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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description's 'Read-only: it changes nothing' reinforces rather than carries the burden. It adds genuinely new behavior detail the annotations cannot convey: that adding negatives requires another tool, that the output is rendered as a visual card, and that the default window is the last 30 days.

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?

Four short sentences, front-loaded with the use case before the return payload and the read-only constraint. Nothing is redundant with the title, and every clause carries information an agent would act on.

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?

With no output schema, the description properly compensates by listing the returned sections and the suggested-negative output, and it flags the card rendering and default period. It could go slightly further on how folder and account interact or on result volume, but nothing critical for correct invocation is missing.

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 every parameter including the detail enum, folder-vs-account choice, and date_range default is already documented in structured data. The description only restates the default period (last 30 days), which the schema also states, so it adds essentially no meaning beyond the schema. Baseline 3 applies.

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 names a specific analytical outcome (Google Ads money being wasted) and enumerates exactly what is returned: campaigns, keywords and search terms with zero conversions, total wasted amount, share of total spend, and suggested negative keywords. This is clearly distinguishable from sibling read tools like google_ads_search_terms or google_ads_keywords, which surface data without the zero-conversion/spend framing.

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?

It gives an explicit trigger ('Use this when the user asks where Google Ads money is being wasted') and routes the write action away by noting that adding negatives is a separate tool. It stops short of naming a specific sibling alternative or stating when-not to use it (e.g. versus a general performance report), so it is strong but not exhaustive.

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