get_my_statsShow counts of the user's event types, bookings and team memberships.
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": "get_my_stats"
}
}| 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 establish that this is a safe, read-only, idempotent operation. The description adds useful scope by clarifying that it returns counts across three specific resource categories rather than full records, but it does not describe response shape, whether zero-count categories are included, or any other behavioral detail.
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?
It is a single, front-loaded sentence with no wasted words. The key distinction—counts rather than full records—is stated immediately.
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?
For a zero-parameter, read-only stats tool with no output schema, the description is largely sufficient: it names the exact categories being counted. A little more detail about the returned counts would help, but the structured annotations already cover the safety profile.
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 the baseline is 4. There are no parameter semantics to clarify, and the description appropriately avoids describing nonexistent inputs.
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 ('Show counts') and the resources being counted: event types, bookings, and team memberships. This clearly distinguishes it from list-style siblings such as list_event_types, list_bookings, and list_teams, though it does not explicitly name those alternatives.
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 count-oriented phrasing implies usage for summary/overview needs rather than detailed listings, but it does not explicitly say when to use this tool instead of list_event_types, list_bookings, list_teams, or get_profile. The guidance is inferable but not stated.
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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