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LGDiMaggio

Predictive Maintenance MCP Server

by LGDiMaggio

generate_test_signal

Generate and auto-register synthetic vibration test signals for fault diagnosis and analysis, supporting bearing faults, gear faults, imbalance, and normal patterns.

Instructions

Generate a synthetic test signal, save it, and load it into the repository.

The signal is written to data/signals/ with a timestamped filename and a
companion _metadata.json declaring sampling_rate and signal_unit='g'
(synthetic acceleration), then auto-registered in the repository — the
returned signal_id is immediately usable by every analysis, diagnosis,
and ISO severity tool with no manual steps.

Signal content: 'bearing_fault' = 10 Hz impacts modulating a 1 kHz
carrier; 'gear_fault' = 200 Hz mesh tone + harmonics; 'imbalance' =
25 Hz (1500 RPM) tone; 'normal' = broadband noise.

Args:
    signal_type: Synthetic fault pattern to generate.
    duration: Signal duration in seconds (10 s gives 0.1 Hz resolution).
    sampling_rate: Sampling frequency in Hz.
    noise_level: Additive white-noise amplitude.
    random_seed: Seed for reproducible noise (None = non-deterministic).
    ctx: MCP context. Unused — see this module's docstring on logging.

Returns:
    StoredSignalInfo of the auto-loaded signal (signal_id, declared
    sampling_rate and unit 'g').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
durationNo
noise_levelNo
random_seedNo
signal_typeNobearing_fault
sampling_rateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
shapeYesShape of the signal array
filepathYesOriginal file path
signal_idYesUnique identifier for the stored signal
duration_sNoDuration in seconds
raw_formatNoEFFECTIVE raw-binary decode parameters (sample_format, byte_order, n_channels, channel_index, header_offset, scale_factor) after the explicit > companion > default merge — recorded as provenance so get_signal_info can answer 'how was this file decoded'. None for self-describing formats.
size_bytesYesApproximate memory size in bytes
num_samplesYesNumber of samples
signal_unitNoDECLARED signal unit — from load_signal(signal_unit=...) or the companion _metadata.json ('signal_unit' field). Never guessed. None means undeclared: ISO severity verdicts will be refused until the unit is declared.
sampling_rateNoSampling rate in Hz (must be positive when set)
load_timestampYesISO 8601 timestamp when signal was loaded
source_metadataNoComplete companion _metadata.json of the source file (rpm/shaft_speed, reference frequencies, ...). Empty when the file has no companion metadata.
Behavior4/5

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

With no annotations provided, the description carries the full transparency burden and does well: it discloses file writing (data/signals/ with timestamp), companion metadata, auto-registration, and the return value. It does not mention potential overwrite behavior or access requirements, but the timestamped naming implies no overwrites, and these are acceptable gaps for a generation tool.

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 efficiently structured: a one-sentence overview, a paragraph on side effects, a bullet-like list of signal content, and a clear Args/Returns breakdown. Every sentence serves a purpose, no filler, and key information is front-loaded.

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?

Despite having no annotations, the description provides a complete picture: outputs, files written, auto-registration, signal patterns, parameter details, and return type. It fully covers the complexity of a 5-parameter tool with no schema descriptions, making it self-sufficient.

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 must compensate entirely, and it does. Every parameter is explained: signal_type gives all enum values with their waveform patterns, duration notes the resolution trade-off, sampling_rate, noise_level, and random_seed with reproducibility. This adds substantial meaning beyond the bare 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 tool's purpose with a specific verb ('Generate'), a resource ('synthetic test signal'), and the full workflow (save, load, auto-register). It distinguishes itself from the many analysis/loading sibling tools by being the only signal-generation tool.

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 clearly implies when to use this tool (to create synthetic test signals for downstream analysis tools), noted by 'immediately usable by every analysis, diagnosis, and ISO severity tool with no manual steps.' It does not explicitly name alternatives or exclusions, but given the sibling set, the usage context is clear.

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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