aya_mcps_classificar

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

Annotations already declare readOnlyHint=true and idempotentHint=true, and the description adds a meaningful semantic warning: 'Registry nao implica confianca.' This clarifies that a registry entry is not an endorsement, which is useful behavioral context beyond the structured hints. No contradiction with annotations exists.

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 definition is two short sentences with no filler. The first sentence front-loads the core action and classification scheme, and the second sentence earns its place by adding an important semantic caveat about trust.

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?

There is no output schema, yet the description does not say what the tool returns or how the A/B/C/D classification is represented. It also does not describe the relevance of the input parameters. Given the tool has 4 parameters and no output schema, the description is too sparse for an agent to invoke it confidently without additional assumptions.

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 does not explain any of the four parameters. Schema coverage is effectively zero for parameter descriptions: 'nome' is required but its format is unspecified, and the boolean flags 'aya', 'referencia_mcp', and 'publisher_verificado' are not linked to the A/B/C/D policy criteria. The description leaves parameter semantics almost entirely to the agent's inference.

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 ('Classifica'), a clear resource ('MCP'), and a concrete classification scheme ('por politica A/B/C/D'). It is distinct from sibling tools like listar_permitidos, catalogo_referencia, and recomendar_capacidade, which clearly involve listing, cataloging, and recommending rather than classifying.

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?

No usage guidance is given. The description does not state when to use this tool versus the sibling MCP tools, nor does it mention any exclusions or conditions such as 'use listar_permitidos when...' or 'use recomendar_capacidade for capabilities.' The intended selection context is left entirely to inference.

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