bcb_series_populares

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

Besides the annotations, the description discloses meaningful details: it is a local catalog with no network call, the response shape changes by filtering, the number of series, and the provenance semantics of `fonteNome` ('portal' vs 'medido'). This goes well beyond the annotations and significantly helps the agent reason about data reliability.

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?

Each sentence adds substantive information: purpose, use cases, exclusions, return shape, local nature, and provenance. The item is longer than average, but the complexity of the catalog and its edge cases warrant it; there is no filler or redundancy.

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 one-optional-parameter catalog tool, the description covers use cases, output structure, data-source caveats, and important exclusions not discoverable from the schema. Combined with the existing output schema, this gives the agent a complete picture for correct invocation.

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 single optional `categoria` parameter is already fully described in the schema, so the description doesn't add syntax-level info. However, it does add key semantics: filtering by categoria changes return from a grouped object to a flat array, and it warns that Focus expectations are excluded. That extra context justifies a score above baseline, even with 100% schema coverage.

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 strong verb and resource: 'Lista o catálogo interno curado de 139 séries econômicas do BCB com seus códigos', and further details the grouping by category and optional filter. It also explicitly distinguishes the tool from siblings like bcb_buscar_serie and bcb_focus_expectativas, making its purpose unmistakable.

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?

It provides explicit 'Quando usar' and 'Quando NÃO usar' sections, naming bcb_buscar_serie for keyword searches and bcb_focus_expectativas for Focus expectations. This gives the agent concrete guidance on when to select or avoid this tool compared to its siblings.

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