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Mercantry Registry

by org.mercantry

Place a booking (async)

place_booking

Request a table reservation. Returns booking_id with state 'queued' immediately; fulfillment is asynchronous (a call is placed to the merchant). Poll get_booking_status or supply callback_url for webhooks. RETRY SAFETY: pass a unique client_reference_id (recommended: always); if this call times out or errors ambiguously, retry with the SAME client_reference_id and the registry returns the already-created booking instead of double-booking the restaurant. Never re-call place_booking after a timeout without one. If the merchant counter-offers a time within window_minutes and accept_within_window=true, it is auto-accepted (recommended). Otherwise the booking pauses in needs_input for you to resolve via modify_booking. Merchants on the human_call channel are fulfilled by a human operator during the operator window published in get_registry_meta — those bookings queue until worked (up to the channel SLA), so book ahead rather than for the next hour.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contactNoOptional phone/email for confirmation relay to the end human
datetimeYesRequested time, ISO-8601. Naive ('2026-07-18T19:00') means the merchant's LOCAL wall time (see the merchant's timezone field); an explicit offset ('2026-07-18T19:00:00+09:00') is also accepted
party_sizeYes
merchant_idYes
callback_urlNoWebhook URL for booking state-change events
window_minutesNoAcceptable +/- window around datetime
sandbox_outcomeNoTEST ONLY, sandbox merchants (sandbox: true): force the simulated call's result so you can exercise a specific branch on demand — confirmed, no_answer (retries then fails), counter_offer (pauses in needs_input), fully_booked, merchant_declined, bad_data. Rejected for real merchants; omit it in production
reservation_nameYesName for the reservation
special_requestsNo
client_reference_idNoYour unique ID for this booking request (a UUID is ideal). Retrying with the same value returns the existing booking (idempotent_replay: true) instead of creating a duplicate; the same value with different parameters is rejected as client_reference_conflict
accept_within_windowNoAuto-accept merchant counter-offers inside the window (recommended: true)

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description fully discloses async fulfillment, idempotency via client_reference_id, auto-accept behavior, human_call channel operator delays, and sandbox testing. No contradictions.

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?

Description is detailed but not unnecessarily verbose; front-loaded with core purpose and async behavior. Could be slightly more structured, but every sentence adds value.

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?

Given 11 parameters and no output schema, description covers all behavioral aspects: async flow, idempotency, merchant channels, auto-accept, testing, and error handling. Complete for agent understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Adds significant meaning beyond the schema: explains datetime naive vs offset, client_reference_id idempotency details, sandbox_outcome usage, and accept_within_window recommendation. Schema coverage is 73%, but description enhances understanding.

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 clearly states 'Request a table reservation' and distinguishes it from siblings like cancel_booking, get_booking_status, and modify_booking. It specifies the async nature and immediate return of booking_id with state 'queued'.

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?

Provides clear guidance on polling get_booking_status, using callback_url, retry safety with client_reference_id, and resolving paused bookings via modify_booking. No explicit when-not-to-use, but context is clear.

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

A4.2/5.0
Disambiguation5/5

Every tool has a clear and distinct purpose: booking operations (place, modify, cancel, status), merchant discovery (search, details, availability), registry metadata, and feedback submission. No overlap or ambiguity.

Naming Consistency5/5

All tool names follow a verb_noun pattern using underscore_case (e.g., place_booking, get_merchant, search_merchants). Verbs are descriptive and consistent across the set.

Tool Count5/5

9 tools are well-scoped for a booking registry server, covering all necessary operations without being overly numerous or sparse. Each tool earns its place.

Completeness5/5

The tool set covers the full lifecycle: search merchants, get details and availability, place/modify/cancel bookings, check status, submit feedback, and registry metadata. No obvious gaps for the intended domain.

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