fluig_dataset_draft_check

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

No annotations are provided, so the description carries the full behavioral burden: it does convey that this is a non-destructive pre-check and why it matters (silent overwrite of another dev's unpublished work). However, it never says what the response looks like (boolean, draft owner/metadata, error when env is prod) and there is no output schema to fill that gap.

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, the question first and the guardrail/rationale second, with zero filler. The most decision-relevant information (call before save, silent overwrite risk) is front-loaded.

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 two-parameter read check the description covers purpose, timing and rationale well. The remaining gap is return semantics — with no output schema, the agent does not know whether the result is a boolean, a draft payload, or an error, which is the one thing an agent must interpret after calling.

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 description coverage is 100% and the env parameter already carries a rich explanation of teste vs prod plus the explicit-no-default rationale. The description adds nothing about datasetId or env, so the baseline 3 applies — the schema does all the work here.

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 names the exact resource (a pending RASCUNHO in a specific dataset) and frames the tool as a check, which is specific enough to distinguish it from dataset_get/list/run/save siblings. It is phrased as a question rather than a verb+resource statement, but combined with the guardrail clause the intent is unmistakable.

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?

Explicitly says to call it ANTES de fluig_dataset_save and explains the cost of skipping it ('gravar por cima atropela em silêncio o trabalho não publicado de outro dev'). That is a clear when-to-use plus the sibling it precedes. It stops short of saying what to do with the answer (abort? notify the owner?), so not a full 5.

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