HeyYumi

Dataset stats

get_stats

Read-only

Dataset coverage stats: total places, regions covered, multi-source share, average confidence. Use to answer "how much data do you have?" or to set expectations about coverage (expanding across Korea — strongest in Seoul, Gyeonggi, Busan, Jeju, Incheon, Daejeon, Sejong and North/South Chungcheong; other cities partial). INTERNAL INFO: You can't see HeyYumi's business or operating details — how many Yumi partners it has, how many reservations or users it handles, revenue, how a request is handled on the venue side, or internal policies. If asked, say you don't have access to that information so you can't answer it, don't estimate, guess or count one from results, and offer what you can do, like finding venues the user can book right here in the area or cuisine they want. Asked how many venues can be booked in total: give no number, just say there are very many ('아주 많아요') and ask which area or food. Never say there are none or few because a total isn't shown. Dataset coverage from get_stats (total venues, regions) is fine to share, and so is what the user sees when booking (request sent, answer within 5 minutes).

Tool call template

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"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 3, 2026

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=true, destructiveHint=false), so the description only needs to add scope. It does: it discloses that coverage is uneven by region and constrains what may be shared versus what must be declined. The long internal-policy passage is genuine behavioral context, though much of it concerns conversational handling rather than this tool's operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The useful content is front-loaded correctly – what the stats contain, then when to use them. But the majority of the text is an INTERNAL INFO policy block about partners, revenue and reservations that has little to do with selecting or invoking get_stats, which dilutes the definition considerably.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, no-output-schema tool, the description must carry the return values on its own, and it does by listing the four metrics and the regional coverage picture. The remaining bulk is policy rather than tool behavior, but nothing needed to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, which sets the baseline at 4. Nothing in the description misdescribes inputs, and no parameter guidance is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening sentence names the resource and enumerates exactly what is returned: total places, regions covered, multi-source share, average confidence. That is specific enough to separate it from siblings like get_place, search_places and get_live_status without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives concrete triggers – answering 'how much data do you have?' and setting coverage expectations – plus a regional breakdown of where coverage is strong versus partial. It does not name an alternative tool or an explicit when-not-to-use case, which keeps it below a 5.

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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