segment_revenue

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

Beyond the readOnlyHint and openWorldHint annotations, the description adds valuable behavioral detail: it does not fabricate splits when unreported, it is pattern-matched from narrative text, and users should verify labeled values against the source URL. This gives an agent an accurate model of the tool's reliability and limitations.

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 earning its place: the first defines the core purpose, the second explains the empty-result behavior, and the third warns about verification. The main function is front-loaded and there is no 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 tool with no output schema, the description conveys the key return behavior (mentions[]), the anti-fabrication guarantee, and the need to verify against source URLs. It does not fully describe the output structure or parameter semantics, but it gives enough context for an agent to call the tool and interpret basic results.

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%, and the description provides essentially no parameter-level guidance. It mentions 'a company' and 'source URL' but does not explain the context object, required company field, optional sector/country/date fields, or how the input affects the search. The description fails to compensate for the low schema coverage.

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 uses a specific verb and resource: it 'Finds business-segment or channel revenue mix' and gives concrete examples like Online vs Offline and product-line splits. It also clarifies that it only returns results when a company actually discloses such a split, which clearly distinguishes it from generic financial or operating metric tools.

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 clearly states when the tool applies: when a company discloses segment revenue in an investor presentation, annual report, or press coverage. It also provides guidance for the negative case by noting that an empty mentions[] is returned rather than a fabricated split. It does not explicitly name alternatives, but the scope is clear enough for selection among sibling tools.

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