comparativo_votacoes_bancadas

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'incluindo disciplina partidária' (including party discipline), which adds some context about what the tool calculates. However, it doesn't describe the return format (e.g., structured data, summary statistics), potential limitations (e.g., data availability, error handling), or performance aspects (e.g., response time, data freshness), leaving significant gaps for a tool with analytical functions.

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, efficient sentence in Portuguese that directly states the tool's purpose without unnecessary words. It is front-loaded with the core function ('Compara como diferentes bancadas partidárias votaram') and adds a key feature ('incluindo disciplina partidária') concisely. There is no redundancy or fluff, making it easy to parse quickly.

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 tool with 3 parameters, no annotations, and no output schema, the description is moderately complete. It clearly defines the tool's purpose and hints at behavioral aspects (party discipline analysis), but lacks details on output structure, error conditions, or usage constraints. Given the analytical nature and absence of structured behavioral data, more context would be beneficial, but it meets a minimum viable level by explaining what the tool does.

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%, with clear descriptions for all three parameters: 'idVotacao' (vote ID), 'incluirOrientacoes' (include leadership guidance and party discipline calculation), and 'incluirAusentes' (include absent deputies in the count). The description adds minimal value beyond the schema by implying the tool uses 'idVotacao' and mentions 'disciplina partidária' (party discipline), which loosely relates to 'incluirOrientacoes'. Given the high schema coverage, a baseline score of 3 is appropriate.

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 clearly states the tool's purpose: 'Compara como diferentes bancadas partidárias votaram em uma votação específica, incluindo disciplina partidária' (Compares how different party blocs voted in a specific vote, including party discipline). It specifies the verb (compare), resource (party bloc votes), and scope (specific vote with party discipline analysis), distinguishing it from sibling tools like 'votos_votacao' (individual votes) or 'orientacoes_votacao' (voting guidance).

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 implies usage context through 'em uma votação específica' (in a specific vote), suggesting it should be used when analyzing voting patterns by party blocs for a particular vote. However, it doesn't explicitly state when to use this tool versus alternatives like 'votos_votacao' (which might show individual votes) or 'detalhar_votacao' (which might provide vote details), nor does it mention prerequisites or exclusions.

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