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loumalouomega

Kratos MCP Server

explain_project_parameters

Parse a ProjectParameters.json to understand a Kratos simulation setup: analysis type, solver, mesh, materials, boundary conditions, and outputs. Quickly grasp a case before modifying or running it.

Instructions

Parse an existing ProjectParameters.json and return a structured summary of what it configures: analysis type, solver + linear solver, mesh and material import, and the flattened boundary-condition / load / output process lists (with the model parts each targets). Multi-stage (orchestrator/stages) cases are summarized per stage. Use this to understand a case you did not scaffold before editing or running it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
parameters_fileYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explains the tool reads an existing file and returns a structured summary with specific contents, also noting multi-stage cases are summarized per stage. It does not explicitly state it is read-only, but 'Parse' implies non-mutating behavior. Missing error handling or side-effect details, but overall transparent.

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 two sentences, front-loaded with action, and every phrase adds value. The first sentence organizes the exposed information clearly, and the second provides a concise usage directive with no filler.

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?

Given the tool's complexity (parsing JSON, multi-stage support) and the existence of an output schema, the description covers the key aspects: what it parses, what it returns, and when to use it. It does not explain the output schema details, but that is covered by the schema itself. The description is complete enough for an agent to select and invoke the tool correctly.

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 schema has one parameter `parameters_file` with no description (0% coverage). The description partially compensates by identifying it as an existing ProjectParameters.json, but does not specify path format, file vs. content, or other nuances. This is adequate but not rich.

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 clearly states the tool's function with a specific verb ('Parse... and return a structured summary') and a detailed resource (ProjectParameters.json). It enumerates the config aspects covered (analysis type, solver, etc.) and distinguishes itself from sibling tools like validate_project_parameters or create_project_parameters by focusing on understanding existing files.

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?

The description provides explicit usage context: 'Use this to understand a case you did not scaffold before editing or running it.' It implies the tool is for analysis before modifications, but does not explicitly name alternatives or state when not to use it, leaving some room for interpretation.

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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