Obter métricas de negócio

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

With no annotations, the description carries the full burden. It discloses that the tool requires prior run_tests execution and optionally reads qa-lab-flows.json, which is useful behavioral context. However, it does not explicitly state whether the operation is read-only or whether there are any side effects, leaving some ambiguity.

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 two sentences, front-loaded with the returned metrics and followed by dependencies. Every sentence adds value and there is no redundant information.

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?

The description covers the tool's prerequisites and optional input file, while the output schema covers return values. It gives enough context to understand how the tool depends on other processes, making it complete for its complexity.

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?

The schema fully describes the single optional 'period' parameter with an enum and default, so the description does not need to add more. There is no additional parameter semantics in the description, but the baseline is adequate due to 100% schema coverage.

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: it returns specific business metrics (time to bug, cost per defect, coverage per flow). The verb 'Retorna' specifies the action, and the metric list distinguishes it from sibling analysis tools.

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?

It provides clear usage context by stating the prerequisite that run_tests must have been executed, and optionally the qa-lab-flows.json file. It does not explicitly mention alternatives or when-not-to-use scenarios, but the dependency on run_tests makes the intended context clear.

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