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

With no annotations, the description carries the transparency burden and does disclose meaningful behavior: the simulation is deterministic and it enumerates returned verdict, breakeven year/month, asset advantage, first-month costs, annual snapshots, and a dashboard link. However, it is silent on assumptions, defaults, and limitations, and its claim of accepting a 'cenarios' field is unsupported by the empty input 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 dense sentence that front-loads the core purpose before covering accepted input modes and return values. It contains no obvious filler, though the long output enumeration could be structured as a list for easier parsing.

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?

No output schema or annotations exist, so the description must carry input, output, and usage context. It lists outputs well but fails to document the actual callable parameters, the scenario format, or when to choose this over related siblings such as sensitivity_analysis and simulate_tr_evolution, leaving a material invocation gap.

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 description adds qualitative parameter information — 'parâmetros simples', multiple scenarios (pessimista/base/otimista), and a field named 'cenarios' — but the input schema declares zero properties. This mismatch makes it impossible for an agent to construct a valid invocation from the provided definition, and no types, shapes, or required fields are specified.

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 opens with a specific action and object: 'Executa a simulação determinística comprar vs alugar para um imóvel.' It clearly conveys the resource and highlights the deterministic nature, distinguishing it from generic simulation tools. It does not explicitly name alternatives, but the purpose is unambiguous.

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 intended use is implied by the tool name and the opening sentence: use it to model buy-versus-rent outcomes. However, there is no explicit 'use when' or 'do not use when' guidance, and no reference to nearby siblings like sensitivity_analysis, so the agent must infer selection criteria.

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