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

With no annotations provided, the description carries the behavioral transparency burden. It usefully discloses that data comes from official Banco Central SGS series and that aggregation exists to reduce volume, which adds context beyond the schema. It does not describe edge cases, response shape, or ordering, but for a read-only query tool the disclosed behavior is reasonably complete.

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 compact: three short sentences covering purpose, authoritative source, and key capabilities. It is front-loaded with the most important information and contains 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?

For a rate-history lookup, the description plus fully documented schema gives an agent enough to select metrics, date ranges, aggregation, and limits. There is no output schema and no description of the returned point structure, but the return concept is simple enough that this is a minor gap. The missing explicit routing among related rate/minimum-wage siblings is the main completeness weakness.

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 100%, so the input schema already documents metric, from, to, aggregate, and limit with enums and defaults. The description adds high-level context by mentioning date filtering and monthly/yearly aggregation but does not provide meaningful semantics beyond the schema. Baseline 3 is appropriate because the schema carries the parameter-documentation load.

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 verb and resource — "Retorna série histórica de uma taxa econômica brasileira" — and lists concrete examples like Selic, CDI, IPCA, and dollar. It is clearly a historical-series lookup, which implicitly separates it from get_current_rates, but it never explicitly names an alternative or states what it is not. This is clear but lacks direct sibling differentiation.

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?

Usage context is implied: an agent can infer to use this tool when historical Brazilian economic rate data is needed, especially with date-range filtering or aggregation. However, there is no explicit guidance about when not to use it or which sibling to prefer, such as get_current_rates for current values or get_minimum_wage_history for wage history. The guidance is functional but not exclusionary.

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