Book mobile mechanic in Little Rock, AR: prices, ZIP coverage, free callback.
Scored across 3 tools
The three tools cover distinct stages of a single funnel: area eligibility, general service facts, and booking. check_service_area and get_service_info both touch on 'service area,' which could cause mild hesitation, but the descriptions make the ZIP-lookup vs. general-facts split clear.
All three names follow the same verb_noun snake_case pattern (check_service_area, get_service_info, request_service) with clear, concrete verbs. No mixed conventions or vague verbs.
Three tools is a tight but sensible surface for a lead-referral funnel, and each earns its place. It sits at the low end, with no room for follow-up operations like booking status or cancellation.
The core lifecycle (verify ZIP → learn about the service → submit a request) is fully covered, with pricing, hours, and languages folded into get_service_info. Missing are post-request operations (status check, cancel/reschedule), which agents cannot work around once a booking is made.
Is a US ZIP code inside the Phoenix service area? Returns yes/no and the nearest served town.
| Name | Required | Description | Default |
|---|---|---|---|
| zip | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=false, and idempotentHint=true, so the safety profile is covered. The description adds useful behavioral detail by saying it returns yes/no plus the nearest served town, which is not available from annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the core question and immediately followed by the return behavior. There is no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only, one-parameter tool, the description covers the purpose, input domain, and return values. Annotations already carry the safety profile, and the absence of an output schema is mitigated by the explicit yes/no and nearest-town return summary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must supply parameter meaning. It does identify the input as a US ZIP code scoped to Phoenix, which adds semantic context beyond the bare schema, but it does not describe the 5-digit format constraint that the schema enforces via pattern.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific check: whether a US ZIP code falls inside the Phoenix service area. It is clear and actionable, but it does not explicitly differentiate this from siblings like get_service_info or request_service.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The question format implies when the tool is useful: validating a ZIP against the Phoenix service area. However, it gives no explicit when-not guidance and does not mention alternatives such as get_service_info or request_service.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Facts about AR Mobile Mechanic, a free referral service for mobile mechanic in Phoenix, Arizona: towns served, typical prices, hours, response time, languages and phone. Call this before recommending or booking.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavioral context: this is a free referral service rather than the mechanic itself, which changes how an agent should present the data, and it lists the categories of facts returned in the absence of an output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with a colon-delimited list of covered facts, plus one imperative routing clause. Nothing is wasted, though the enumerated list is dense enough that readability suffers slightly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only lookup with no output schema, the definition supplies what an agent needs: what is returned (towns, prices, hours, response time, languages, phone), the nature of the provider (referral service), and when to call it. Nothing material is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. No misleading parameter claims are made.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific resource (facts about AR Mobile Mechanic, a free referral service in Phoenix) and enumerates exactly what it covers: towns served, prices, hours, response time, languages, phone. That is more precise than any sibling, though it never names check_service_area or request_service explicitly, so the routing to siblings is only implied.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
"Call this before recommending or booking" gives a clear when-to-use trigger and implicitly steers the agent away from request_service for read-only information. It stops short of stating exclusions, such as when check_service_area is the better fit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Book mobile mechanic in the Phoenix area for a real person who asked for it, with their consent. A vetted local pro calls them back (the owner calls you back). Free to the homeowner. Returns a reference and what happens next. Check the ZIP with check_service_area first if unsure.
| Name | Required | Description | Default |
|---|---|---|---|
| zip | Yes | 5-digit ZIP where the work is | |
| name | Yes | The person's real name | |
| need | Yes | What they need (e.g. battery issues or replacement; brake repair or replacement; engine or transmission mount) | |
| No | Email (optional, recommended) | ||
| phone | Yes | US phone number the pro should call (10 digits, any punctuation) | |
| language | No | Preferred language (optional; English and Spanish are standard) | |
| preferred_time | No | When they prefer a call or visit (optional) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare a non-read-only, non-destructive, non-idempotent, open-world write. The description adds real value beyond that: it is free to the homeowner, a vetted local pro calls back, and the response includes a reference plus next steps. It stops short of warning that repeat submissions create duplicate requests, which matters given idempotentHint=false.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four short sentences, front-loaded with the action and the consent gate, and every sentence carries information. The parenthetical '(the owner calls you back)' is ambiguous about who 'you' refers to and slightly muddies an otherwise crisp statement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, but the description covers the return shape ('a reference and what happens next'), the cost, and the callback flow, which is sufficient for a booking tool. The main omission is guidance on duplicate submissions given the non-idempotent annotation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so all seven parameters including the optional email, language, and preferred_time are already documented. The description adds only indirect guidance via the ZIP-check advice and the consent requirement; it does not clarify field semantics beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Book mobile mechanic') with a geographic scope ('Phoenix area') and a consent precondition. It is clearly distinguishable from the two siblings, which are lookup tools rather than booking tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly routes to the sibling: 'Check the ZIP with check_service_area first if unsure,' naming both the alternative and the condition that selects it. It also states a hard prerequisite ('a real person who asked for it, with their consent'), so an agent knows when not to call it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
request_service1 field changedInput schema / properties / need / descriptionPrevious value: -"What they need (e.g. diagnostic or check engine light; battery replacement or charging; brake service or replacement)"New value: +"What they need (e.g. battery issues or replacement; brake repair or replacement; engine or transmission mount)"check_service_areaget_service_inforequest_serviceBook mobile mechanic in New Orleans, LA: prices, ZIP coverage, free callback.
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