EngineerCore — Mechanical Engineering Calculator

Analyze State Space System

analyze_state_space

Read-onlyIdempotent

Analyze an LTI system in state-space form. Evaluates stability, controllability, and observability. Automatically catches ragged matrices and dimension mismatches.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "A": "<A>",
      "B": "<B>",
      "C": "<C>",
      "D": "<D>"
    },
    "name": "analyze_state_space"
  }
}

Input Schema

Name	Required	Description
`A`	Yes	System matrix A (n x n)
`B`	Yes	Input matrix B (n x m)
`C`	Yes	Output matrix C (p x n)
`D`	Yes	Feedforward matrix D (p x m)

Output Schema

Name	Required	Description	Default
`observability`	Yes
`controllability`	Yes
`system_dimensions`	Yes
`stability_analysis`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedJul 24, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already indicate readOnly, idempotent, and not destructive. The description adds that the tool automatically catches ragged matrices and dimension mismatches, which is useful behavioral information beyond the annotations.

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 with no unnecessary words. It front-loads the core purpose and adds a key behavioral detail.

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 complexity of the tool (matrix parameters, analytical output) and the presence of schema descriptions and an output schema, the description covers the main analyses and error handling. It could mention return value structure but is otherwise sufficient.

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 input schema has 100% description coverage, with each parameter (A, B, C, D) having a description. The description adds no additional parameter-level semantics, so a baseline score of 3 is appropriate.

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 analyzes LTI systems in state-space form, evaluating specific properties (stability, controllability, observability). This distinguishes it from siblings like analyze_vibration or tune_pid.

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 does not provide guidance on when to use this tool versus alternatives. It lacks explicit usage context or exclusions, leaving the agent to infer based on tool name alone.

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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