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google_ads_ad_performance_report

Retrieve per-ad performance metrics including impressions, clicks, cost, and conversions for Google Ads campaigns. Filter by ad group or campaign to analyze individual ad results.

Instructions

Report per-ad performance across Google Ads ad_group_ad rows. Returns one row per ad shaped as {ad_id, ad_type, status ('ENABLED'|'PAUSED'|'REMOVED'), ad_group_id, ad_group_name, campaign_id, campaign_name, metrics} where metrics contains impressions, clicks, cost_micros, cost (currency), conversions, ctr, average_cpc_micros, average_cpc, cost_per_conversion_micros, cost_per_conversion. Filterable by ad_group_id and/or campaign_id (both optional, both numeric). Read-only; no mutation. For ENABLED-only A/B comparison within a single ad group with WINNER/LOSER verdicts use google_ads_ad_performance_compare; for campaign-level aggregates 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.
ad_group_idNoOptional ad group ID as a numeric string (e.g. '145680123456') to restrict results to a single ad group. Omit to include every ad group matching the campaign filter.
campaign_idNoOptional campaign ID as a numeric string (e.g. '23743184133') to restrict the report to a single campaign. Omit to aggregate across every campaign in the account.
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?

No annotations are provided, so the description carries full burden. It explicitly states 'Read-only; no mutation' and describes the return shape and metrics. It mentions that customer_id can be inferred from credentials but does not cover potential pagination or rate limits. Overall, it provides good behavioral context.

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 front-loaded with the main purpose and output shape, followed by filtering, read-only note, and alternatives. Every sentence adds value with no wasted words. It is appropriately sized for the tool's complexity.

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?

Despite no output schema, the description details the return shape and metrics. It covers purpose, parameters, alternatives, and behavioral nature. It might miss details like sorting or pagination, but overall it is sufficiently complete for a read-only report tool.

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% and the description adds meaning beyond the schema: for 'period', it suggests using shorter windows for recent changes; for 'ad_group_id' and 'campaign_id', it explains default behavior when omitted; for 'customer_id', it explains fallback to credentials. This adds substantial value.

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 reports per-ad performance from ad_group_ad rows, specifies the output shape with fields like ad_id, ad_type, status, and metrics. It differentiates from siblings by naming google_ads_ad_performance_compare for A/B comparison and google_ads_performance_report for campaign-level aggregates.

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

Usage Guidelines4/5

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

The description clearly indicates the tool is read-only and filterable by ad_group_id and campaign_id. It provides guidance on when to use alternative tools for specific needs (A/B comparison or campaign-level). However, it does not explicitly state when not to use this tool beyond those alternatives.

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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