Vista compacta de headings

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

With no annotations, the description carries the full burden. It describes the conversion behavior and output format, but does not disclose edge cases (e.g., invalid JSON handling), whether the operation is read-only, or any side effects. It adds useful context (reduces payload) but lacks depth.

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 long, front-loaded with the action, and contains no filler. Every sentence adds value: the first defines the transformation and output, the second explains the use case and benefit.

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 one-parameter tool with no output schema, the description provides the input source, output format, and intended benefit. It is fairly complete, though it leaves some field semantics (e.g., what 'LEVEL' and 'start-end' represent) implicit. This is acceptable given the tool's simplicity.

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 description mentions the input as 'get_document_structure JSON', which identifies the expected source of the `structureJson` parameter, but does not elaborate on its structure or constraints. With 0% schema description coverage, this partial explanation is helpful but not fully compensatory.

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 uses a specific verb ('Convierte') and resource ('get_document_structure JSON'), and specifies the exact output format (`[start-end] LEVEL "texto"`). This clearly distinguishes it from sibling tools like lint_structure and lint_text_placeholders, which have different purposes.

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 gives clear context for when to use the tool: 'Ideal para agentes (evita JSON de 100KB+)'. It implies it is for reducing large JSON payloads, and the sibling tools are linters, so no confusion arises. However, it does not explicitly state when not to use it or mention alternative tools.

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