aya_toolsets_sugerir

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

Annotations already establish readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds some behavioral context beyond the annotations by stating the tool optimizes for a minimal set and reduces token load. No contradiction with annotations.

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?

A single, efficient sentence that front-loads the verb and core purpose. Every phrase earns its place; no filler or redundancy.

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 one-parameter recommendation tool this is nearly adequate, but gaps remain: the input format of 'consulta' is unspecified and, with no output schema, the description does not state what the suggested toolset set looks like in the response. The core behavior is clear enough for basic use.

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 0%, so the description carries the burden of explaining the 'consulta' parameter, and it never mentions it. The parameter name is mildly self-explanatory, but the description does not clarify what form the query should take (e.g., a natural-language task description) or how it maps to toolset selection.

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 ('Sugere' / suggests), a clear resource (toolsets), and a distinctive objective: the minimum toolset set for a task while reducing schemas/tokens. This differentiates it conceptually from sibling 'listar' tools like aya_toolsets_listar, though it never names a sibling explicitly.

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?

Usage context is implied ('para uma tarefa', aiming to reduce tokens/schemas) but there is no explicit when-to-use vs. when-not-to-use guidance, nor any mention of alternatives such as aya_toolsets_listar or aya_mcps_recomendar_capacidade. An agent can infer the purpose but must guess about trade-offs.

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