list_studentsReturn all Hogwarts students from the HP API (up to 60), each with name, house, species, gender, ancestry, patronus, wand, actor, date of birth, and alive status.
This call uses example arguments supplied in the tool’s input schema.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "list_students"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Input schema / examplesAdded value: +[
+ {}
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is well-covered. The description adds valuable context by specifying the source (HP API), the maximum result count (60), and the list of returned fields, which goes beyond the annotations to set clear expectations about the output.
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, well-structured sentence with the key information up front ('Return all Hogwarts students'), followed by the source, limit, and returned fields. Every part adds value with 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?
The tool is simple with no parameters, but the description compensates for the lack of an output schema by explicitly listing all returned fields and the result limit. The sibling tool context is not necessary for this straightforward list operation, and the description provides enough information to use the tool correctly.
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, and the schema has no properties, resulting in effective 100% schema coverage. Per the rubric, a baseline of 4 is used for zero-parameter tools. The description doesn't need to add parameter-level detail because there are no parameters to document.
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 the specific verb 'Return' with the resource 'all Hogwarts students from the HP API', clearly distinguishing it from sibling tools like list_characters, list_spells, and list_staff. It also enumerates the fields included, making the tool's purpose unmistakable.
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 clearly indicates this tool is for retrieving Hogwarts students, providing a clear context for when to use it. However, it does not explicitly mention alternatives or exclusions, such as using list_characters for broader character data, so it stops short of the highest guidance level.
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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