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senado_ecidadania_ideias_populares

Retrieve top citizen-supported legislative ideas from Brazil's e-Cidadania platform to monitor public opinion and identify trending proposals.

Instructions

Retorna as ideias legislativas mais apoiadas pelos cidadãos.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limiteNoNúmero máximo de resultados
apenasAbertasNoApenas ideias com apoiamento aberto
Behavior2/5

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 states the tool returns data ('retorna'), implying a read-only operation, but doesn't clarify aspects like rate limits, authentication needs, or what 'mais apoiadas' means in practice (e.g., sorted by vote count). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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

Conciseness4/5

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core functionality, making it easy to parse. However, it could be slightly more structured by explicitly mentioning the parameters or usage context, but it's appropriately sized for its purpose.

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 (2 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It covers the basic purpose but lacks behavioral details (e.g., sorting order, data format) and usage guidelines. Without an output schema, it doesn't explain return values, which is a minor issue since the purpose implies a list of ideas. Overall, it's minimally viable but 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 schema description coverage is 100%, with both parameters ('limite' and 'apenasAbertas') well-documented in the schema. The description doesn't add any parameter-specific information beyond what the schema provides, such as explaining how 'apenasAbertas' affects the results. According to the rules, with high schema coverage (>80%), the baseline is 3 even without param info in the description.

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 tool's purpose: 'Retorna as ideias legislativas mais apoiadas pelos cidadãos' (Returns the legislative ideas most supported by citizens). It specifies the verb ('retorna') and resource ('ideias legislativas'), and adds a qualifier ('mais apoiadas pelos cidadãos'). However, it doesn't explicitly differentiate from sibling tools like 'senado_ecidadania_listar_ideias', which might list all ideas without filtering by popularity.

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 sibling tools such as 'senado_ecidadania_listar_ideias' (which might list all ideas) or 'senado_ecidadania_obter_ideia' (which might retrieve a specific idea), leaving the agent to infer usage based on the name alone. There's no explicit when/when-not or alternative recommendations.

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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