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jacksonnnzzz

leam-opt-mcp

by jacksonnnzzz

create_antenna_modeling_job

Create a staged modeling job from antenna specifications to generate auditable HFSS Python code, without running simulations or optimization.

Instructions

Create a staged prompt-driven modeling job without running the LLM or simulator.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNo
backendNohfss
templateNostrong_description
include_2dNo
attachmentsNo
descriptionYes
include_simulationNo
include_optimizationNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool does not run the LLM or simulator, which is a helpful negative behavior, but it does not explain what 'staged prompt-driven' entails, whether the job is persisted, or any side effects of creation. This leaves significant ambiguity for a creation tool.

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?

The description is a single, front-loaded sentence with no wasted words. It is economical and directly states the core purpose, though its terseness does leave gaps that are accounted for in other dimensions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema (which covers return values), the description is insufficient for a tool with 8 parameters, no annotations, and a rich set of sibling tools. The domain term 'staged prompt-driven modeling job' is undefined, and the description does not explain how this tool fits into the workflow or what differentiates it from other creation tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage for its 8 parameters, and the description mentions none of them. The meaning of fields like model, backend, template, include_2d, attachments, etc., is entirely unexplained, so the description adds no value beyond the raw schema.

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 identifies the action 'Create', the resource 'staged prompt-driven modeling job', and the key qualifier 'without running the LLM or simulator'. This distinguishes it from siblings like run_antenna_modeling_job, which presumably executes the job.

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?

The phrase 'without running' implies this tool is for setting up a job to be executed later, but the description does not explicitly state when to use this tool versus alternatives. It names no alternatives or exclusions, leaving the agent to infer usage from the sibling tool names.

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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