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Little Hotelier: Export report

little-hotelier_export_report
Read-only

Little Hotelier: A Front Desk report for up to 365 days as rows, the same data as its CSV export. Returns a Front Desk report as rows, the same data as the report's CSV export. A single report cannot span more than 365 days. Use get_statistics for the Statistics report. Needs the user's Cotlet API key with access to this app.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesLast date of the range, inclusive.
fromYesFirst date of the range.
reportYescheck_in, payments, extras, housekeeping, daily_transactions or guests.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds beyond that: the 365-day cap, that output mirrors the CSV export, and the authentication requirement (Cotlet API key with app access). Return format details are thin, keeping it below 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core statement 'A Front Desk report ... as rows, the same data as its CSV export' is effectively repeated verbatim in the next sentence, wasting the reader's attention. Removing the duplication would leave a tighter, better front-loaded definition.

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 no output schema, the description does explain the return shape (rows equivalent to a CSV export), and it covers the key operational constraints (365-day limit, auth). For a 3-parameter, fully-documented read tool with annotations, this is close to sufficient.

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, but the description adds a real constraint on the date parameters: a single report cannot span more than 365 days, and the output is row-oriented like the CSV export. That materially shapes how 'from'/'to' should be set.

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 action (export/return a report as rows) on a specific resource (Front Desk report), and explicitly names the sibling it is not (get_statistics). An agent can distinguish this from other little-hotelier tools without opening the schema.

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?

Provides one explicit alternative: 'Use get_statistics for the Statistics report.' That is genuinely useful routing, but there is no guidance on when to prefer this export over list_reservations or get_booking_performance, so usage is only partially triangulated.

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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