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NOLA Mechanic — book mobile mechanic in New Orleans

Request mobile mechanic (free callback)

request_service

Book mobile mechanic in the New Orleans 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. battery dead or weak; brake pads or rotors; car won’t start)
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 declare write (readOnlyHint=false), open-world, and non-idempotent behavior, so the bar is lower. The description adds real behavioral context beyond that: it is free to the homeowner, a vetted local pro calls back within the hour during business hours, consent is required, and it returns a reference plus next steps.

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-loaded on the core action, but the callback detail is stated twice in a redundant parenthetical ('A vetted local pro calls them back (a vetted local pro calls back within the hour during business hours)'), which is wasted space in an otherwise tight description.

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?

No output schema exists, and the description compensates by noting it 'Returns a reference and what happens next,' which tells the agent what to expect. Combined with the consent requirement, timing, and cost, it covers what an agent needs to invoke this correctly, with only minor gaps.

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 all seven parameters are already documented with types, patterns, and constraints. The description adds no per-parameter detail (e.g., no syntax for phone, zip, or need), so 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 (book/request) and resource (mobile mechanic callback in the New Orleans area), plus scope constraints (real person, with consent). It also names the sibling check_service_area for pre-validation, so the agent can distinguish it from check_service_area and get_service_info without opening schemas.

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 clear context ('for a real person who asked for it, with their consent') and a routing rule: 'Check the ZIP with check_service_area first if unsure.' This names the alternative tool and the condition that selects it, though it stops short of stating when the tool should NOT be used.

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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