Brazil Historical Series

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

With no annotations provided, the description carries the full behavioral burden. It discloses the return shape (every data point plus min, max, average, first, last, change), the accepted series values, the expected ISO date format, and the data source. It does not discuss edge cases like missing dates or rate limits, but it provides solid behavioral context.

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 well-structured and front-loaded: it opens with the core action, then lists series values, date format, return contents, use cases, and source. Every sentence adds useful information, and the formatting with backticks and parentheticals improves scanability without wasting space.

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?

Given the tool's low complexity (3 required string parameters) and the presence of an output schema, the description covers the essential information an agent needs: valid series values, date format, what the response includes, and the data source. It is sufficient for correct invocation and expectation-setting.

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. It fully explains the possible values for 'series' (SELIC, CDI, IPCA, USD/PTAX) and clarifies that dates use ISO format YYYY-MM-DD. It does not elaborate on range constraints or inclusive/exclusive date boundaries, but it provides meaningful semantics beyond the bare schema.

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 ('Get a historical time series') and a specific resource ('a Brazilian indicator over a date range'), and even enumerates the exact series supported. It is clear and not a tautology, though it does not explicitly differentiate itself from related siblings like brazil_market_rates or colombia_trm_history.

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 gives clear usage context by naming example use cases ('trend analysis, indexation, and FX backtesting') and specifying the source (Banco Central do Brasil). However, it does not explicitly state when not to use it or how it compares to sibling tools such as brazil_market_rates or currency_convert.

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