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Glama

Import Airbnb Csv

import_airbnb_csv
Destructive

Importe un fichier CSV Airbnb (historique des transactions ou réservations) dans un bien donné. Le contenu du fichier CSV doit être encodé en base64 dans le champ csv_base64. Retourne le nombre de lignes importées, ignorées et les erreurs éventuelles.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
previewNo
csv_base64Yes
property_idYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

The description adds value beyond the destructiveHint annotation by specifying return values (imported/ignored counts and errors) and the base64 encoding requirement. It does not disclose potential side effects like overwriting, but the annotation already signals destructive potential, and the added output details are useful.

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 two sentences, front-loaded with the main purpose, and contains no unnecessary detail. Every sentence contributes meaningful information about the tool's functionality and output.

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?

The description covers the core import behavior, input encoding, and return values, which is helpful given no output schema. However, it omits the preview parameter entirely, which is significant because the destructiveHint suggests a potential dry-run capability. This leaves the tool's behavior incompletely specified.

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?

The description explicitly explains csv_base64 (base64-encoded CSV content) and property_id (the target property) in context, but it does not mention the preview parameter. With 0% schema coverage, this leaves one parameter unexplained, so the description only partially compensates for the schema gap.

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 imports Airbnb CSV files (transaction/reservation history) into a specific property, using a specific verb and resource. It distinguishes from sibling CRUD tools by being the only import operation.

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 provides clear context on the expected use case and input requirements (base64 encoding), but it does not explicitly state when to use this tool over alternatives or any exclusions. Since there are no competing import tools, usage is implied rather than explicitly guided.

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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