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

With no annotations, the description carries full responsibility for behavioral disclosure. It reveals that the tool returns historical data, but does not state the output format, granularity (annual/monthly), whether 2026 is a projection, or how the data is structured. This is a meaningful gap for a data-retrieval tool with no output schema.

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 a single, front-loaded sentence with no filler. Every word contributes: it names the verb, the resource, and the complete date range efficiently.

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 zero-parameter read-only tool, the description is largely complete and sufficient for invocation. The main missing elements are the response structure and clarification about the 2026 endpoint, which could matter if the data is projected or partially complete.

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 tool has zero parameters, so per the rubric the baseline is 4. The description does not need to explain parameter meanings, and the empty input schema already confirms no arguments are required.

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 states a specific action ('Retorna histórico'), a precise resource ('salário mínimo brasileiro'), and an explicit period ('1994 (Plano Real) até 2026'). This clearly distinguishes it from sibling tools like get_current_rates, get_average_salary, and calculate_real_salary.

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 usage context is implied: an agent needing Brazilian minimum wage history should call this tool. However, there is no explicit guidance on when not to use it or which sibling tool to prefer for current wages, average wages, or wage calculations.

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