reservations-mcp

resy_booking_preview

Preview a Resy reservation before confirming. Resolves a slot's book token to display time, seating type, and cancellation fees, and returns a book token for the next step.

Instructions

STEP 1 of booking. Resolves a slot bookToken into a confirmable booking and surfaces the time, seating type, and any cancellation/no-show fee. Does NOT book. Returns a real book_token to pass to resy_book.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "bookToken": "<bookToken>",
      "date": "<date>",
      "partySize": "<partySize>"
    },
    "name": "resy_booking_preview"
  }
}

Input Schema

Name	Required	Description
`date`	Yes	YYYY-MM-DD.
`bookToken`	Yes	config token from a resy_availability slot.
`partySize`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 2, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the non-destructive nature ('Does NOT book') and what it surfaces (time, seating, fees, token). However, it omits details like authentication requirements or error behaviors, which would make it fully transparent.

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 tightly packed sentences. The description is front-loaded with 'STEP 1 of booking' and every sentence adds value—purpose, non-destructive warning, and next-step guidance. No waste.

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 or annotations, but the description summarizes the expected return values (time, seating type, fees, token) and clarifies the workflow position. It lacks edge cases or prerequisites, but given the tool's simple preview nature, this is reasonably complete.

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

Parameters2/5

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

Schema coverage is only 67% (partySize lacks description), and the description does not compensate. It merely restates bookToken's schema description and does not explain partySize or add any semantic value beyond the schema. This leaves a gap in parameter 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 the tool's purpose: it is STEP 1 of booking, resolves a slot bookToken, surfaces time/seating/fees, explicitly does NOT book, and returns a book_token for resy_book. This verb+resource combination distinguishes it from siblings like resy_book.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly frames usage as 'STEP 1 of booking' and states 'Does NOT book. Returns a real book_token to pass to resy_book.' This provides clear sequential guidance and disambiguates from the resy_book sibling, satisfying when-to-use and alternatives.

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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