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Python
Hybrid

google_ads_cpc_detect_trend

Identify rising or falling CPC trends within Google Ads campaigns. Use daily data and linear regression to calculate the trend direction and rate of change over a specified reporting window.

Instructions

Detect rising/falling CPC trends in a Google Ads campaign over a reporting window using daily segmentation and linear regression. Returns {campaign_id, campaign_name, period, data_points, daily_data:[{date, average_cpc, clicks, impressions, cost}], trend:{direction ('rising'|'falling'|'stable'|'insufficient_data'), slope_per_day, change_rate_per_day_pct? (present only when direction is not 'insufficient_data' — i.e. when at least 2 daily data points are available), avg_cpc, min_cpc, max_cpc}, insights:[strings]}. Direction is 'rising' when daily change > +1%, 'falling' when < -1%. Days with zero clicks are excluded from the GAQL. Insights call out week-over-week surges >15% and days exceeding 2x average CPC. Read-only. For device or auction-share investigation use google_ads_device_analyze or google_ads_auction_insights_analyze.

Input Schema

NameRequiredDescriptionDefault
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. 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.
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. 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: -"Reporting 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. 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: +"Reporting 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. 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. Changed3 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: -"Reporting 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."New value: +"Reporting 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. 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"
-]
  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. Addedv1.0.5

TDQS

A4.2/5.0
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 it does well: 'Read-only' declares safety, the +1%/-1% thresholds define what 'rising'/'falling' mean, zero-click days are disclosed as excluded from the GAQL, and the insights triggers (>15% WoW surge, 2x average CPC days) are spelled out. Not a 5 only because it doesn't touch auth/scoping caveats beyond the customer_id fallback.

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 verb and resource, and every clause (thresholds, exclusions, routing) earns its place. The inline return-shape block is lengthy, but it substitutes for the absent output schema, so the density is justified rather than wasteful.

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?

For a statistical analysis tool with no annotations and no output schema, the description supplies the full return structure, the direction thresholds, the edge case ('insufficient_data' when fewer than 2 data points), and the insight-generation rules. An agent has everything needed to call and interpret it 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?

Schema description coverage is 100%, so campaign_id, customer_id, and the period enum/ranges are already fully documented in the schema. The description adds no parameter-level meaning the schema lacks, 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 ('Detect rising/falling CPC trends in a Google Ads campaign') plus the exact method (daily segmentation, linear regression). It closes by naming the siblings it is not (google_ads_device_analyze, google_ads_auction_insights_analyze), so an agent can disambiguate without opening a 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?

Explicitly routes device and auction-share investigation to two named alternatives, and the schema-adjacent period advice ('shorter window when diagnosing recent changes, LAST_90_DAYS for baselines') gives clear context. It doesn't distinguish itself from the broader google_ads_performance_analyze or google_ads_cost_increase_investigate siblings, so routing is clear but incomplete.

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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