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Python
Hybrid

google_ads_keywords_audit

Audit a Google Ads campaign’s keyword portfolio to surface pause, bid-raise, match-type-tighten, and unused-keyword recommendations with spend, conversion, and reason data.

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. When the keyword performance read fails, total_keywords, avg_cvr, recommendations and summary are null. Read-only — recommendations are not applied. Materialize accepted ones via google_ads_keywords_pause / add / negative_keywords.add.

Input Schema

NameRequiredDescriptionDefault
periodNoAnalysis window for the keyword metrics. Default 'LAST_30_DAYS'. Also accepts an explicit range — "YYYY-MM-DD..YYYY-MM-DD" (the spelling Meta Ads takes too) or, 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 changedv0.33.0
    • changedInput schema / properties / period / anyOf
      Previous 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"
-  }
-]New 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"
+  },
+  {
+    "pattern": "\\A([0-9]{4}-[0-9]{2}-[0-9]{2})\\.\\.([0-9]{4}-[0-9]{2}-[0-9]{2})\\Z",
+    "type": "string"
+  }
+]
    • changedInput schema / properties / period / description
      Previous 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."New value: +"Analysis window for the keyword metrics. Default 'LAST_30_DAYS'. Also accepts an explicit range — \"YYYY-MM-DD..YYYY-MM-DD\" (the spelling Meta Ads takes too) or, 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. 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."
  3. Changed1 schema field changedv0.10.37
    • addedInput schema / additionalProperties
      Added value: +false
  4. Addedv0.10.11
  5. Removedv0.10.9
  6. Addedv0.9.12
  7. Removedv0.9.6
  8. Addedv0.9.2
  9. Removedv0.9.1
  10. Addedv0.2.1
  11. Removedv0.2.0
  12. Addedv0.3.0
  13. Removedv0.7.1
  14. Addedv0.6.0
  15. Removedv1.0.6
  16. Addedv1.0.5

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it declares read-only semantics, enumerates the returned fields per item (criterion_id, text, spend, conversions, reason), and discloses a concrete failure mode (total_keywords, avg_cvr, recommendations and summary become null when the performance read fails). It says nothing about permissions scope, cost/latency, or whether the audit is bounded in size, which are the remaining unknowns for an aggregate analysis call.

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 the action, then the output shape, then the failure case, then the follow-up tools — a logical order with no filler. The enumeration of returned fields and the null-list sentence are dense but each earns its place; only slight tightening would improve it.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description compensates by naming the recommendation groups, per-item fields, and the null-degradation contract, plus how to act on results. For a read-only aggregate analysis tool this is nearly sufficient; what is missing is any sense of result volume/ordering or how target_cpa affects the ranking criteria.

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 description coverage is 100%, and the schema already documents period semantics (including the LAST_90_DAYS time-zone asymmetry), target_cpa fallback, and customer_id fallback in detail. The description adds no parameter-level meaning beyond the schema, so the 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?

States a specific verb and resource ('runs a holistic keyword-portfolio audit for a campaign') and immediately enumerates the four recommendation categories returned, which lets an agent distinguish it from siblings like google_ads_keywords_diagnose or google_ads_keywords_cross_adgroup_duplicates without opening the schema.

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 clearly frames the tool as advisory ('read-only — recommendations are not applied') and routes the agent to the concrete write tools (pause / add / negative_keywords.add) for materializing accepted items, which is genuine when-next guidance. It stops short of stating when to prefer this over the adjacent diagnostic tools (keywords_diagnose, search_terms_analyze), so no explicit exclusion is given.

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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