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LGDiMaggio

Predictive Maintenance MCP Server

by LGDiMaggio

load_signal

Load a machine vibration signal into memory, making it available by ID for efficient repeated use in vibration analysis and fault detection tools.

Instructions

Load a signal into the in-memory repository for fast repeated access.

    Once loaded, reference the signal by its signal_id in other tools like
    compute_power_spectral_density, diagnose_vibration, etc.

    Args:
        filepath: Filename relative to data/signals/, or absolute path.
        signal_id: Custom ID (defaults to filename stem).
        sampling_rate: Sampling rate in Hz (overrides metadata file).
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filepathYes
signal_idNo
sampling_rateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
signal_idYesUnique identifier for the stored signal
filepathYesOriginal file path
load_timestampYesISO 8601 timestamp when signal was loaded
shapeYesShape of the signal array
num_samplesYesNumber of samples
sampling_rateNoSampling rate in Hz
duration_sNoDuration in seconds
size_bytesYesApproximate memory size in bytes
signal_unitNoSignal unit (g, mm/s, m/s², etc.)
Behavior3/5

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

No annotations are provided, so the description must cover behavioral traits. It mentions loading into memory (a state change) but does not discuss side effects like overwriting existing signals, memory limits, or error handling.

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 fairly concise, with a clear opening sentence and structured Args list. It could be slightly tighter, but it is well-organized and front-loaded with the main purpose.

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

Completeness3/5

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

Given the presence of an output schema, the description adequately explains the tool's role and usage context. However, it lacks details on error conditions, default behavior for optional parameters, and potential side effects.

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?

The description adds detailed explanations for each parameter in the Args section (filepath path format, signal_id default, sampling_rate override), which is not present in the schema (0% coverage). This adds significant meaning beyond the schema.

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 verb 'Load' and the resource 'signal into the in-memory repository', distinguishing it from sibling analysis tools which operate on already-loaded signals.

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 explains that the tool is for fast repeated access and that loaded signals are referenced by signal_id in other tools, implying usage before analysis. However, it does not explicitly state when not to use it or list alternatives.

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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