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google_ads_negative_keywords_suggest

Analyzes search term performance and returns negative keyword suggestions that exceed target CPA, reducing wasted spend. Candidates include text, match type, spend, conversions, and rationale for operator review.

Instructions

Analyses recent search-term performance and returns suggested negative keywords that waste spend relative to a target CPA. Returns candidates with text, suggested match_type, spend, conversions, and rationale (e.g. 'spend > 3x target CPA, 0 conversions'). Read-only — suggestions are not applied. Use google_ads_negative_keywords_add / add_to_ad_group to materialize the ones you want after operator review.

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 whose search terms are analysed.
periodNoAnalysis window. Accepts Google Ads predefined ranges ('LAST_7_DAYS', 'LAST_14_DAYS', 'LAST_30_DAYS' — default 'LAST_30_DAYS') or explicit 'YYYY-MM-DD..YYYY-MM-DD'.
target_cpaNoTarget CPA in the account's currency. Search terms whose effective CPA exceeds this are flagged. If omitted, the campaign's configured target_cpa is used when available.
ad_group_idNoRestrict analysis to a single ad group. Omit to analyse the whole campaign.
Behavior5/5

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

Declares read-only nature, describes output fields (text, match_type, spend, conversions, rationale), and explains the rationale logic. No annotations provided, so description fully covers behavior. No contradictions.

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?

Two main sentences plus a brief follow-up. Front-loaded with purpose and key details. No filler or redundancy.

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?

Covers purpose, input parameters, output format, and usage direction. No output schema, but description explains return fields. Missing details like pagination or error handling, but acceptable for a suggestion tool.

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% with individual parameter descriptions. The description adds meaning by explaining how parameters like target_cpa and period relate to the analysis logic (e.g., flagging terms exceeding target CPA). This goes beyond the schema's basic descriptions.

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 'Analyses recent search-term performance and returns suggested negative keywords that waste spend relative to a target CPA.' It specifies the verb (analyse, suggest), resource (search terms, negative keywords), and distinguishes from siblings like add tools.

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 — suggestions are not applied' and directs to materialize suggestions using google_ads_negative_keywords_add / add_to_ad_group. Provides clear when-to-use and alternatives.

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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