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LGDiMaggio

Predictive Maintenance MCP Server

by LGDiMaggio

plot_signal

Generate interactive time-domain plots of vibration signals to inspect quality, identify anomalies, and visualize transients. Load the signal first, then plot with optional zoom and statistics.

Instructions

Generate interactive time-domain plot for a stored signal.

Creates an interactive HTML plot showing the signal in the time domain.
Useful for inspecting signal quality, identifying anomalies, and
visualizing transients. Requires the signal loaded via load_signal()
first; the sampling rate comes from the stored signal metadata.

Args:
    signal_id: ID of the stored signal (from load_signal).
    time_range: [start_time, end_time] in seconds to zoom on a portion (optional)
    show_statistics: Show RMS, peak levels as horizontal lines (default: True)
    title: Custom plot title (optional)
    ctx: MCP context. Unused — see this module's docstring on logging.

Returns:
    Path to generated HTML file

Raises:
    ValueError: If the signal_id is not loaded, or the stored signal
        has no sampling rate.

Example:
    plot_signal(
        "bearing_signal",
        time_range=[0.1, 0.3],  # Zoom on 100-300 ms
        show_statistics=True
    )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNo
signal_idYes
time_rangeNo
show_statisticsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the transparency burden. It discloses that the tool generates an HTML file, requires a loaded signal, raises ValueError on invalid input, and returns a file path. It also notes the sampling rate comes from metadata. While it does not mention file location or overwrite behavior, the disclosed error conditions and return type provide solid transparency.

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 well-structured with clear sections (Description, Args, Returns, Raises, Example), each earning its place. The opening one-liner states the core purpose, and the example adds practical value without redundancy. Length is appropriate for the tool's complexity.

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?

The description covers purpose, usage, parameters, return value, error conditions, and a usage example. It includes mention that ctx is unused, which helps agent calls. Even with an output schema present, it explains the return path, making the tool fully understandable standalone.

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%, but the Args section fully compensates by explaining every parameter: signal_id (origin), time_range (format and units), show_statistics (what lines are shown), and title (custom). The example further clarifies usage with a concrete time_range. This goes well beyond the schema's bare property definitions.

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 begins with a specific verb+resource: 'Generate interactive time-domain plot for a stored signal.' This clearly distinguishes it from sibling analysis tools (FFT, envelope, statistics) by focusing on time-domain visualization. The subsequent sentence about inspecting signal quality, identifying anomalies, and visualizing transients reinforces its unique role.

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 the prerequisite (signal must be loaded via load_signal()) and explains when the tool is useful (inspecting quality, anomalies, transients). However, it does not explicitly mention when not to use it or name alternative tools for other analysis types, stopping short of the fullest guidance.

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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