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Place person in scene

place_person_in_scene

Use only with the user's own likeness or content they are authorized to use. Do not use for impersonation, deception, sexual content, or content involving minors.

Places a person from one supplied photo into a supplied scene image. Cost depends on resolution (from 50 credits at 640px); returns a project id for wait_for_image_project.

Input Schema

NameRequiredDescriptionDefault
nameNoGive your image a custom name for easy identification.Body Swap - dateTime
assetsYesPerson image and scene image for body swap
resolutionYesOutput resolution. Determines credits charged for the run.

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

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds real context beyond that: credit cost scales with resolution (from 50 credits at 640px) and the call returns a project id rather than a finished image, implying asynchronous work. It does not mention rate limits or failure modes, which keeps it from a 5.

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?

Two tight paragraphs with no waste. The compliance restrictions are front-loaded before the operational description, which is defensible for a tool with likeness/consent risk, though an agent scanning for 'what does this do' has to read past them first.

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?

For a nested-parameter, enum-bearing tool with an output schema, the description covers what it does, the cost implication of one required parameter, the async handoff to wait_for_image_project, and the policy constraints. The only soft spot is the absence of any hint about what the resulting image contains or how assets are uploaded, though the schema's file-path docs handle the latter.

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. The description earns an extra point by explaining that resolution drives credit cost, which is decision-relevant meaning the schema does not convey. It says nothing extra about the assets or name parameters, but the schema already documents them thoroughly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb and resource: it places a person from one supplied photo into a supplied scene image, and notes the project id it returns. That is concrete enough to separate it from edit_face_in_photo or change_clothes_in_photo by implication, though it never names those siblings directly.

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?

It gives clear context for use (own likeness or authorized content) plus explicit exclusions for impersonation, deception, sexual content, and minors. It also names the follow-up step, wait_for_image_project, which tells the agent how to continue. It stops short of pointing at alternative tools for other editing needs, so it is not a full when-to-use/when-not guide.

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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