google_ads_negative_keywords_suggest

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

With no annotations provided, the description bears the full burden of behavioral disclosure. It clearly states 'Read-only — suggestions are not applied', describes the output (text, match_type, spend, conversions, rationale), and explains the logic (relative to target CPA, with an example rationale). This provides good transparency for a suggestion tool.

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, each serving a distinct purpose: function, read-only nature, and usage guidance. It is concise, front-loaded with the most important information, and contains no redundant or irrelevant details.

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?

Given the tool's complexity (5 parameters, no output schema, no annotations), the description is fairly complete. It explains the purpose, output fields (text, match_type, spend, conversions, rationale), read-only behavior, and workflow integration. It could optionally provide more detail on output format, but the listed fields suffice.

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 coverage is 100%, so baseline is 3. The description does not add any parameter-specific semantics beyond what the schema provides; it focuses on the tool's overall behavior. The schema already fully describes each parameter's purpose and optional/required status.

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: it analyses search-term performance and returns suggested negative keywords based on target CPA. It specifies the verb 'analyses' and 'returns', the resource 'negative keywords', and the condition 'waste spend relative to a target CPA'. It distinguishes itself from sibling tools like google_ads_negative_keywords_add by noting that suggestions are not applied and directing users to those tools for materialization.

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 explicitly guides usage: 'Use google_ads_negative_keywords_add / add_to_ad_group to materialize the ones you want after operator review.' It also states the tool is read-only and suggests operator review. While it doesn't explicitly list when NOT to use, the guidance is clear and actionable.

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