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google_ads_network_performance_report

Compare Google Ads performance across Google Search and Search Partners networks to decide whether to toggle Search Partners for better campaign efficiency.

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.
Behavior5/5

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

Despite no annotations, the description thoroughly discloses behavior: read-only operation, filtering out Display/YouTube/Discover rows, rounding of certain metrics to whole-unit currency, and the output shape. No contradictions.

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?

Efficient and front-loaded: first sentence states purpose, followed by output shape, filtering details, rounding notes, and usage guidance. No redundant information.

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?

Complete for a read-only report tool: describes output schema, filtering, rounding, default behaviors, and usage context. No output schema existed, so the detailed output shape description is essential and well-provided.

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%. The description adds significant value by explaining parameter defaults (e.g., period default and usage recommendations) and the customer_id fallback, going beyond the schema's definitions.

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?

Clearly defines the tool as reporting Google Ads performance split by ad network (Google Search vs. Search Partners). Specifies the output structure and explicitly distinguishes from sibling tools like google_ads_performance_report and google_ads_ad_performance_report.

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 guidance: 'Use this to decide whether to toggle Search Partners.' Also tells when not to use it, referencing alternative tools for overall campaign totals and per-ad breakdowns.

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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