buscar_conteudo

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals several important traits: accent normalization by the server, partial matching for multi-word searches, the `ano` filter being applied locally (not server-side), and the fact that results include `uuid_ato` instead of full text. This goes beyond a simple 'search' description and helps the agent anticipate behavior.

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 well-structured and concise. It opens with a clear purpose, then uses a compact list for arguments, and ends with a coverage note. Every sentence provides valuable information without redundancy. It is appropriately sized for the tool's complexity.

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?

Despite having no output schema or annotations, the description covers essential context: what the tool does, what each parameter means, what the results contain (uuid_ato, palavras_encontradas, total_encontrado), how to proceed with `ler_ato`, and the coverage scope. This is complete enough for an agent to select and invoke the tool correctly.

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 input schema provides only types and defaults (0% description coverage). The description compensates fully by explaining each parameter: `termo` (keywords, accent normalization, partial matching), `ano` (year restriction, local filter), and `limite` (max results, default 20, with `total_encontrado` field). This adds substantive meaning beyond the schema.

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 function: 'Busca palavras-chave no TEXTO dos atos publicados no DOE-PI' (searches keywords in the text of published acts). It also lists the types of acts covered (leis, decretos, etc.) and distinguishes itself from siblings by explaining that it returns `uuid_ato` to be used with `ler_ato` for full text.

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 provides clear context for use: search text content, then use `ler_ato` with the returned `uuid_ato` to get the full text. It also notes that the `ano` filter is applied locally because the API does not filter by date, which helps set expectations. However, it does not explicitly contrast with sibling tools like `listar_edicoes` or `baixar_edicao`, so a perfect score is not warranted.

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