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guardianer9-debug

CST Studio Orchestrator MCP

cst_get_axial_ratio

Extract axial ratio from completed CST simulations to assess circular polarization quality, with options to plot against angle or frequency.

Instructions

Extract axial ratio for circularly polarized antennas from a completed CST simulation. Axial ratio (AR) indicates the quality of circular polarization: AR=0 dB is perfect CP, AR<3 dB is acceptable. Can plot AR vs angle or vs frequency.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNo'vs_angle' to plot AR vs theta at fixed frequency, 'vs_frequency' to plot AR vs frequency at fixed angle.vs_angle
phi_cutNoPhi angle (degrees) for the observation direction.
frequencyYesFrequency in GHz at which to extract axial ratio.
theta_cutNoTheta angle (degrees) for the observation direction.
Behavior4/5

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

With no annotations, the description carries the full burden. It correctly implies a read-only operation after simulation (no mention of state changes) and adds interpretive context (thresholds). It does not disclose output format (e.g., data vs plot), but the mention of 'plot' suggests visualization.

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 sentences, no filler. The first sentence states the core purpose; the second provides context and options. Every word serves a purpose.

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 specificity and the absence of an output schema, the description covers prerequisites (completed simulation), key parameters, and output interpretation. It could mention the need for farfield results or return format, but it remains sufficient for typical use.

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 description coverage is 100%, but the description adds value beyond it: explaining what axial ratio means, when to use each mode (vs_angle vs vs_frequency), and the significance of thresholds. This helps the agent understand parameter choices.

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 extracts axial ratio from completed CST simulations, defines its meaning (CP quality) with thresholds (0 dB perfect, <3 dB acceptable), and distinguishes between plotting vs angle or frequency. This differentiates it from siblings like cst_get_gain or cst_get_farfield.

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 explicitly states 'from a completed CST simulation,' indicating post-simulation use. It does not explain when not to use or list alternatives, but the context of sibling tools and the specific function (axial ratio extraction) makes usage clear.

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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