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google_ads_performance_analyze

Diagnose a Google Ads campaign by comparing current and previous performance, top search terms, Google recommendations, and recent change history.

Instructions

Diagnose a single Google Ads campaign by composing current-vs-previous comparison, top search terms, Google recommendations, and recent change history. Returns {campaign_id, period, campaign (get_campaign shape), performance_current, performance_previous, changes:{impressions_change_pct, clicks_change_pct, cost_change_pct, conversions_change_pct}, cpa_current? (only when current-period conversions > 0), cpa_previous? (only when previous-period conversions > 0), cpa_change_pct? (only when both above are present), top_search_terms (top 20 by cost), recommendations_from_google (up to 10), recent_changes (up to 10), issues:[strings], insights:[strings], recommendations:[strings]}. Any subcomponent that fails is replaced with the string 'Retrieval failed' rather than aborting the call. Read-only. Default period is LAST_7_DAYS. For cost-spike root-cause analysis use google_ads_cost_increase_investigate; for account-wide health use google_ads_health_check_all.

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_idYesCampaign ID as a numeric string without dashes (e.g. '23743184133'). Obtain via google_ads_campaigns_list.
periodNoReporting window for the metrics. Default 'LAST_7_DAYS' — this tool is tuned for short-horizon comparison. Use LAST_14_DAYS or LAST_30_DAYS for longer baselines.
Behavior5/5

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

No annotations provided, but the description fully compensates by declaring 'Read-only', failure behavior ('Any subcomponent that fails is replaced with the string Retrieval failed'), and detailing the return structure including optional fields.

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 comprehensive but not excessively long; every sentence serves a purpose. Slightly verbose in listing return fields but necessary given no output schema.

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 provides a detailed return structure, failure handling, read-only declaration, and default period. All necessary context for an agent to use the tool correctly.

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%, but description adds value: campaign_id is linked to a sibling tool, period is described as 'tuned for short-horizon comparison' with suggestions for longer baselines.

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 verb 'diagnose' and resource 'single Google Ads campaign', and specifies the composed subcomponents. It distinguishes from siblings like google_ads_cost_increase_investigate and google_ads_health_check_all.

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 this tool vs alternatives: 'For cost-spike root-cause analysis use google_ads_cost_increase_investigate; for account-wide health use google_ads_health_check_all.' Also mentions default period and fallback for customer_id.

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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