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ls-dyna-mcp

ls-dyna-mcp

by codersag
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Python
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get_analysis_settings

Reads LS-DYNA analysis settings for a chosen analysis index, optionally filtered by group or visibility, and returns property names, captions, raw values, types, and read-only flags.

Instructions

Read the Analysis Settings. Each row has the property name ("Step Controls/Endtime"), the Details-panel caption ("End Time"), the raw value, its type, and whether it is read-only/visible. Enum settings (solver precision, processing type...) come back as integers; -1 is the Program Controlled default. Values are in the model's solver units (End Time here is seconds). Args: analysis_index; group (name prefix, e.g. "Output Controls"); visible_only

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": "get_analysis_settings"
  }
}

Input Schema

NameRequiredDescriptionDefault
groupNo
visible_onlyNo
analysis_indexNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.9.2

TDQS

B3.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: it discloses the row structure (property name, caption, raw value, type, read-only/visible flags), that enum settings return as integers with -1 meaning Program Controlled, and that values are in solver units. It omits operational context such as connection prerequisites and error behavior for an invalid analysis_index.

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?

Information-dense and front-loaded: what is read, what a row looks like, then value conventions, then args. Nothing is padded, though the Args list is terse-list style rather than integrated prose and some row-structure detail overlaps the output schema.

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?

A read getter with an output schema needs less return-value explanation, and the description arguably over-delivers there. But with no annotations and 0% param coverage, gaps remain: what analysis_index refers to, whether a connection must be established first, and how this relates to set_analysis_settings are all unspecified.

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 description coverage is 0%, so the description must compensate, and it only partly does: group gets a genuinely useful explanation ("name prefix, e.g. 'Output Controls'"), while analysis_index and visible_only are named but never explained. One of three parameters is meaningfully documented.

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?

Specific verb and resource: "Read the Analysis Settings" immediately tells an agent this is a read-only getter, and the contrast with the sibling set_analysis_settings is inferable from the name. It stops short of explicitly naming that alternative, so it isn't a textbook 5, but the purpose 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 Guidelines2/5

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

The description never states when to call this versus set_analysis_settings or inspect_object, nor any prerequisite (e.g. connect_to_mechanical or first fetching an analysis_index from list_lsdyna_analyses). The 'Args:' hints describe parameters, not usage conditions.

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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