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Python
Hybrid

google_ads_search_terms_review

Score Google Ads search terms against six fixed rules and sort them into add, exclude, or watch buckets for review. Emits actionable candidates only — it never adds or excludes terms itself.

Instructions

Score every search term in a Google Ads campaign against six hardcoded rules and split them into add / exclude / watch buckets. Returns {campaign_id, ad_group_id, period, target_cpa, target_cpa_source, add_candidates, exclude_candidates, watch_candidates, summary:{total_search_terms, add_count, exclude_count, watch_count}}. Each candidate has {search_term, action, match_type ('EXACT'|'PHRASE'), score (40-90), reason, metrics:{conversions, clicks, cost, ctr}}. target_cpa is resolved from the explicit argument first, then the campaign's bidding strategy, then last-30-days actual CPA; target_cpa_source reports which path ('explicit'|'bidding_strategy'|'actual'|'none'). New terms absent from the previous period are routed to watch_candidates. Read-only — emits candidates but does not add or exclude anything. Default period is LAST_7_DAYS. For keyword/N-gram overlap stats use google_ads_search_terms_analyze; for the raw query log use google_ads_search_terms_report.

Input 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 — "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_cpaNoOptional explicit target CPA in account currency (e.g. 3000 = ¥3,000). Exclusion rule 4 fires at cost >= target_cpa * 2. Falls back to the campaign's bidding strategy target, then last-30-days actual CPA; if none can be resolved, CPA-gated rules are skipped.
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": [
-      "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"
-  }
-]New 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"
+  },
+  {
+    "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_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."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 — \"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": [
+      "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"
-]
  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

A4.8/5.0
Behavior5/5

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

No annotations exist, so the description carries the full burden and does: it declares 'Read-only — emits candidates but does not add or exclude anything,' explains the three-step target_cpa resolution chain and that CPA-gated rules are skipped when unresolvable, and notes that new terms are diverted to watch_candidates. It also flags the LAST_90_DAYS server-timezone asymmetry, which an agent could not infer elsewhere.

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?

Purpose and read-only guarantee are front-loaded, then the return shape, then sibling routing. The literal return-shape listing is verbose, but since no output schema exists it earns its space; the paragraph is dense rather than padded.

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 and no annotations, the description fully specifies the return object, the per-candidate fields, scoring range, the meaning of target_cpa_source values, and the read-only contract. Nothing an agent needs to invoke this correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description adds value by explaining the target_cpa precedence order (explicit → bidding strategy → last-30-days actual) and that target_cpa_source reports which path fired. It reinforces the campaign_id/customer_id sourcing but adds little beyond the schema there.

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 opening sentence states a specific verb and resource ('Score every search term in a Google Ads campaign') plus the concrete outcome (add / exclude / watch buckets). It also names the two sibling tools it is not, so an agent can distinguish review from analyze and report without opening any schema.

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?

It routes explicitly: 'For keyword/N-gram overlap stats use google_ads_search_terms_analyze; for the raw query log use google_ads_search_terms_report.' It also states the default period, when to widen it, and when to pass an explicit range instead.

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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