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google_ads_keywords_cross_adgroup_duplicates

Identify duplicate keywords across ad groups in a Google Ads campaign, with per-ad-group stats and a consolidation recommendation to reduce auction competition and improve quality score.

Instructions

Finds the same text+match_type keyword appearing across multiple ad groups in a campaign. Returns groups of duplicate criteria with per-ad-group spend, conversions, and quality score, plus a consolidation recommendation (which copy to keep, which to pause/remove). Read-only. Duplicates compete in the auction and hurt aggregate quality score — run this before a keyword restructuring sprint.

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 to scan for duplicates.
periodNoAnalysis window used to compute per-copy spend and conversions. Accepts 'LAST_7_DAYS', 'LAST_14_DAYS', 'LAST_30_DAYS' (default), or 'YYYY-MM-DD..YYYY-MM-DD'.
Behavior4/5

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

The description declares 'Read-only', making its non-destructive nature clear. It also explains that duplicates 'compete in the auction and hurt aggregate quality score', adding useful behavioral context. Without annotations, this covers the essential transparency well, though it could mention potential performance impacts or output size.

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 concise with 3-4 sentences, front-loading the main purpose. Every sentence adds value: what it does, what it returns, that it's read-only, and when to use it. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (3 parameters, no output schema), the description adequately covers the purpose, return content, and usage context. It explains the output (groups with metrics and recommendation) but does not detail the exact structure or format, which is acceptable without an output schema.

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 covers all three parameters with 100% description coverage. The tool description adds no new semantic details to the parameters beyond what is already in the schema, so it meets the baseline with no additional value.

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 specifies the verb 'Finds' and the resource 'duplicate keywords across ad groups'. It details the exact criteria (same text+match_type) and the output (groups with spend, conversions, quality score, consolidation recommendation). This distinctly sets it apart from sibling keyword tools like add, list, or remove.

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?

The description states it is 'Read-only' and recommends using it 'before a keyword restructuring sprint', providing clear context on when to use. However, it does not explicitly compare with similar analysis tools (e.g., audit, diagnose) or indicate when not to use it.

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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