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LGDiMaggio

Predictive Maintenance MCP Server

by LGDiMaggio

check_bearing_faults_direct

Analyze stored vibration signals to detect bearing faults (BPFO, BPFI, BSF, FTF) using bearing specifications and RPM.

Instructions

Run all bearing fault checks (BPFO, BPFI, BSF, FTF) on a stored signal.

    Args:
        signal_id: ID of the stored signal.
        bearing_id: Bearing designation (e.g. '6205').
        rpm: Shaft speed in RPM.
        tolerance_pct: Frequency matching tolerance (default 5%).
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
signal_idYes
bearing_idYes
rpmYes
tolerance_pctNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
signal_idYesSignal identifier used
bearing_idYesBearing designation
rpmYesShaft speed (RPM)
shaft_frequency_hzYesShaft frequency (Hz)
bearing_frequenciesYesCalculated BPFO/BPFI/BSF/FTF (Hz)
fault_checksYesResults for each fault type
overall_assessmentYesSummary assessment text
most_likely_faultNoMost likely fault type if any
Behavior2/5

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

No annotations provided, so description must fully disclose behavior. It only states the action without mentioning side effects, prerequisites, or output. For a tool with many siblings, this is insufficient.

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?

One-line summary followed by concise parameter list, front-loaded with essential info. No redundant sentences.

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?

Covers purpose and parameters but lacks usage guidance and behavioral details given the tool's complexity and absence of annotations. Output schema exists but not referenced.

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?

Schema coverage is 0%, but description adds meaning for all four parameters: signal_id, bearing_id, rpm, tolerance_pct. However, details like bearing format could be more explicit.

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?

Description states 'Run all bearing fault checks (BPFO, BPFI, BSF, FTF) on a stored signal,' which clearly specifies the verb, resource, and scope. It effectively distinguishes from siblings like 'check_bearing_fault_peak_tool' and 'calculate_bearing_characteristic_frequencies' by indicating it runs all four checks.

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 on when to use this tool versus alternatives such as 'check_bearing_fault_peak_tool' or 'calculate_bearing_characteristic_frequencies'. Lacks context for selection or exclusions.

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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