the source to 'one of your custom audiences', which separates it from create_website_audience. It doesn't explicitly name that sibling, but the source constraint is enough for an agent to disambiguate.

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

Usage Guidelines3/5

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

It supplies a real prerequisite (source audience of at least ~100 people) and flags the plan requirement ('Pro'), which helps an agent decide whether the call can succeed. However, there is no explicit when-to-use/when-not guidance and no alternative tool is named for building an audience from a website or pixel instead.

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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