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senado_obter_votacao

Retrieve detailed voting records from the Brazilian Federal Senate, including individual senator votes, to analyze legislative decisions and track political positions.

Instructions

Obtém detalhes de uma votação específica, incluindo votos nominais de cada senador.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codigoVotacaoYesCódigo único da votação
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves details including nominal votes, which implies a read-only operation, but doesn't explicitly confirm this or mention other behavioral traits like rate limits, authentication needs, error conditions, or response format. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('Obtém detalhes de uma votação específica') and adds valuable context ('incluindo votos nominais de cada senador'). There's no wasted verbiage, and every word contributes to understanding the tool's function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (one required parameter, no nested objects) and high schema coverage (100%), the description is minimally adequate. However, with no annotations and no output schema, it fails to disclose behavioral traits or return format details. The description covers the basic 'what' but leaves gaps in 'how' and 'what you get back,' making it incomplete for optimal agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description doesn't add any parameter-specific information beyond what's in the schema, which has 100% coverage and clearly documents 'codigoVotacao' as a unique vote code with a positive integer constraint. Since the schema fully describes the single parameter, the baseline score of 3 is appropriate—the description doesn't compensate but doesn't need to given the comprehensive schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Obtém detalhes' - Gets details) and resource ('de uma votação específica' - of a specific vote), making the purpose immediately understandable. It distinguishes from siblings like 'senado_listar_votacoes' (which lists votes) by specifying it retrieves details for a specific vote. However, it doesn't explicitly contrast with 'senado_votacoes_senador' or 'senado_votos_materia', which might have overlapping functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a vote code from another tool like 'senado_listar_votacoes'), nor does it contrast with similar tools like 'senado_votacoes_senador' (votes by senator) or 'senado_votos_materia' (votes on a matter). The agent must infer usage from the description alone.

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

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