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google_ads_search_terms_review

Score every search term in a Google Ads campaign against six hardcoded rules to split them into add, exclude, or watch buckets, delivering candidates with scores and reasons for optimization.

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}, intent_analysis?}. 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

TableJSON Schema
NameRequiredDescriptionDefault
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.
campaign_idYesCampaign ID as a numeric string without dashes (e.g. '23743184133'). Obtain via google_ads_campaigns_list.
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.
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.
Behavior5/5

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

With no annotations, description fully covers behavioral traits: read-only, six hardcoded rules, target CPA resolution from multiple sources, new terms routed to watch_candidates, default period, and behavior when CPA cannot be resolved.

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?

Description is comprehensive but well-structured: starts with main purpose, then return structure, then parameter details, then sibling differentiation. Every sentence adds value without redundancy.

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?

Despite no output schema, description details the return format including nested objects. Covers all parameter behaviors, defaults, fallbacks, and distinguishes from siblings. Provides complete context for an AI to use this tool correctly.

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?

All 4 parameters have schema descriptions, but description adds significant context: target CPA resolution logic (explicit, bidding strategy, actual, none), default period, customer_id fallback, and the specific exclusion rule threshold (cost >= target_cpa * 2).

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?

Description clearly states it scores search terms against six hardcoded rules and splits into add/exclude/watch buckets. It names the return structure and distinguishes from sibling tools google_ads_search_terms_analyze and google_ads_search_terms_report.

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?

Explicitly says 'Read-only — emits candidates but does not add or exclude anything' and directs to siblings for other use cases (keyword/N-gram overlap stats, raw query log). Provides default period and fallback behavior for target_cpa.

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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