@striderlabs/mcp-american

cancel_trip

Cancel an American Airlines reservation. Provide record locator and last name; set confirm=true after explicit user confirmation to complete, otherwise preview only.

Instructions

Cancel an American Airlines reservation. IMPORTANT: Set confirm=true only after explicit user confirmation. Without confirm=true returns a preview.

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": {
      "recordLocator": "<recordLocator>"
    },
    "name": "cancel_trip"
  }
}

Input Schema

Name	Required	Description
`confirm`	No	Set to true to actually cancel. If false or omitted, returns a preview only. NEVER set to true without explicit user confirmation.
`lastName`	No	Passenger last name
`recordLocator`	Yes	The 6-character confirmation code (e.g., 'ABC123')

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 3, 2026

TDQS

A4/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that without confirm=true the tool returns a preview, and emphasizes that confirm=true should only be set after explicit user confirmation. This transparently conveys the destructive nature and the safeguard mechanism, which goes beyond basic information.

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 concise and front-loaded, with two sentences that state the purpose and critical safety instruction without waste. Every sentence provides value.

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?

The description explains the essential behavior (preview vs actual cancellation) and the confirmation requirement, which is adequate for a destructive tool with this schema. It does not explain return values in detail, but no output schema exists and the preview behavior is mentioned. Given the tool's complexity, it is sufficiently complete.

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?

Schema description coverage is 100% for all three parameters. The description adds no additional meaning beyond the schema; it repeats the confirm preview behavior and the warning, which are already in the schema. Therefore, baseline 3 is appropriate.

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 function: 'Cancel an American Airlines reservation.' This distinguishes it from sibling tools like modify_trip or check_in, as it specifically names the cancel action and the resource (reservation).

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

Usage Guidelines3/5

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

The description implies usage (when you want to cancel a reservation) and includes the important safety instruction about confirm=true, but it does not explicitly discuss when to use this tool versus alternatives like modify_trip. It provides context for safe usage but lacks explicit exclusions or alternative recommendations.

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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