ltspice-mcp

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getBandwidth

Compute the bandwidth of an AC response vector at a specified dB drop. Identifies the frequency range where signal stays within the attenuation limit.

Instructions

Compute -drop_db bandwidth for an AC response vector.

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": {
      "vector": "<vector>"
    },
    "name": "getBandwidth"
  }
}

Input Schema

Name	Required	Default
`vector`	Yes
`plot`	No
`run_id`	No
`raw_path`	No
`step_index`	No
`reference`	No	first
`drop_db`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.32.0Jun 10, 2026

TDQS

C2.6/5.0

Behavior2/5

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It only states the core computation, omitting side effects, required input format, output structure, error conditions, or permission requirements. The existence of an output schema is not referenced.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise but too minimal for a tool with 7 parameters. It lacks structure such as parameter grouping, examples, or explicit formulation. While not verbose, it sacrifices informativeness.

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?

Given the tool's complexity (7 parameters, 0% schema coverage) and the presence of an output schema, the description should at least list the key parameters and provide usage context. It does neither, leaving the agent underinformed for correct invocation.

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

Parameters2/5

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

Schema coverage is 0% (no parameter descriptions), so the description must compensate. It mentions 'vector' and 'drop_db' (via the name), but fails to explain the other 5 parameters (plot, run_id, raw_path, step_index, reference). Their purpose remains ambiguous.

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?

The description states a specific action ('Compute -drop_db bandwidth') on a specific resource ('AC response vector'), which clearly distinguishes it from sibling tools like getGainPhaseMargin or getSettlingTime. However, it does not elaborate on what bandwidth means (e.g., -3dB bandwidth) nor explicitly contrast with similar tools.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, typical use cases, or exclusions. Sibling tools exist for similar measurements (e.g., getGainPhaseMargin), but no comparison is made.

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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