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Retrieve matching record IDs from Meta Ads data by querying across accounts, campaigns, ads, pages, and businesses.

Instructions

Search through Meta Ads data and return matching record IDs.
It searches across ad accounts, campaigns, ads, pages, and businesses to find relevant records
based on the provided query.

Args:
    query: Search query string to find relevant Meta Ads records
    access_token: Meta API access token (optional - will use cached token if not provided)
    
Returns:
    JSON response with list of matching record IDs
    
Example Usage:
    search(query="active campaigns")
    search(query="account spending")
    search(query="facebook ads performance")
    search(query="facebook pages")
    search(query="user businesses")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
access_tokenNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description must disclose behavior but only states it returns record IDs. It does not mention read-only nature, pagination, rate limits, or authentication details beyond a cached token option.

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 concise and well-structured, with a clear purpose statement, Args and Returns sections, and example usage. No superfluous content exists.

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?

The description is adequate for basic use but lacks details on pagination, scope limitations, and handling of large result sets. The presence of an output schema partially mitigates the need for return value explanations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Given 0% schema description coverage, the description adds value by explaining both parameters: query as a search string and access_token as optional with fallback to cached token. This compensates for the schema's lack of documentation.

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 clearly states the tool searches Meta Ads data and returns matching record IDs across multiple resources. However, it does not differentiate this general search from more specific sibling tools like search_ads_archive or search_interests, leaving ambiguity about when to use which.

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?

The description lacks guidance on when to use this tool versus alternatives. No explicit conditions or exclusions are provided, leaving the agent without context for selection.

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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