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mureo

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OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

google_ads_performance_analyze

Diagnose a single Google Ads campaign's performance by comparing current vs previous metrics, top search terms, Google recommendations, and recent change history to surface issues and actionable insights.

Instructions

Diagnose a single Google Ads campaign by composing current-vs-previous comparison, top search terms, Google recommendations, and recent change history. Returns {campaign_id, period, campaign (get_campaign shape), performance_current, performance_previous, changes:{impressions_change_pct, clicks_change_pct, cost_change_pct, conversions_change_pct}, cpa_current? (only when current-period conversions > 0), cpa_previous? (only when previous-period conversions > 0), cpa_change_pct? (only when both above are present), top_search_terms (top 20 by cost), recommendations_from_google (up to 10), recent_changes (up to 10), issues:[strings], insights:[strings], recommendations:[strings]}. Any subcomponent that fails is replaced with the string 'Retrieval failed' rather than aborting the call. Read-only. Default period is LAST_7_DAYS. For cost-spike root-cause analysis use google_ads_cost_increase_investigate; for account-wide health use google_ads_health_check_all.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNoReporting window for the metrics. Default 'LAST_7_DAYS' — this tool is tuned for short-horizon comparison. Use LAST_14_DAYS or LAST_30_DAYS for longer baselines. This tool also reads the equal-length window immediately before the one you request, so only fixed-length windows are accepted — calendar constants such as THIS_MONTH are rejected rather than silently replaced. 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.
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. Dates show when Glama detected each change.

  1. Changed3 schema fields changedv0.17.1
    • addedInput schema / properties / period / anyOf
      Added value: +[
+  {
+    "enum": [
+      "LAST_7_DAYS",
+      "LAST_14_DAYS",
+      "LAST_30_DAYS",
+      "LAST_90_DAYS"
+    ],
+    "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: -"Reporting window for the metrics. Default 'LAST_7_DAYS' — this tool is tuned for short-horizon comparison. Use LAST_14_DAYS or LAST_30_DAYS for longer baselines."New value: +"Reporting window for the metrics. Default 'LAST_7_DAYS' — this tool is tuned for short-horizon comparison. Use LAST_14_DAYS or LAST_30_DAYS for longer baselines. This tool also reads the equal-length window immediately before the one you request, so only fixed-length windows are accepted — calendar constants such as THIS_MONTH are rejected rather than silently replaced. 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."
    • removedInput schema / properties / period / enum
      Removed value: -[
-  "TODAY",
-  "YESTERDAY",
-  "LAST_7_DAYS",
-  "LAST_14_DAYS",
-  "LAST_30_DAYS",
-  "LAST_90_DAYS",
-  "THIS_MONTH",
-  "LAST_MONTH"
-]
  2. Changed1 schema field changedv0.10.37
    • addedInput schema / additionalProperties
      Added value: +false
  3. Addedv0.9.12
  4. Removedv0.9.6
  5. Addedv0.9.2
  6. Removedv0.9.1
  7. Addedv1.0.5

TDQS

A4.7/5.0
Behavior5/5

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

No annotations are present, so the description carries the full burden of behavioral disclosure. It explicitly states the tool is read-only, describes the failure fallback behavior ('Retrieval failed' instead of aborting), and specifies output limits and conditional fields. These are substantive behavioral details beyond any structured metadata.

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 description is long but each sentence carries information: purpose, returned object shape, fallback behavior, read-only status, default period, and sibling routing. The return object is compactly represented with optionality markers and count limits, and the most important scoping information is front-loaded.

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, the description thoroughly documents the return object's keys, nested changes fields, conditional cpa fields, item limits, and failure behavior. Combined with the detailed period semantics in the schema and explicit sibling alternatives, an agent has enough context to select and invoke 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?

The input schema already covers all three parameters with detailed descriptions, including a thorough explanation of the period parameter and an explicit example for campaign_id. The description adds tool-level context but little parameter-specific meaning beyond what the schema provides, so the baseline score is appropriate.

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 the specific action 'Diagnose a single Google Ads campaign' and lists the exact component analyses it combines. It explicitly contrasts itself with google_ads_cost_increase_investigate and google_ads_health_check_all, so an agent can distinguish it from siblings without opening schemas.

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?

The description explicitly routes to alternatives: use google_ads_cost_increase_investigate for cost-spike root-cause analysis and google_ads_health_check_all for account-wide health. It also states the default period, notes the tool is tuned for short-horizon comparison, and clarifies it targets a single campaign rather than broader diagnostics.

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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