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Create QR code

create_qr_code

Creates a stylized QR code from supplied text or a URL and an art-style description. Currently costs 0 credits. Starts a background job; returns a project id for wait_for_image_project.

Input Schema

NameRequiredDescriptionDefault
nameNoGive your image a custom name for easy identification.Qr Code - dateTime
styleYes
contentYesThe content of the QR code.

Output Schema

NameRequiredDescriptionDefault
idYesUnique ID of the image. Use it with the [Get image Project API](https://docs.magichour.ai/api-reference/image-projects/get-image-details) to fetch status and downloads.
credits_chargedYesThe amount of credits deducted from your account to generate the image. We charge credits right when the request is made. If an error occurred while generating the image(s), credits will be refunded and this field will be updated to include the refund.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false, and the description adds genuinely new behavior: the operation is currently 0 credits and is asynchronous, returning a project id rather than a finished asset. That async/credit context is the key thing an agent can't infer from annotations.

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?

Two sentences, zero waste, with the core action stated first and the cost/async behavior front-loaded before the follow-up hint.

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?

An output schema exists, so return values need no explanation, and the description links to the correct polling sibling. Minor gap: nothing about the style template list or failure behavior, but the essentials for a correct invocation are present.

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 coverage is 67%, and the description only restates that content is 'text or a URL' and style is an 'art-style description' — the schema already says this. It adds no constraints on the nested art_style object or the name parameter, so baseline 3 is appropriate.

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 and resource (creates a stylized QR code) plus the two inputs that drive it (text/URL and an art-style description). This is clearly distinguishable from sibling image generators like generate_image or create_meme.

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?

Gives explicit operational context: it starts a background job and returns a project id to pass to wait_for_image_project, which tells the agent exactly what to do next. It does not name when to prefer this over e.g. generate_image, so no exclusions/alternatives are covered.

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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