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planejar_consulta

Creates an execution plan for complex queries that need multiple API calls. It analyzes your question, identifies which tools to use, and sequences dependent steps.

Instructions

Cria um plano de execução para consultas complexas.

Analisa a pergunta, identifica quais tools usar, em que ordem, e quais etapas dependem de outras. Útil para consultas que precisam de múltiplas chamadas combinadas.

Args: query: Pergunta em linguagem natural (ex: "compare os gastos do deputado X com a média").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It explains the tool's behavior in detail: it analyzes the question, identifies tools, order, and dependencies, which implies it only creates a plan and does not execute it. This is transparent and non-misleading.

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 concise and front-loaded, with a one-sentence purpose, a brief but informative explanation, and an Args section. Every sentence adds value, and the example is helpful without verbosity.

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

Completeness5/5

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

Given the single parameter, presence of an output schema, and no annotations, the description covers the purpose, usage context, parameter meaning, and provides an example. It is sufficient for an agent to select and invoke this tool correctly.

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

Parameters5/5

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

The input schema only declares 'query' as a string with no description. The description compensates by explaining it as a natural language question and providing a concrete example, which fully disambiguates the parameter.

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

Purpose5/5

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

The description states a specific action ('cria um plano de execução') for complex queries, and, further details explain it analyzes the question and determines tool order and dependencies. This clearly distinguishes it from sibling tools by emphasizing ordering and dependency analysis beyond mere tool recommendation.

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

Usage Guidelines4/5

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

It explicitly states it is useful for queries that need multiple combined calls, which tells an agent when to use it. However, it does not mention when not to use it or explicitly compare it to alternatives like recomendar_tools, so it lacks exclusions.

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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