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Request Valet Quote

valet_request_quote

Submit a valet parking quote request to the operators serving a US city. Use this when a person has asked you to arrange valet and has given their name, email, phone, city, service type and event date. The request is only sent after they confirm by email.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNoFree-text notes for the operator, e.g. venue name or timing details
serviceYesOne of the 9 canonical valet service slugs
city_slugNoCanonical kebab-case city slug from valet_search_cities, e.g. 'austin'. Omit if using city_other.
city_otherNoFree-text city name when no directory slug is known. Omit if using city_slug.
event_dateYesEvent date in YYYY-MM-DD format
guest_countNoApproximate guest count, if known
contact_nameYesThe requester's full name
contact_emailYesEmail address to send the one-tap confirmation link to
contact_phoneYesPhone number the operator can call
operator_slugNoSend to this one operator only instead of the full fan-out for the city. Omit to notify every matched operator in the city.
vehicle_countNoApproximate vehicle count, if known

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nextYesWhat the agent should tell the person to do next
_metaYesTOOL-11 ToS and attribution block
statusYesAlways pending-confirmation on success
referenceYesShort human-readable reference for this quote request

TDQS

A4.2/5.0
Behavior4/5

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

Annotations are all false, providing no positive behavioral guidance. The description adds meaningful side-effect context: the quote request is not sent immediately but only after the user confirms by email. This goes beyond the annotations and informs the agent how to handle the user's expectation.

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 tight sentences: the first covers what and when; the second covers a crucial workflow detail. There is no filler, and the most important behavioral caveat is placed in the final sentence where it stands out.

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?

Given the rich schema with 100% coverage, an output schema, and a clear trigger in the description, the tool is adequately documented. The main missing item is an explicit reference to the operator_slug fan-out option (send to one vs many), but that is covered in the schema, so this is a minor gap.

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?

The schema description coverage is 100%, so the schema already explains each parameter, including optionality and city_slug vs city_other. The description mentions 'city' but not the exact parameter mapping, yet this is sufficiently handled by the structured schema. No additional semantic value is added by the description.

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?

The description states the precise action ('Submit a valet parking quote request'), the resource ('operators serving a US city'), and the user scenario. It clearly differentiates this submission tool from sibling search/find operators, since it's the only one that creates a quote request.

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?

The description provides an explicit trigger: 'when a person has asked you to arrange valet and has given their name, email, phone, city, service type and event date.' It also adds a critical timing constraint: the request is sent only after email confirmation. However, it doesn't explicitly state when not to use it or name sibling alternatives, leaving slight ambiguity with the operator-finding tools.

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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TDQS

A4.1/5.0
Disambiguation3/5

Some tools overlap in purpose: valet_find_nearest_operators and valet_find_operators_near both use coordinates and return nearby operators, while valet_find_operators_in_city and valet_search_by_service_and_city have similar city+service semantics. The descriptions help distinguish them, but an agent must read carefully to pick the right one.

Naming Consistency4/5

All tools use the valet_ prefix and snake_case, so the naming family is recognizable and mostly verb-led. Minor deviations like valet_find_operators_near versus valet_find_nearest_operators and the longer valet_search_by_service_and_city make it slightly less predictable.

Tool Count5/5

8 tools is well-scoped for a valet directory server: city lookup, service lookup, operator searches, profile retrieval, and quote submission. Each tool earns a distinct place in the workflow without bloat or dead weight.

Completeness4/5

The toolkit covers the core workflow end-to-end: resolve cities, search operators by city/coordinate/service, get full profiles, validate service slugs, and request a quote. Obvious minor gaps are operator name search and any quote management/update operation, but the primary directory flow is complete.