See a student diet feedback
list_diet_feedbackWhat the student said about meals of the diet (liked, swapped, skipped).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| studentId | Yes | The student_id from list_students. |
list_diet_feedbackWhat the student said about meals of the diet (liked, swapped, skipped).
| Name | Required | Description | Default |
|---|---|---|---|
| studentId | Yes | The student_id from list_students. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With annotations declaring readOnlyHint=true, destructiveHint=false, and openWorldHint=false, the safety profile is covered. The description adds that feedback includes liked, swapped, and skipped meals, which is useful context, but it omits details like permissions, pagination, or what happens if no feedback 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 description is a single, efficient sentence that front-loads the key information with no wasted words. It is appropriately sized for a simple read-only list tool.
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 is a read-only list with one parameter and annotations covering safety, the description is minimally adequate. However, it lacks usage guidance and does not clarify how the feedback is structured or whether it is paginated, which would be helpful even without an output schema.
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 100%, so the schema fully documents the studentId parameter. The description adds no additional parameter information beyond what the schema already provides, which is a baseline 3.
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 specifies the resource (diet feedback) and what it contains (liked, swapped, skipped meals), but it does not explicitly state the verb 'list' or clarify that it returns a list for a single student. It also fails to distinguish this from similar siblings like get_diet_adherence or get_diet_plan, leaving the purpose somewhat vague.
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 guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, when-not-to-use cases, or related tools such as get_diet_adherence, leaving the agent to infer usage entirely.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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