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

The description adds useful behavioral context beyond annotations: it discloses that results are a 'sample,' that 'top stories remain observed sample types without expansion,' and that 'relative publication labels do not replace timestamps.' These details help set expectations about data completeness and publication evidence. It does not address limits or read-only behavior, but annotations already provide openWorldHint and readOnlyHint.

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 short and front-loaded with the news_search sample context, but its phrasing is dense and jargon-heavy ('observed sample types without expansion'), which reduces clarity. Every sentence is relevant but not optimally structured for quick comprehension.

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 four parameters, only 25% schema description coverage, no output schema, and minimal annotations, the description is not complete enough. It does not explain what a result contains, how the limit parameter behaves, or what 'publication evidence' means in practice, leaving the agent with material gaps.

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 only 25%, and the description does not explain the keyword, limit, market, or language parameters beyond the fixed 'US English' phrasing. It implicitly aligns with the market and language constants but adds no meaning for the keyword format, limit maximum, or how these parameters affect results.

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 identifies the resource as a 'Google US English news_search sample with publication evidence,' which points toward Google News search results. However, it uses a noun phrase rather than a clear verb and does not explicitly state that it searches or retrieves news results, leaving the core action vague.

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?

There is no guidance on when to use this tool versus alternatives such as nexscope_seo_serp, nexscope_web_search, or other Google result tools. It also omits any prerequisites or exclusions, so the agent must infer usage from the name and title alone.

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