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Price an AI 3D generation

prepare_3d_generation
Read-onlyIdempotent

Step 1 of AI 3D generation on the user's connected PrintPal account. Validates the prompt or attached image, quality and format, and returns the exact credit cost, the account's available credits, normalised settings and a short-lived quote_token. Nothing is generated or charged. Show the user the cost and settings, then call generate_3d_model only if they agree. Text: pass prompt. Image-to-3D: pass the attached image as image (prompt is then an optional label). default (the standard setting, 256³), high (384³) and ultra (512³) accept text or an image and export stl/glb/obj/ply. super / superplus / superplus_1280 / superplus_1536 are high-resolution tiers (stl/glb/obj/fbx); their *_texture variants add colour textures and export glb or obj (obj arrives as a zip). High-resolution tiers work best from an image. prepare_3d_generation returns the exact credit cost.

Input Schema

NameRequiredDescriptionDefault
imageNoAn image the user attached in the conversation (PNG, JPEG or WebP).
formatNoglb
promptNoWhat to generate, e.g. "low-poly seated fox figurine". Required without an image.
qualityNodefault
image_urlNoFor clients without file attachments: an https URL of a PNG/JPEG/WebP image.

Output Schema

NameRequiredDescriptionDefault
imageNo
promptNo
settingsYes
next_stepYes
quote_tokenYes
credits_costYes
billing_policyNo
quote_expires_atNo
credits_availableYes
sufficient_creditsYes
estimated_time_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Adds real value beyond the annotations by ruling out side effects ('Nothing is generated or charged') and disclosing the quote_token artifact that the next step depends on. 'Short-lived' is left vague (no TTL), and it doesn't say what happens if the quote expires, so it stops short of full disclosure.

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 purpose and the no-charge guarantee, then dense tier/format guidance with little filler. The closing sentence 'prepare_3d_generation returns the exact credit cost' merely repeats the opening and is wasted space.

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?

Given an output schema exists and annotations cover safety, the description supplies the workflow ordering, cost-preview semantics and tier/format rules an agent needs. The omission of the `image_url` input path is the one real gap for a 5-parameter, branching tool.

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 only 60%, and the description compensates by explaining quality tiers with their resolutions (256³/384³/512³) and the per-tier export format constraints (stl/glb/obj/ply vs stl/glb/obj/fbx, texture variants glb/obj with obj as a zip) — constraints absent from the schema. It never mentions `image_url` (the fourth input path) or the format default, so it isn't complete.

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 ('Step 1 of AI 3D generation... validates the prompt... returns the exact credit cost') and positions itself in a sequence, making it clearly distinct from generate_3d_model (which actually generates) and check_3d_generation. An agent can pick the right one 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 Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit routing: 'Show the user the cost and settings, then call generate_3d_model only if they agree', plus explicit branch conditions ('Text: pass `prompt`. Image-to-3D: pass the attached image as `image`'). It even gives guidance on which input suits high-resolution tiers.

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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