Company Fundamentals

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

Annotations already communicate readOnlyHint/openWorldHint/idempotentHint, so the safety profile is known. The description adds that the call bundles a live quote and is a headline-level summary, which is useful but does not disclose edge-case behavior, data limitations, or response size. This is acceptable given the strong annotation coverage.

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 two tight sentences: the first front-loads exactly what data the user gets, and the second gives the query intent. No filler or redundant restatement of the tool name.

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?

This is a simple one-parameter, read-only tool with an output schema and strong annotations. The description covers scope, included metrics, target audience, and typical question types, so nothing essential is missing for an agent to select and call 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 coverage is 100% and the ticker parameter is already described as a US stock symbol with an example. The description's mention of a US stock adds no new meaning beyond the schema, so the baseline score of 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 clearly states the tool returns headline fundamentals for a US stock and enumerates the specific metrics included (revenue, EBITDA, margins, EV/EBITDA, net debt, free cash flow, live quote). This precise inventory distinguishes it from siblings like get_quote or get_key_metrics without needing to open schemas.

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 concrete usage context: "Best first stop for 'how is <company> doing / what are its fundamentals / is it cheap' questions." This clearly implies when to use it, though it stops short of explicitly naming alternatives or stating when not to use it.

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