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by gchen19
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Python
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FEM Results

fem_results
Read-only

Retrieve simulation outcomes by passing an analysis or completed job ID. Get maximum von Mises stress, displacement, and top stress nodes for review.

Instructions

Extract summary results from an analysis.

Pass analysis, or the job_id of a finished fem_run_submit solve (a running or failed job is an error that says so).

Returns {max_vonmises_mpa, max_displacement_mm, max_displacement_vector, top_stress_nodes: [{node, vonmises_mpa, displacement_mm}, ...]}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNo
job_idNo
analysisNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv0.5.5
    • addedInput schema / properties / analysis / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
    • addedInput schema / properties / analysis / default
      Added value: +null
    • removedInput schema / properties / analysis / type
      Removed value: -"string"
    • addedInput schema / properties / job_id
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Job Id"
+}
    • removedInput schema / required
      Removed value: -[
-  "analysis"
-]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description adds value by disclosing the error condition when the job is running/failed and by spelling out the exact return shape (including the `top_stress_nodes` array), which is beyond what annotations provide.

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?

The description is only three sentences, front-loads the purpose, and packs the return format into an inline code block. There is no fluff, and every sentence earns its place.

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?

It covers the main usage paths, the return structure (acts as a faux output schema), and error behavior for unready jobs. It does not explain precedence when both `analysis` and `job_id` are supplied, or the effect of `top_n`, but those are minor gaps for a read-only tool of this complexity.

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?

The description explains the two alternative string parameters (`analysis` and `job_id`) and their relationship to a finished solve, but says nothing about `top_n`. With 0% schema description coverage, it partially compensates for the missing parameter documentation but leaves the meaning of `top_n` implicit.

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?

The description states a specific action ('Extract summary results from an analysis') and clearly ties to the FEM domain with the field names (max_vonmises_mpa, max_displacement_mm). This distinguishes it from sibling tools like fem_modal_results or fem_thermal_results by focusing on the general summary result from a finished fem_run_submit solve.

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?

It explicitly tells the agent to pass either `analysis` or the `job_id` of a finished fem_run_submit solve, and warns that a running or failed job produces an error. It does not explicitly name alternative tools for different FEM result types, but the context is clear enough for routine use.

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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