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Roteador de domínio

eng_route

Directs natural language tasks to the appropriate engineering domain—work, QA, time, investigation, knowledge, or reporting—for streamlined workflow management.

Instructions

Encaminha uma tarefa em linguagem natural para o domínio certo: work, qa, time, investigation, knowledge ou reporting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesO que você quer fazer, em linguagem natural.
Behavior2/5

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

With no annotations, the description carries the full burden of disclosing behavior. It states the tool 'routes' a task, but it is ambiguous whether it actually executes the task in the target domain or merely identifies/returns the domain. There is no mention of side effects, whether it is a read-only operation, or what the output looks like. This ambiguity is a significant gap for a mutating-capable tool.

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, front-loaded sentence that states the purpose and enumerates the domains without any redundant words. It is concise and effectively structured for quick comprehension.

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

Completeness2/5

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

Despite having only one parameter and no output schema, the description leaves out critical operational details. An agent needs to know what happens after routing: does the tool return a domain label, an instruction set, or does it invoke another tool? Without annotations or an output schema, this ambiguity means the description is not complete enough for the agent to use the tool correctly.

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

Parameters4/5

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

The input schema already documents the 'task' parameter at 100% coverage. The description adds value by listing the possible domains, giving the agent a concrete sense of what the task string will be classified into, which goes beyond the schema's minimal description.

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 clearly states the tool's function: routing a natural language task to the correct domain, and explicitly enumerates the six possible domains (work, qa, time, investigation, knowledge, reporting). This is a specific verb+resource with clear scope, and it distinguishes itself from sibling tools which are domain-specific actions.

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?

The description implicitly conveys when to use this tool: when you have a natural language task and need it routed to the appropriate domain. It does not explicitly mention alternatives (like using domain-specific tools directly) or exclusions, but the context of sibling tools makes the use case clear. No conflicting guidance is provided.

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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