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create_rate_alert

Monitor a hotel for price drops and get email notifications when rates fall. Optionally specify dates to watch a specific stay.

Instructions

Create a rate alert to monitor a hotel for price drops.

Set up an alert to be notified by email when the rate drops for a specific hotel.
Optionally specify dates, or leave them out to monitor any stay.
Requires a Gondola account with an API key.

Args:
    hotel_id: The hotel's Vervotech property ID (from search results).
    checkin: Check-in date in YYYY-MM-DD format. Must be provided with checkout, or both omitted.
    checkout: Check-out date in YYYY-MM-DD format. Must be provided with checkin, or both omitted.

Returns:
    Confirmation that the rate alert was created, with notification details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
checkinNo
checkoutNo
hotel_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations indicate a write operation (readOnlyHint=false) and non-destructive (destructiveHint=false). The description confirms by saying 'Create a rate alert' and adds details like email notification and optional date constraints, beyond what annotations provide.

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?

The description is well-structured with an introductory line, usage note, and parameter list. It is concise without being overly terse. Slight improvements could include shortening the prerequisites line, but overall effective.

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 the tool's moderate complexity (3 parameters, output schema exists), the description covers purpose, usage prerequisites, parameter details, and return value. No obvious gaps are present.

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 0%, but the description includes an exhaustive 'Args:' section explaining each parameter, constraints (e.g., checkin/checkout must be provided together), and the source of hotel_id. This compensates well for the lack of schema descriptions.

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 creates a rate alert to monitor a hotel for price drops. It uses a specific verb ('create') and resource ('rate alert'), distinguishing it from related tools like 'delete_rate_alert' and 'get_rate_alerts'.

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 explains when to use the tool (set up an alert for price drops) and mentions prerequisites (requires Gondola account with API key). It does not explicitly state when not to use it or compare to alternatives, but the context is clear enough.

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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