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Japan External Execution

by io.github.furoito
OverviewDiscussionsAdmin

Check Japan physical verification fit

check_service_fit
Read-onlyIdempotent

Use when an AI needs someone on the ground in Japan to verify a current physical-world fact such as store stock, shelf price, opening status, or permitted photos, after web research or APIs are insufficient.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "location": "<location>",
      "objective": "<objective>"
    },
    "name": "check_service_fit"
  }
}

Input Schema

NameRequiredDescriptionDefault
locationYesPublic business or retail location in Japan.
objectiveYesThe physical-world fact that must be verified.
evidence_requirementsNoRequested evidence such as photo, displayed price, stock observation, or timestamp.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare read-only, idempotent, non-destructive, and closed-world behavior. The description adds useful context that verification involves a human on the ground in Japan and is a fallback after web research, but it does not disclose what the check returns or how it relates to subsequent request creation.

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

Conciseness4/5

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

The description is a single, front-loaded sentence that begins with 'Use when' and packs in domain, examples, and a precondition without filler. It is appropriately sized for a brief routing tool.

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

Completeness3/5

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

Given no output schema and rich annotations, the description covers when to invoke but omits what the tool actually returns (e.g., a fit assessment) and how it fits before sibling tools like prepare_verification_request or create_verification_request. An agent can decide to call it but may not know what to expect next.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema fully documents location, objective, and evidence_requirements. The description adds no parameter-level meaning beyond what the schema already provides, which is the expected baseline when coverage is high.

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

Purpose3/5

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

The description explains the scenario in which to use the tool but does not state what the tool itself does (e.g., assesses feasibility, returns a fit result). The name and title imply a check, but the description never says 'this tool checks whether a physical verification request can be fulfilled.' It also does not differentiate this tool from sibling request-creation tools.

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 clearly states when to use the tool: when an AI needs ground verification in Japan and web research or APIs are insufficient. The condition acts as an implicit when-not, but no sibling alternatives (e.g., create_verification_request) are named for comparison.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Japan External Execution toolsInspect
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