google_ads_negative_keywords_suggest

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

With no annotations provided, the description carries the full burden. It explicitly discloses 'Read-only — suggestions are not applied,' which is critical behavioral context. It also details the return fields (text, suggested match_type, spend, conversions, rationale) and gives an example rationale. Minor gaps: no mention of rate limits or permissions, but given the non-mutating nature and clear return spec, this is very good.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with the core purpose, followed by output details and next-step guidance. Every sentence is informative with no redundancy or filler.

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

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

For a read-only suggestion tool with no annotations and no output schema, the description is thorough. It covers input context, output content, safety profile, and follow-up actions. The period parameter and default behavior are already in the schema, so the description compensates well for missing structured fields.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds value by explaining the semantic meaning of the target_cpa parameter ('waste spend relative to a target CPA') and illustrating the rationale format ('spend > 3x target CPA, 0 conversions'), which goes beyond the schema's field descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Analyses recent search-term performance and returns suggested negative keywords that waste spend relative to a target CPA.' It uses a specific verb ('Analyses... returns') and specifies the resource (negative keywords), making it distinct from sibling tools like google_ads_keywords_suggest and google_ads_negative_keywords_add.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: use this to identify wasteful negative keywords, and explicitly notes it is read-only with suggestions, directing users to google_ads_negative_keywords_add / add_to_ad_group to apply them. This clearly distinguishes when to use this tool vs alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.