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google_ads_monitoring_zero_conversions

Diagnose Google Ads campaigns with zero conversions by checking tracking, bidding alignment, 7-day funnel, delivery issues, and search-term quality to pinpoint the bottleneck and recommend fixes.

Instructions

Diagnose a Google Ads campaign that is not acquiring conversions by composing tracking config, bidding alignment, last-7-days funnel, delivery diagnostics, and search-term quality. Returns {campaign_id, conversion_tracking:{total_actions, enabled_actions, has_issue, actions}, bidding_cv_alignment:{strategy, is_smart_bidding, cv_tracking_configured, issue}, funnel:{period:'LAST_7_DAYS', impressions, clicks, conversions, cost, ctr, cvr, bottleneck ('no_delivery'|'no_clicks'|'no_conversions'|None)}, delivery_diagnosis:{issues, warnings, recommendations}, search_term_quality:{total_terms, zero_cv_terms, zero_cv_cost, top_wasteful_terms} (null when clicks==0), status ('critical'|'warning'|'healthy'|'unknown'), issues:[strings], summary, suggested_workflow?, recommended_actions:[{priority, action, description}]}. A part that could not be retrieved is null and named in issues, and nothing is derived from it: a failed conversion action read leaves conversion_tracking and cv_tracking_configured null, a failed campaign read leaves strategy and is_smart_bidding null, a failed performance read leaves funnel null. status is 'unknown' when the campaign, conversion action or performance read failed and nothing that was read is critical. The evaluation window is hardcoded to LAST_7_DAYS. Read-only; generates an action plan but does not execute anything. For CPA monitoring use google_ads_monitoring_cpa_goal; for CV-count monitoring use google_ads_monitoring_cv_goal.

Input Schema

NameRequiredDescriptionDefault
campaign_idYesCampaign ID as a numeric string without dashes (e.g. '23743184133'). Obtain via google_ads_campaigns_list.
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.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.10.37
    • addedInput schema / additionalProperties
      Added value: +false
  2. Addedv0.9.12
  3. Removedv0.9.6
  4. Addedv0.9.2
  5. Removedv0.9.1
  6. Addedv1.0.5

TDQS

A4.4/5.0
Behavior4/5

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

No annotations exist, so the description carries the whole burden and does so well: it declares read-only behavior ('generates an action plan but does not execute anything'), the hardcoded LAST_7_DAYS window, and detailed null-propagation semantics on partial retrieval failures. It does not state rate limits, auth/permission requirements, or latency/cost of the multi-source composite, which keeps it below 5.

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?

Front-loaded with purpose and alternatives, and the exhaustive return-shape enumeration earns its place because no output schema exists. It is dense and readable but the inline type dump is long and slightly run-on, so not a 5.

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?

With no output schema, no annotations, and a composite multi-source tool, the description compensates by documenting every returned field, the status enum values, the bottleneck enum, and the failure semantics that drive status='unknown'. An agent has everything needed to call it and interpret the result.

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% and both parameters are documented in the schema with format examples and fallback behavior for customer_id. The description adds nothing about parameters, so baseline 3 applies.

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?

Opens with a specific verb and a precisely scoped resource: 'Diagnose a Google Ads campaign that is not acquiring conversions.' It then enumerates the exact sub-analyses composed (tracking config, bidding alignment, funnel, delivery, search terms), so the agent knows this is a composite diagnostic, not a raw 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?

Explicitly names the two alternatives and the condition that selects each: 'For CPA monitoring use google_ads_monitoring_cpa_goal; for CV-count monitoring use google_ads_monitoring_cv_goal.' Combined with the zero-conversions trigger, the routing decision is unambiguous.

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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