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andrealufino

aapl-ads-mcp

get_search_terms_report

Retrieve actual search queries that triggered Apple Search Ads impressions with performance metrics. Identify new keywords to add and irrelevant queries to exclude. Aggregate data from the last 30 days.

Instructions

Fetch the actual user search queries that triggered Apple Search Ads impressions, along with performance metrics per search term. Requires ASA authentication; read-only. Most useful for keyword discovery (finding new terms to add) and negation (finding irrelevant queries to exclude). Does not support granularity breakdown — returns aggregate totals per search term. Use get_keyword_report to see metrics for your configured targeting keywords instead. Defaults to the last 30 days.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
startDateNoStart of the reporting period (YYYY-MM-DD). Defaults to 30 days ago.
endDateNoEnd of the reporting period (YYYY-MM-DD). Defaults to today.
granularityNoIgnored for this report — the ASA API does not support granularity on search terms reports.
campaignIdYesID of the campaign containing the ad group. Obtain from list_campaigns.
adGroupIdYesID of the ad group to report on. Obtain from list_ad_groups.
Behavior4/5

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

Discloses read-only nature, authentication requirement, that granularity is not supported, and aggregate totals are returned. However, lacks details on error handling, rate limits, or specific performance metrics returned.

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?

Five sentences, each serving a purpose. Front-loaded with main action, then usage, then limitations. No redundant information.

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?

Covers purpose, usage, behavior, and limitations. Lacks specifics on return format or metrics, but given no output schema, the description is reasonably complete for a report tool.

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?

Schema coverage is 100% and description adds value by explaining defaults for startDate/endDate, that granularity is ignored, and how to obtain campaignId and adGroupId (via list_campaigns and list_ad_groups).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description specifies the verb 'Fetch' and resource 'actual user search queries... along with performance metrics per search term'. It clearly distinguishes from sibling tool get_keyword_report by stating the difference between search terms and configured targeting keywords.

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

Usage Guidelines5/5

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

Provides explicit when-to-use scenarios: 'keyword discovery' and 'negation'. Explicitly directs to use get_keyword_report for targeting keywords. Also notes that granularity is ignored and defaults to 30 days.

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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