@striderlabs/mcp-marriott

modify_reservation

Change dates or room type for an existing reservation. Preview modifications before applying with user confirmation.

Instructions

Change dates or room type for an existing reservation. IMPORTANT: Set confirm=true only after getting explicit user confirmation.

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": {
      "confirmationNumber": "<confirmationNumber>"
    },
    "name": "modify_reservation"
  }
}

Input Schema

Name	Required	Description
`confirm`	No	Set to true to apply the modification. If false or omitted, returns a preview. NEVER set to true without explicit user confirmation.
`newCheckIn`	No	New check-in date in YYYY-MM-DD format
`newCheckOut`	No	New check-out date in YYYY-MM-DD format
`newRoomType`	No	New room type code
`specialRequests`	No	Updated special requests
`confirmationNumber`	Yes	Reservation confirmation number

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 30, 2026

TDQS

A4.3/5.0

Behavior4/5

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

No annotations are provided, so the description carries full burden. It adequately discloses the core behavior (changing dates/room type) and the confirm flag's effect (preview vs apply). However, it could mention potential side effects (e.g., price changes, cancellation of associated services) or output format.

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?

The description is two sentences long with no filler. The crucial warning about confirm is front-loaded after the purpose statement. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the main purpose and a key behavioral detail, but given 6 parameters and no output schema, it lacks explanation of what the preview returns or the actual modification's consequences (e.g., price recalculation, impact on existing extras). This leaves gaps for an agent to fully understand the tool's behavior.

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?

Schema coverage is 100%, so the baseline is 3. The description adds critical semantics for the confirm parameter (NEVER set without user confirmation), which goes beyond the schema's own description. This added value justifies a 4.

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 explicitly states 'Change dates or room type for an existing reservation,' clearly specifying the verb (change) and resource (existing reservation). It distinguishes from sibling tools like cancel_reservation (cancellation) and get_reservation (read-only).

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 a critical guideline: 'Set confirm=true only after getting explicit user confirmation.' While it doesn't explicitly compare to siblings, the sibling list is available, and the usage context is clear enough for an agent to infer when to use modify vs 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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