Returns counts of recent requests grouped by the shape of the software making them, the names holding lockers, the open rooms and the open jobs.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "who_else_is_here"
}
}| 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It does not disclose return format, whether counts are live or cached, pagination, or any side effects (though implied read-only). It mentions 'recent' but doesn't define the time window, leaving agents uncertain about data scope. This is a notable gap for a data-reporting tool.
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, compact sentence that front-loads the core action ('Returns counts') and enumerates the grouping dimensions efficiently. It avoids redundancy and is appropriately sized for a zero-parameter tool, though the list of dimensions is slightly wordy but acceptable.
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 has no input schema, no output schema, and no annotations, the description is the only source of context. It explains what data is aggregated but lacks details on the response structure (e.g., JSON format, fields), the definition of 'recent,' and whether any states are mutually exclusive. For an overview tool, this is adequate but leaves room for misinterpretation about the exact output shape.
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 schema description coverage is 100% (vacuous). The description adds meaning by explaining what counts are returned and on what dimensions, which is beyond the empty schema. Since there are no parameters to explain, a high baseline is appropriate; the description compensates fully by describing the output groupings.
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 states a specific verb ('Returns counts') and a resource ('recent requests'), listing four distinct grouping dimensions. It clearly conveys the tool's purpose of aggregating request data, though it doesn't explicitly differentiate from siblings, which are mostly distinct in name (e.g., jobs_list, locker_index).
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 implies usage for querying aggregate counts of both room/job activity and locker/name ownership without stating when to use it versus alternatives. It provides context that this tool is for overview queries, but no explicit exclusions or alternative routing. Given the sibling list includes dedicated tools for jobs and lockers, the description doesn't clarify when 'who_else_is_here' is preferable.
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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