Get the number of published wine cellar specialists, places and categories, and when the data last changed.
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_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 declare readOnlyHint, idempotentHint, non-destructive, and closed-world behavior. The description adds that counts are for 'published' data and reports a last-changed freshness marker, but it does not detail response shape or auth/rate-limit behavior. With rich annotations, this is adequate added context.
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?
A single front-loaded sentence with no filler; it covers all stated outputs without repetition.
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 endpoint with rich annotations, the description gives the metrics and freshness scope needed to call it. It could be more precise about the exact response structure or whether 'published' applies to all listed entities, but no output schema exists to carry that detail.
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?
There are no parameters; schema coverage is 100% and no parameter semantics are needed. The baseline for zero-parameter tools is 4.
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?
States a specific verb ('Get') and concrete return metrics: counts of published specialists, places and categories plus a last-changed timestamp. This clearly differs from list/search siblings by returning aggregates rather than records, though it does not explicitly name those siblings.
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 when-to-use or when-not-to-use guidance is given, and no alternative tool is named. An agent must infer that this is for aggregate counts/last-updated metadata rather than listing categories or places.
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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