get_revenue_segments

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

No annotations are provided, so the description carries full burden. It discloses data source (annual report PDFs) and currency (NZD thousands), but lacks details on limitations (e.g., year range, company eligibility, error behavior). The transparency is adequate but not comprehensive.

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 brief, with the first sentence stating the core purpose. Subsequent sentences detail return data, usage prompts, and examples. It is front-loaded and efficient, with no redundant information.

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 absence of an output schema, the description should clarify the response structure. It mentions data fields but not whether the response is an array or how segments are organized. The description is sufficient for basic use but leaves ambiguity about the exact return format.

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 adds context by providing example tickers (FPH, MEL, FBU) and explaining that type can be operating, geographic, or product. It does not add significant new meaning beyond the schema, but reinforces the parameter purposes.

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 it returns revenue segment breakdown for NZX companies, lists the types of segments (operating, geographic, product) and data fields (revenue, profit, assets, percentage). It differentiates from sibling tools like get_earnings or get_financials by focusing specifically on segment data, though it does not explicitly name siblings.

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 provides example user queries ('revenue breakdown for [company]', 'business segments') that guide when to use this tool. It does not explicitly state when not to use it or compare to alternatives, but the examples give clear context for appropriate usage.

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