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OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Hybrid

google_ads_keywords_audit

Audit a Google Ads campaign's keyword portfolio and get grouped recommendations: pause underperformers, raise bids, tighten match types, and discover new keyword ideas. Read-only guidance.

Instructions

Runs a holistic keyword-portfolio audit for a campaign and returns grouped recommendations: pause candidates (zero-spend or zero-conversion), bid-raise candidates (below first-page bid), match-type-tighten candidates (broad stealing spend), and unused keyword-planner ideas. Each item includes criterion_id, text, spend, conversions, and a reason string. Read-only — recommendations are not applied. Materialize accepted ones via google_ads_keywords_pause / add / negative_keywords.add.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNoAnalysis window for the keyword metrics. Default 'LAST_30_DAYS'. Also accepts an explicit range in GAQL spelling — "BETWEEN 'YYYY-MM-DD' AND 'YYYY-MM-DD'", both endpoints inclusive, in the account's time zone — for a window no trailing constant can reach (e.g. a single past calendar month). One asymmetry to know about: every constant except LAST_90_DAYS is resolved by Google Ads in the account's reporting time zone, whereas LAST_90_DAYS has no API constant and is expanded by mureo into the 90 days ending yesterday **on the server's date**, so its edges can differ by a day when the server and the account are in different zones. Pass an explicit range when the exact boundary matters.
target_cpaNoTarget CPA in the account's currency used to score efficiency. Falls back to the campaign's configured target_cpa when omitted.
campaign_idYesCampaign to audit.
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. Changed2 schema fields changedv0.17.1
    • addedInput schema / properties / period / anyOf
      Added value: +[
+  {
+    "enum": [
+      "TODAY",
+      "YESTERDAY",
+      "THIS_WEEK_SUN_TODAY",
+      "THIS_WEEK_MON_TODAY",
+      "LAST_BUSINESS_WEEK",
+      "LAST_WEEK_SUN_SAT",
+      "LAST_WEEK_MON_SUN",
+      "LAST_7_DAYS",
+      "LAST_14_DAYS",
+      "LAST_30_DAYS",
+      "LAST_90_DAYS",
+      "THIS_MONTH",
+      "LAST_MONTH"
+    ],
+    "type": "string"
+  },
+  {
+    "pattern": "\\ABETWEEN '([0-9]{4}-[0-9]{2}-[0-9]{2})' AND '([0-9]{4}-[0-9]{2}-[0-9]{2})'\\Z",
+    "type": "string"
+  }
+]
    • changedInput schema / properties / period / description
      Previous value: -"Analysis window. Accepts 'LAST_7_DAYS', 'LAST_14_DAYS', 'LAST_30_DAYS' (default), or 'YYYY-MM-DD..YYYY-MM-DD'."New value: +"Analysis window for the keyword metrics. Default 'LAST_30_DAYS'. Also accepts an explicit range in GAQL spelling — \"BETWEEN 'YYYY-MM-DD' AND 'YYYY-MM-DD'\", both endpoints inclusive, in the account's time zone — for a window no trailing constant can reach (e.g. a single past calendar month). One asymmetry to know about: every constant except LAST_90_DAYS is resolved by Google Ads in the account's reporting time zone, whereas LAST_90_DAYS has no API constant and is expanded by mureo into the 90 days ending yesterday **on the server's date**, so its edges can differ by a day when the server and the account are in different zones. Pass an explicit range when the exact boundary matters."
  2. Changed1 schema field changedv0.10.37
    • addedInput schema / additionalProperties
      Added value: +false
  3. Addedv0.10.11
  4. Removedv0.10.9
  5. Addedv0.9.12
  6. Removedv0.9.6
  7. Addedv0.9.2
  8. Removedv0.9.1
  9. Addedv0.2.1
  10. Removedv0.2.0
  11. Addedv0.3.0
  12. Removedv0.7.1
  13. Addedv0.6.0
  14. Removedv1.0.6
  15. Addedv1.0.5

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden and does so well: it states twice that this is read-only, that recommendations are not applied, and what each returned item contains. It doesn't cover edge behaviors like empty results or account permission failures, but for a read-only audit the critical non-mutating behavior is explicit.

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?

The main description is compact and front-loaded with the action and output categories, followed by the read-only caveat and materialization pointers. The long period explanation is justified because it documents a non-obvious timezone boundary that can change results.

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?

There is no output schema, so the description compensates by stating the exact item fields (criterion_id, text, spend, conversions, reason) and the four group types. Combined with rich parameter documentation and the explicit read-only/application path, an agent has what it needs to invoke this tool correctly and interpret the result.

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?

Although the schema already describes all four parameters, the description adds substantial non-obvious meaning: the default for period, acceptance of GAQL range syntax, the timezone asymmetry of LAST_90_DAYS, and credential fallbacks for customer_id and campaign target CPA. These are exactly the details an agent needs to pass correct values.

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 opens with a specific verb and resource: 'Runs a holistic keyword-portfolio audit for a campaign' and enumerates exactly what recommendation groups are returned. It clearly distinguishes itself from mutation siblings by stating it is read-only and directing materialization to google_ads_keywords_pause/add/negative_keywords.add.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear context for when this is the right tool—whole-portfolio audit across four named recommendation categories—and names the follow-up tools for applying results. It stops short of explicit exclusion guidance against nearby analysis tools like keywords_diagnose or keywords_list, so it earns a 4 rather than a 5.

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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