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google_ads_network_performance_report

Analyze Google Ads performance per campaign segmented by ad network: Google Search vs Search Partners. Examine impressions, clicks, cost, and conversions to decide whether to toggle Search Partners.

Instructions

Report Google Ads performance split by ad network — Google Search vs. Search Partners. Returns one row per (campaign, network) shaped as {campaign_id, campaign_name, network_type ('SEARCH'|'SEARCH_PARTNERS'), network_label ('Google Search'|'Search Partners'), impressions, clicks, cost, conversions, ctr (percent), average_cpc, cost_per_conversion}. Display, YouTube, and Discover rows are filtered out. ctr, average_cpc, and cost_per_conversion are rounded to whole-unit currency. Read-only. Use this to decide whether to toggle Search Partners. For overall campaign totals use google_ads_performance_report; for per-ad breakdowns use google_ads_ad_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_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?

With no annotations, the description carries full burden. It declares read-only, filters out display/YouTube/Discover, and notes rounding. However, it omits error handling and permission requirements.

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?

Well-structured: front-loaded with purpose, followed by output shape, filtering, rounding, read-only note, and usage guidance. Every sentence adds value, 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?

Despite no output schema, the description fully specifies the output shape, filtering, rounding, and fallback behavior. It covers enough context for an AI 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.

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. Description adds little beyond schema; it repeats period usage guidance already in schema descriptions, providing minimal extra parameter insight.

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 'Report Google Ads performance split by ad network' and the specific resource, distinguishing it from siblings by naming alternative tools for different scopes.

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?

Explicit guidance provided: 'Use this to decide whether to toggle Search Partners' and direct references to sibling tools for overall totals and per-ad breakdowns, with period recommendations for diagnosis.

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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