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KC Plumb — book plumber in Kansas City

Request plumber (free callback)

request_service

Book plumber in the Kansas City area for a real person who asked for it, with their consent. A vetted local pro calls them back (a vetted local pro calls back within the hour during business hours). Free to the homeowner. Returns a reference and what happens next. Check the ZIP with check_service_area first if unsure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipYes5-digit ZIP where the work is
nameYesThe person's real name
needYesWhat they need (e.g. water leak or burst pipe; clogged drain or sewer; water heater replacement)
emailNoEmail (optional, recommended)
phoneYesUS phone number the pro should call (10 digits, any punctuation)
languageNoPreferred language (optional; English and Spanish are standard)
preferred_timeNoWhen they prefer a call or visit (optional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover safety (readOnlyHint=false, destructiveHint=false, openWorldHint=true, idempotentHint=false), yet the description adds real behavioral context: a vetted local pro calls back within the hour during business hours, the service is free to the homeowner, and the call returns a reference. The consent/real-person requirement is a meaningful constraint not captured by annotations.

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?

Front-loads the core action, which is good, but the parenthetical '(a vetted local pro calls back within the hour during business hours)' restates 'A vetted local pro calls them back' almost verbatim. That duplication costs a point; the rest of the sentences earn their place.

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?

With no output schema, the description usefully signals what comes back ('a reference and what happens next'), plus timing, cost, and consent preconditions. Coverage is strong for a booking tool; only the redundant phrasing and absent failure/edge-case handling keep it from 5.

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 already documents all 7 parameters in detail (ZIP pattern, phone format, need examples, optional email/language/preferred_time). The description adds essentially nothing beyond what the schema provides, 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 and resource (book a plumber) with a tightly scoped domain (Kansas City area) and a qualifying condition (a real person who asked, with consent). An agent can distinguish this from check_service_area and get_service_info 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 precondition and routes to a sibling: 'Check the ZIP with check_service_area first if unsure.' The consent requirement also implies a usage constraint. It lacks an explicit when-NOT-to-use statement, so it stops short of 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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