ddd

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states what is returned and does not mention that this is a read-only operation, whether authentication is required, what happens on invalid input, or any other behavioral traits. This is a significant gap for a tool with zero annotation coverage.

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?

Two short sentences with no filler. The main purpose is stated first, and the outcome is described immediately. Every word contributes to understanding the tool's function. This is a model of concise, front-loaded documentation.

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?

For a simple single-parameter lookup tool, the description is nearly complete: it identifies the input, the operation, and the output. The absence of an output schema is partially mitigated by the explicit statement of what is returned. However, it does not mention error behavior or any edge cases (e.g., invalid DDD), which an agent might encounter. Still, the core information needed to invoke it correctly is present.

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 provides no description for the parameter 'ddd' (0% coverage), so the description must compensate. It adds that the parameter is a two-digit area code, which gives meaningful semantic context beyond the bare schema property. However, it does not specify format constraints (e.g., exactly two digits, numeric only) or error handling for malformed input, so compensation is partial.

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 verb (look up), the resource (Brazilian phone area code / DDD), and the expected output (state and list of cities). It is specific enough to differentiate from sibling tools like cep, cnpj, banks, etc., which operate on entirely different data domains.

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?

The description conveys its use case implicitly: querying a Brazilian DDD to get state and cities. It does not explicitly mention alternatives or exclusions, but the context of sibling tools makes it clear that this is the dedicated DDD resolver. There are no pitfalls or prerequisites to warn about, so the guidance is adequate.

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