Skip to main content
Glama

Late checkout

ot_late_checkout
Read-onlyIdempotent

Check a room's late checkout availability, extra hours, Toman price, and bookability for a specific departure day.

Instructions

Check whether a room offers late checkout, for how many hours and at what price (Toman, a unit not confirmed on the site), and with check_out whether it can be booked on that departure day (offered rooms are often closed for it on a given day).

Use when the user wants to leave later than the check-out time. ot_price_quote adds it to a total with late_checkout_hours.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
room_idYesRoom id (code), e.g. 2512254.
check_outNoDeparture day to check, Gregorian YYYY-MM-DD, e.g. '2026-10-23'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, open-world, non-destructive, which fits a lookup. Beyond that the description discloses two behavioral traits the structured fields do not: results are date-dependent and non-deterministic across departure days ("often closed for it on a given day"), and the currency unit is uncertain. No contradiction with annotations.

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?

Front-loaded with the outcome and keeps the routing sentence short. The parenthetical "(Toman, a unit not confirmed on the site)" is slightly clunky but carries real information, so it earns its place; overall there is little 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?

With an output schema present, return values needn't be spelled out, and annotations carry the safety profile. The description covers purpose, trigger, key caveats, and the sibling relationship, leaving only minor gaps such as what happens when check_out is omitted (default null).

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 room_id and check_out are already documented; the description still adds meaning by explaining that check_out is not just a date but the switch that determines bookability on that departure day (rooms are often closed for a given day). It also flags that the price unit (Toman) is unconfirmed, which the schema does not say.

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?

States a specific verb+resource (check a room's late checkout) and enumerates exactly what the answer contains: availability, hours, price, and bookability on a given departure day. It explicitly distinguishes itself from the sibling ot_price_quote, which only aggregates the cost, so an agent can route without opening either schema.

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?

"Use when the user wants to leave later than the check-out time" gives a clear triggering condition, and it names ot_price_quote as the complementary tool for totaling cost. There is no explicit when-not guidance, but the use case is narrow and well bounded.

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