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google_ads_search_terms_report

Retrieve actual search terms that triggered your ads, with impressions, clicks, cost, and conversions. Filter by campaign or ad group to inspect raw query logs for any period.

Instructions

List actual user search queries that triggered ads in the account over a reporting window. Returns one row per search term shaped as {search_term, metrics}, where the metrics object contains impressions, clicks, cost_micros, cost (currency-formatted), conversions, and ctr. The rows are filterable by campaign_id and/or ad_group_id but those IDs are NOT echoed back in the output — scope your query before calling. Read-only. Use this for raw query logs when you need to eyeball the terms yourself. For rule-based add/exclude candidates use google_ads_search_terms_review; for intent-class distribution use google_ads_search_terms_analyze; for campaign-level aggregates without query breakdown use google_ads_performance_report.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customer_idNoGoogle Ads customer ID as a 10-digit string without dashes (e.g. '1234567890'). Optional — falls back to GOOGLE_ADS_CUSTOMER_ID / GOOGLE_ADS_LOGIN_CUSTOMER_ID from the configured credentials when omitted.
campaign_idNoRestrict results to a single campaign by numeric ID. Omit to include all campaigns.
ad_group_idNoRestrict results to a single ad group by numeric ID. Omit to include all ad groups under the campaign filter (or the entire account if campaign_id is also omitted).
periodNoReporting window for the metrics. Default 'LAST_30_DAYS'. Use a shorter window (LAST_7_DAYS / LAST_14_DAYS) when diagnosing recent changes; use LAST_90_DAYS for trend baselines.
Behavior4/5

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

With no annotations, the description bears full burden. It declares read-only and warns that filter IDs are not echoed back. It does not mention pagination or result limits, but overall provides sufficient behavioral context for a reporting tool.

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?

Every sentence earns its place; front-loaded with main action, covers return format, filtering, read-only, and sibling differentiation with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description explains the output shape completely. It covers filtering behavior, scope, and relationships with siblings. All aspects are addressed for confident agent use.

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

Parameters5/5

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

Schema coverage is 100%, but description adds value: warns that campaign_id and ad_group_id are not echoed, and provides guidance on period choice (shorter windows for recent changes, longer for trends).

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?

The description clearly states the tool lists actual user search queries that triggered ads, specifies the return shape, and explicitly names sibling tools for differentiation, achieving a specific verb+resource and distinguishing from alternatives.

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?

Explicitly states when to use (raw query logs for eyeballing) and when not, with named alternatives: google_ads_search_terms_review for rule-based, google_ads_search_terms_analyze for intent-class, google_ads_performance_report for campaign-level aggregates.

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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