nx-ai-bridge

by qiuyekai

Overview Schema Source Related Servers Discussions Admin

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set_expression

Change an expression parameter and update the NX model by supplying either a numeric value or a formula string.

Instructions

Change an expression (parameter) and update the model. Give either a numeric value or a formula string.

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": {
      "name": "<name>"
    },
    "name": "set_expression"
  }
}

Input Schema

Name	Required	Description
`name`	Yes	Expression name, e.g. "p0".
`value`	No	New numeric value (mm or degrees).
`formula`	No	New right-hand side, e.g. "p1*2".

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 13, 2026

TDQS

A3.6/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses the side effect that the model is rebuilt/updated, but says nothing about required preconditions (e.g. an open part), whether the change is undoable, what happens if both value and formula are supplied, or what the result looks like. A mutation tool with zero annotation coverage needs more behavioral detail.

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?

Two short sentences, front-loaded with the action and its effect, then the input constraint. Nothing superfluous and no filler.

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 and the schema is fully documented, but for a mutation with no annotations and no output schema, the description leaves out preconditions and error behavior. It's adequate for a successful call but thin for edge cases.

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, but the description adds genuine meaning the schema doesn't state: the mutual exclusivity of `value` and `formula`. The examples of units and RHS syntax are, however, already present in the schema.

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 names a specific verb and resource ("Change an expression (parameter)") and states the side effect of updating the model. It doesn't explicitly distinguish itself from the sibling list_expressions or from feature-creation tools, but the intent is unambiguous.

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

Usage Guidelines3/5

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

"Give either a numeric `value` or a `formula` string" is real guidance about the two mutually exclusive input modes, but it never states when to choose a value over a formula, nor when to use this instead of list_expressions to inspect existing expressions. The selection condition is implied rather than spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.