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

Annotations already declare readOnly, idempotent, non-destructive and non-open-world, so the safety profile is covered. The description adds genuine behavioral context beyond them: the list-vs-full-text duality and that the content is free ('Gratuito'), which hints at no cost constraint.

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?

Two compact sentences with zero filler, and the core purpose plus both modes are front-loaded. Every clause adds 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?

For a single-parameter lookup with no output schema, the description fully covers what an agent needs: what it returns in each mode and a sample input. Nothing essential is missing.

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 well: it explains that 'nome' selects a specific page and gives a concrete example ('roic') alongside the default behavior when it is omitted. Only the exact valid page names are left unspecified.

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?

States a specific resource ('metodologia pública dos indicadores') clearly, so an agent understands this returns documentation rather than data. It distinguishes itself implicitly from the numeric-data siblings (dividendos, precos, multiplos), though it never names an alternative explicitly.

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?

Describes the two invocation modes concretely: without the argument it lists the available pages, with a name it returns the full text. This is clear context on how to call it, but there is no explicit statement of when to prefer it over sibling tools or any exclusions.

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