Deal Radar MCP Server

detect_checkout_inflation

Detect why a flight price jumped at checkout by separating airline bucket jumps, OTA dynamic markup, and phantom seat-lock timers, so you know whether to wait or rebook.

Instructions

Anti-Markup & GDS Phantom Seat Hold Checker: Detects why a flight price jumped during checkout—identifying whether it is an Airline Bucket Jump, an OTA Dynamic Markup, or a 15-minute Phantom TTL Seat Lock from your own prior booking session with remaining cooldown timer.

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": {
      "origin": "<origin>",
      "destination": "<destination>",
      "currentQuotedPrice": "<currentQuotedPrice>"
    },
    "name": "detect_checkout_inflation"
  }
}

Input Schema

Name	Required	Description
`origin`	Yes	Origin airport or city
`provider`	No	OTA or airline name (e.g. "MakeMyTrip", "EaseMyTrip")
`passengers`	No	Passenger count (default: 1)
`destination`	Yes	Destination airport or city
`flightNumber`	No	Optional flight number
`departureDate`	No	Departure date in YYYY-MM-DD
`currentQuotedPrice`	Yes	The inflated or newly quoted checkout price in ₹

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 9, 2026

TDQS

B3.4/5.0

Behavior3/5

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

No annotations exist, so the description carries the full burden. It usefully discloses the classification taxonomy and that results can depend on the user's own prior booking session (a lingering phantom TTL with remaining cooldown), which is real behavioral context. However, it never states whether the call is read-only or has side effects, whether it performs live provider lookups, or what happens when no prior session exists.

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?

A single front-loaded sentence that names the tool's category first and then the three outcomes. It is dense with domain jargon but every clause adds information; no filler or repetition.

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?

With no annotations and no output schema, the description must cover behavior and results, and it only sketches the three possible verdicts. It does not explain required inputs beyond origin/destination/price, nor what the response contains besides a cause label (e.g., cooldown remaining, alternative actions), leaving gaps for a 7-parameter diagnostic tool.

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%, so all seven parameters including currentQuotedPrice in ₹ are already documented. The description adds no parameter-level meaning, such as how provider or flightNumber affect classification accuracy or that departureDate is needed to correlate a prior session. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and subject: detects why a flight price jumped during checkout, and enumerates the three causes it distinguishes (bucket jump, OTA dynamic markup, phantom TTL seat lock). An agent can understand the tool's function without opening the schema, though it never names the closely related sibling analyze_fare_bucket_state to draw a boundary.

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 checkout-price-jump scenario is implied by the description, giving a rough cue for when to call it. There is no explicit when-not guidance and no routing between this and siblings such as analyze_fare_bucket_state or compare_prices, so an agent must infer the choice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.