etiquetar

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

With no annotations supplied, the description carries the full burden and does the important part: it discloses replace semantics (the list is the complete set, overwriting current values) and the destructive edge case ("Lista vazia remove todas"). It does not cover what happens on invalid group slugs, whether unknown labels are auto-created, or what the call returns, so it stops short of full mutation transparency.

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 mutation semantics are front-loaded in the first clause, followed by the conceptual explanation and then the alternative-tool routing — a sensible ordering for an agent. One sentence (the 'rótulo que diz de qual contexto' gloss) is partly redundant with the examples, keeping it just below top marks.

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 2-parameter tool with no annotations and no output schema, the definition covers the essentials: full-replacement semantics, clearing behavior, label vocabulary, and where to read labels instead. It is only thin on error/validation behavior and on whether the call echoes back the resulting label set.

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?

Schema coverage is 100%, so the baseline is 3, and the description earns a bump by adding conceptual meaning beyond the schema: what a label represents semantically and concrete label vocabulary to use. It also restates the empty-list removal behavior, which the schema already encodes, so the added value is real but not large.

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 opens with a specific verb and resource ("Define as ETIQUETAS de um chat") and immediately grounds it with concrete label examples ('Empresa A', 'Freelance') and the business meaning (the work context the group/contact belongs to). It is clearly distinguishable from the reading path it names (estado_triagem).

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 states the operational motivation ("use pra saber COM QUEM está falando antes de redigir") and explicitly routes label-reading to a named alternative (estado_triagem with the `etiquetas` field). Both the when-to-use and the when-to-use-something-else conditions are spelled out.

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