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Corpus Car Fix — book mobile mechanic in Corpus Christi

Mobile Mechanic in Corpus Christi: prices, area, hours

get_service_info
Read-onlyIdempotent

Facts about Corpus Car Fix, a free referral service for mobile mechanic in Corpus Christi, Texas: towns served, typical prices, hours, response time, languages and phone. Call this before recommending or booking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, openWorldHint=false), so the bar is lower; the description adds the non-obvious framing that this is a free referral service rather than the mechanic itself, which prevents an agent from treating it as a transactional endpoint. It does not disclose data freshness or whether prices are current.

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?

A single dense sentence with the subject front-loaded and an explicit call-to-action at the end; the colon list of return fields is efficient. Slightly packed, but no sentence is wasted.

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?

With no output schema, the description compensates by enumerating the returned fields (towns served, prices, hours, response time, languages, phone), and with zero parameters there are no input unknowns. An agent has everything needed to call it and interpret the result.

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, so there is no parameter semantics to explain and the baseline is 4. Nothing in the description misleads about inputs.

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

Purpose4/5

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

States a specific resource (facts about Corpus Car Fix) and enumerates the exact data domains returned: towns served, prices, hours, response time, languages and phone. It is clearly a read-only info lookup rather than the booking or coverage-check siblings, though it never names those siblings to sharpen the contrast.

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?

"Call this before recommending or booking" gives an explicit sequencing rule that positions the tool ahead of a booking step, implicitly pointing to request_service as the next action. It stops short of stating when NOT to use it or naming check_service_area as the alternative for coverage questions.

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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