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google_ads_performance_analyze

Compare current and previous Google Ads campaign performance, view top search terms, Google recommendations, and recent changes. Identify issues and insights to optimize campaigns.

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.
Behavior4/5

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

No annotations exist; description carries full burden. It states read-only, explains subcomponent failure behavior (replaced with 'Retrieval failed'), and details optional return fields (cpa_current, cpa_previous, cpa_change_pct) with conditions. Lacks explicit mention of authentication or rate limits, but covers core behavioral traits well.

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?

Description is well-structured but slightly verbose. It front-loads the purpose and return shape, then provides detailed notes. Could be trimmed slightly without losing clarity, but remains effective.

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?

Fully covers the complex tool with multiple subcomponents. Addresses edge cases (retrieval failures, conditional fields), provides default behavior, and ties output to sibling tools. No output schema needed as description sufficiently explains return structure.

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%; description adds significant context: customer_id fallback from credentials, campaign_id reference to google_ads_campaigns_list, and period customization advice (short-horizon tuning, long baselines). Goes beyond schema by explaining how parameters interact with tool 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 uses a specific verb 'diagnose' and resource 'single Google Ads campaign', lists concrete components (comparison, search terms, recommendations, history), and 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?

Provides explicit when-to-use (diagnosing a campaign), default period (LAST_7_DAYS), and alternatives for related analyses (cost-spike root-cause: google_ads_cost_increase_investigate; account-wide health: google_ads_health_check_all). Also mentions read-only nature and graceful failure handling.

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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