Estatísticas agrupadas

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

With no annotations, the description carries the full burden. It discloses the aggregation semantics and the two metrics counted per group, but it does not explicitly state that the operation is read-only, nor does it describe permissions, side effects, or output structure.

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 definition is a single front-loaded sentence with no wasted words. It efficiently states the aggregation behavior and the metrics before listing grouping dimensions.

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 9-parameter aggregation tool with no annotations and no output schema, the description is adequate but incomplete. It explains the core aggregation and metrics, but it lacks usage guidance versus siblings and does not describe the return shape beyond raw counts per group.

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 high at 89%, so the schema already documents most parameters. The description maps several grouping choices (state, party, office, social network, day), but it omits the situacao grouping option and does not explain the filter parameters.

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 uses a specific verb and resource: it aggregates counts by group and names the metrics (politicians who cited/requested vote and posts citing Flávio). It is clear what the tool computes, but it does not explicitly distinguish itself from siblings such as ranking or resumo_geral.

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?

There is no explicit guidance on when to use this tool versus alternatives like ranking or resumo_geral. The grouping dimensions imply a grouped-statistics use case, but the description provides no exclusions or routing advice.

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