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nx-ai-bridge

nx-ai-bridge

by qiuyekai
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list_faces

Lists faces of an NX body with IDs, types, sample points, normals/axes, and bounding boxes to inspect geometry and select faces for modeling.

Instructions

List the faces of a body with id, type, a point on the face, its normal/axis direction and bounding box.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_faces"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyNoBody or feature name. Optional when the part has exactly one body.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations exist, so the description carries the behavioral burden. 'List' implicitly signals a non-mutating read, and the description does usefully disclose the returned attributes (point, normal/axis, bounding box), but it says nothing about behavior when several bodies exist, ordering, size of results, or whether geometry must be loaded first.

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?

A single sentence, front-loaded with the operation and then the return fields, with no filler or redundancy. Every clause conveys information about what comes back.

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 and no annotations, the description compensates well by enumerating the return fields, which is the main missing structured information. It leaves gaps only around preconditions (e.g., must a part be open) and behavior with multiple bodies.

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 single parameter 'body' is already documented there, including that it is optional for single-body parts. The phrase 'of a body' only loosely aligns with the schema and adds no naming/syntax guidance beyond it, 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?

States a concrete verb (list) and resource (faces of a body) and enumerates what is returned (id, type, point, normal/axis, bounding box), which distinguishes it from siblings like list_edges or get_model_info. It stops short of explicitly naming those alternatives.

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?

No when-to-use or when-not-to-use guidance is given, and no alternative is mentioned. The only implied usage is the restatement of the name; the agent must infer that this is the read-only inspection tool to reach for before operations like boolean_* or chamfer.

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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