news_coverage

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

With no annotations, the description carries full responsibility for behavioral disclosure, and it delivers: it explains the data source (Google News), the capped result set, how 'total' and 'last_30_days' should be interpreted as rough gauges rather than exact counts, the newest-first ordering, and the use of Google News' `when:` filter. This is strong transparency beyond the bare schema.

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 well-structured with a clear lead sentence, an Args section, and a Returns section. It is somewhat longer than strictly necessary, but the extra details (cap caveat, newest first, rough attention gauge) are genuinely useful and not redundant 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?

Even with no output schema, the description fully specifies the return structure, field semantics, and important caveats about counts. It also covers setup expectations ('No setup needed') and the tool's intended analytical uses, so an agent has enough context to select and invoke it correctly.

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 0%, so the description must compensate, and it does thoroughly: query is defined as search terms, geo as an ISO country code with examples, recent as a time range with the underlying filter explained, and limit as a max-headline count with a note about Google's ~100 cap. It adds meaning and usage guidance that the schema alone does not provide.

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 opens with a specific verb and resource: 'Recent news coverage from Google News' and immediately frames the purpose ('is the press writing about this, and what angle are they taking?'). The use cases (funding rounds, regulation, launches, attention trends) make it clear what this tool does and how it differs from the sibling tools like related_topics or interest_over_time.

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 gives clear context for when to use the tool ('Usable for spotting funding rounds, regulation, launches, and whether a topic is getting more or less attention') and notes 'No setup needed.' It does not explicitly name alternatives or say when not to use it, but the stated use cases are sufficient orientation.

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