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google_ads_search_terms_review

Score every search term in a Google Ads campaign against six rules and split into add, exclude, or watch buckets. Read-only analysis returns candidates with metrics and reasons, using CPA from campaign or actuals.

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
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.
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.
Behavior5/5

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

No annotations provided, so the description carries full burden. It declares read-only behavior, explains target_cpa resolution path (explicit, bidding strategy, actual, none), routing of new terms to watch, and that CPA-gated rules are skipped if target_cpa cannot be resolved. This is thorough.

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 detailed but every sentence adds value. It front-loads the main purpose and output structure, then explains parameters and behavior. No wasted words.

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 fully describes the return object and all fields. It covers all aspects for a complex tool with 4 parameters, making it complete.

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?

Schema coverage is 100%, and the description adds significant meaning: fallback for customer_id, how to obtain campaign_id, default period tuning, and target_cpa fallback logic including exclusion rule #4. This goes well beyond the schema.

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 clearly states the tool scores search terms against six hardcoded rules and splits them into buckets. It specifies the output structure and distinguishes itself from sibling tools like 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?

The description explicitly notes the tool is read-only, explains default period, and contrasts with siblings for keyword/N-gram overlap stats or raw query logs, providing clear when-to-use guidance.

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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