Metas nutricionais do usuário (calorias, proteína, carbo, gordura, água, fibra e metas customizadas). Compare com os totais de dietaai_foods para avaliar a aderência.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by noting that goals include custom goals and that this data is meant to be compared against food totals. It does not describe return format or edge cases, but for a simple read-only tool this is adequate.
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 compact and well-structured: the first sentence defines the resource and its contents, and the second sentence provides actionable usage guidance. There is no redundancy or filler.
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 that the tool takes no parameters, has no output schema, and is marked as a safe read, the description is nearly complete. It tells the agent what data is available and suggests how to use it with dietaai_foods. It could be slightly more explicit about output granularity or date handling, but the low complexity and strong annotations make this sufficient.
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 tool has zero parameters, so there is no parameter documentation burden. Per the rubric, the baseline for zero-parameter tools is 4. The description does not need to compensate for undocumented schema fields, and it does not.
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 identifies the tool's resource—the user's nutritional goals—and enumerates specific goal types (calories, protein, carbs, fat, water, fiber, custom). It distinguishes itself from siblings by suggesting comparison with dietaai_foods. However, it lacks an explicit action verb such as 'retrieves' or 'lists', so it stops short of a fully explicit purpose statement.
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 gives concrete guidance: compare this tool's goal data with dietaai_foods totals to assess adherence. This frames the primary use case and differentiates it from sibling tools. It does not explicitly state when not to use the tool, but the context is clear enough for basic selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.