AutoPeças MCP Server

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false, covering safety and idempotency. The description adds valuable context beyond this: it explains the tool's equivalence to an N8N agent, details three specific report types with parameter mappings, and provides usage examples. However, it doesn't mention rate limits or authentication needs, keeping it from a perfect score.

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 description is well-structured with a clear purpose statement, usage guidelines, parameter details, and examples. It's appropriately sized for the tool's complexity, but the 'Args' section could be integrated more seamlessly into the flow. Every sentence adds value, though minor redundancy exists in listing parameter values.

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?

Given the tool's moderate complexity, rich annotations, and the presence of an output schema (which handles return values), the description is complete. It covers purpose, usage scenarios, parameter semantics, and examples, leaving no gaps for an AI agent to understand and invoke the tool correctly in context with its siblings.

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 schema description coverage at 0%, the description fully compensates by detailing all parameters in the 'Args' section with clear explanations, default values, and allowed values. It maps parameters to specific use cases (e.g., status_ocupacao for availability reports) and provides practical examples, adding significant meaning beyond the bare schema.

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 clearly states the tool's purpose: 'Lista apenas os leitos do tipo Enfermaria (Tipo_Quarto = 'Enfermaria')'. It specifies the exact resource (beds of type Enfermaria) and distinguishes it from siblings like 'leitos_listar_leitos' (all beds) and 'leitos_listar_uti' (UTI beds), making the scope explicit and differentiated.

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?

The description provides explicit guidance on when to use this tool versus alternatives. It mentions 'Equivale ao Agent Enfermaria do N8N' for context, lists three specific report scenarios with parameter mappings, and references 'leitos_resumo_ocupacao' as an alternative for occupancy reports without filters. This clearly defines use cases and exclusions.

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