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get_product_faces

Read-only

Retrieve the full semantic face registry for a given product type, enabling agents to identify and work with individual faces in a design.

Instructions

Return the full semantic face registry for a product type.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "product_type": "<product_type>"
    },
    "name": "get_product_faces"
  }
}

Input Schema

NameRequiredDescriptionDefault
product_typeYesone of the keys from ``list_product_types``, or a sketch-built design's id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.5.1
    • addedInput schema / properties / product_type / description
      Added value: +"one of the keys from ``list_product_types``, or a sketch-built design's id."
  2. Addedv1.5.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so safety is fully covered and the bar is lower. The description adds only the word "full", hinting that the complete registry is returned rather than a filtered subset, but says nothing about size, ordering, or whether the result varies by product type beyond the argument.

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?

A single front-loaded sentence with no filler or redundancy. It is efficient, though bordering on so terse that the jargon phrase "semantic face registry" is never unpacked.

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 tool is simple (one required, fully documented parameter) and there is no output schema, so the description should sketch what a "face registry" contains. It does not say whether entries include face ids, normals, material roles, or emboss metadata, leaving the agent unable to anticipate the response shape.

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 100%, and the schema already explains that product_type is a key from list_product_types or a sketch-built design id. The description restates "for a product type" without adding format, casing, or fallback behavior beyond the schema, so baseline 3 applies.

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?

"Return the full semantic face registry for a product type" names a concrete verb and resource and is specific enough to distinguish it from most siblings. However, it never contrasts itself with closely related siblings like list_decoratable_faces, describe_face, or get_face_emboss_depth, so the agent must guess which face-related tool answers which question.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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

There is no explicit when-to-use or when-not-to-use guidance. The agent is not told to call this before decorating faces, nor when to prefer list_decoratable_faces instead, and the dependency on list_product_types appears only in the schema, not the description.

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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