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LGDiMaggio

Predictive Maintenance MCP Server

by LGDiMaggio

plot_envelope

Generate an interactive envelope spectrum plot from a vibration signal file. Optionally apply bandpass filtering and highlight bearing or gear fault frequencies to identify machinery faults.

Instructions

    Generate interactive envelope spectrum plot.

    Creates an interactive HTML plot showing both the envelope spectrum and optionally
    the filtered signal. Can highlight bearing/gear frequencies.

    Args:
        signal_file: Name of the CSV file in data/signals/
        sampling_rate: Sampling frequency in Hz (default: 10000)
        filter_band: [low_freq, high_freq] for bandpass filter (optional, default: [500, 5000])
        freq_range: [min_freq, max_freq] to limit the envelope spectrum plot (optional)
        highlight_freqs: List of frequencies (Hz) to mark (e.g., BPFO, BPFI) (optional)
        freq_labels: Labels for highlighted frequencies (optional)
        title: Custom plot title (optional)
        ctx: MCP context for progress/logging

    Returns:
        Path to generated HTML file

    Example:
        plot_envelope(
            "bearing_signal.csv",
            sampling_rate=10000,
            filter_band=[500, 5000],
            freq_range=[0, 300],
            highlight_freqs=[120.5, 241.0],
            freq_labels=["BPFO", "2xBPFO"]
        )
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
signal_fileYes
sampling_rateNo
filter_bandNo
freq_rangeNo
highlight_freqsNo
freq_labelsNo
titleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries full burden for behavioral transparency. It discloses that the tool reads a CSV file from data/signals/, generates an interactive HTML plot, uses context for logging, and returns a file path. However, it does not mention file overwrite behavior or performance considerations.

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 structured with a docstring format (Args, Returns, Example) but is relatively verbose. It includes some redundancy with parameter details available in the schema. However, the example and parameter context are valuable, making it reasonably concise for the amount of information.

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

Completeness5/5

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

Given 7 parameters with no schema descriptions and an output schema exists, the description covers all aspects: parameter meanings, return value, and a practical example. No missing context for proper tool invocation.

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

Parameters5/5

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

Schema description coverage is 0%, so the description fully compensates by providing detailed explanations for all 7 parameters, including defaults, types, and purpose. The example illustrates typical usage, adding significant meaning beyond the schema titles.

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 generates an interactive envelope spectrum plot, specifying it creates an HTML plot showing the envelope spectrum and optionally the filtered signal, with frequency highlighting. This specific verb+resource combination distinguishes it from sibling tools like 'plot_signal' or 'plot_spectrum'.

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 description provides an example but no explicit guidance on when to use this tool versus alternatives like 'compute_envelope_spectrum_tool' or 'analyze_envelope'. Usage context is implied through the description, but no exclusion criteria or alternative recommendations are given.

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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