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google_ads_search_terms_report

List actual search queries that triggered ads with metrics (impressions, clicks, cost, conversions, CTR). Filter by campaign or ad group to analyze raw query performance.

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?

Despite no annotations, the description declares read-only behavior and explains that filter IDs are not in output. It lists return metrics in detail. Slightly lacking on pagination or rate limits, but adequate for a read-only report tool.

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?

The description is well-structured, starting with purpose, then output format, then behavioral details, then sibling differentiation. Each sentence adds value, though it could be slightly shorter. No redundancy.

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 thoroughly explains the return shape including metrics. It covers all parameters' purpose, default behavior, and when to use siblings. No gaps for the agent.

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%, so baseline is 3. The description adds value by providing examples for customer_id, suggesting window lengths for diagnostics, and clarifying default behavior.

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 returns actual search queries that triggered ads, with one row per term and a metrics object. It explicitly distinguishes from sibling tools by naming them and their purposes.

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?

The description provides explicit guidance: use this for raw query logs, and for other use cases like rule-based review or intent analysis, it names specific sibling tools. It also warns that filter IDs are not echoed back.

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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