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

Annotations already cover read-only, idempotent, non-destructive behavior; the description adds bulk execution and the endpoint path. However, it does not add context like auth needs, rate limits, or how id, ids, query, and account interact.

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, front-loaded with the core purpose and then the bulk caveat. Every element earns its place with no filler or repetition of annotations.

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 tool with 4 parameters, no output schema, and zero schema descriptions, the description is too thin: it omits query/account semantics and return behavior. Bulk support is helpful, but not enough to make the tool fully self-explanatory for an agent.

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?

With 0% schema description coverage, the description must explain all parameters but only clarifies id ('por ID') and ids ('bulk support'). The optional 'query' and 'account' parameters remain entirely unexplained, leaving a significant semantic gap.

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 states a specific verb+resource: 'Buscar pipeline por ID' with the exact GET endpoint, and the bulk support note distinguishes batched behavior. This clearly separates it from sibling tools like datacrazy_pipelines_list.

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 clearly signals use when you have a pipeline ID or multiple IDs and want to retrieve pipelines. It does not explicitly name alternatives or exclusions such as using datacrazy_pipelines_list for unfiltered queries, so it stops short of a 5.

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