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3Descu 3D Printing Quotes (EU)

Analyze a 3D model

analyze_model
Read-onlyIdempotent

Download a 3D model from a public https URL and measure it: volume, bounding box, surface area, triangle count, and whether the mesh is watertight. Accepts .stl and .obj. Feed surface_area_mm2 from the result into estimate_price to get an exact price instead of a range. Only well-known model-hosting and file-sharing domains can be fetched.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic https URL to a .stl or .obj file, served as the raw file rather than as an HTML page.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and openWorld, so safety is covered. The description still adds beyond that: an outbound-fetch domain allowlist, the accepted file formats, and the exact measurements returned, which is valuable context for a network-touching tool. It does not cover failure behavior (e.g. what happens for an unsupported domain or malformed mesh).

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 the action and the measured outputs, then the downstream estimate_price link, then the fetch constraint. Sizing is appropriate for a one-parameter tool, with only mild redundancy in restating the .stl/.obj formats already present in the schema.

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 carries the return-value burden and does list the measured quantities, which is enough for an agent to know what it gets back. It omits units conventions beyond mm², error/failure cases, and latency/cost expectations for remote downloads, leaving modest gaps.

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% and the schema already documents the url format and the raw-file-not-HTML requirement, setting a baseline of 3. The description contributes extra constraint on the same parameter by restricting fetchable domains to well-known hosting/file-sharing sites, and repeats the .stl/.obj acceptance, so it adds a little value over the schema.

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?

Specific verb (download + measure) and resource (3D model from a public https URL), followed by an explicit enumeration of what is measured: volume, bounding box, surface area, triangle count, watertightness. It also names a sibling (estimate_price) and the downstream relationship, so it is distinguishable from get_capabilities and list_materials without opening any schema.

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 a clear when-to-use context via the routing instruction to feed surface_area_mm2 into estimate_price for an exact price instead of a range, which tells the agent this tool is the precise-pricing path. It also states a real precondition (only well-known model-hosting and file-sharing domains can be fetched), though it does not spell out an explicit 'do not use this if...' exclusion.

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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