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Bay Area Mobile Dog Wash Booking

check_service_area

Confirm whether Bay Area Mobile Dog Wash serves a given address or city, and whether a flat travel fee applies. Call this whenever the customer names where they live before booking — never guess coverage.

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": {
      "address_or_city": "<address_or_city>"
    },
    "name": "check_service_area"
  }
}

Input Schema

NameRequiredDescriptionDefault
address_or_cityYesThe customer's address or city, e.g. 'Cupertino', '123 Main St, Santa Cruz, CA'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the burden, and it does reasonably well: 'Confirm whether' signals a non-mutating lookup, and it discloses both pieces of information returned (coverage determination and travel-fee applicability). It says nothing about latency, rate limits, or what happens on an unmatched address, which keeps it out of 5 territory.

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

Conciseness5/5

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

Two sentences, both earning their place: the first defines the outcome, the second defines the trigger and the failure mode to avoid. Front-loaded with the action and zero filler.

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

Completeness5/5

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

For a single-parameter read lookup with no output schema, the description supplies everything needed: it names the two results an agent should expect back and the condition under which the tool is called. Nothing required to invoke it correctly is missing.

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% for the single required parameter, and the schema already gives format examples ('Cupertino', '123 Main St, Santa Cruz, CA'). The description only restates that the input is an address or city, adding no new syntax or normalization guidance, so the baseline 3 applies.

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?

States a specific verb ('Confirm') and two concrete judgments (service coverage and whether a flat travel fee applies) for a named business. The pre-booking framing cleanly separates it from book_wash, get_quote, and get_available_slots so an agent can pick it 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?

Gives an explicit trigger ('whenever the customer names where they live before booking') and a strong prohibition ('never guess coverage'), which is clear usage context. It does not, however, name alternatives or state when this check is unnecessary (e.g. existing booked customers), so it stops short of the full when/when-not/alternatives bar.

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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