multiplos

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals the critical behavioral choice of using the first trading session after publication date to eliminate look-ahead, and it details authentication via the `chave_api` parameter, including the fallback to an environment variable. This goes well beyond the schema and covers key safety and data-integrity aspects, though it does not explicitly state read-only nature or error handling.

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 front-loaded, stating the returned data first, and then explains the important point-in-time methodology that justifies the tool's use. The parameter section is clear and directly addresses the API key ambiguity. While slightly verbose due to the methodology explanation, that length is justified given the conceptual subtlety and its importance for correct usage in backtesting contexts.

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?

The description covers the tool's purpose, the exact financial metrics returned, the crucial look-ahead-free price methodology, and both parameters with examples and fallback behavior. Although there is no output schema and the description does not specify the response format (e.g., array vs. object), the data content is sufficiently described for an agent to invoke the tool correctly. The API key handling is fully explained, addressing a common pitfall.

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?

The schema offers no parameter descriptions (0% coverage), so the description must compensate. It thoroughly defines `ticker` with concrete B3 examples and a reference to `listar_empresas`, and fully explains `chave_api` including optionality for WEGE3, the requirement for other tickers, and the empty-string fallback to the environment variable. This completely compensates for the missing schema documentation.

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's function: returning point-in-time valuation multiples (P/L, P/VP, EV/EBITDA) per fiscal year and P/L TTM per quarter for a B3 company. It includes the specific verb 'Devolve' and resource, and naturally distinguishes itself from siblings like `indicadores_anuais` by emphasizing the look-ahead-free methodology.

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 implicit usage context by highlighting the point-in-time methodology as suitable for backtests and instructs users to consult `listar_empresas` for ticker formatting. However, it does not explicitly compare this tool to sibling tools like `indicadores_anuais` or `fatos_contabeis`, nor does it state when to avoid this tool. The guidance on API key usage is explicit but tool-selection guidance is weak.

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