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LGDiMaggio

Predictive Maintenance MCP Server

by LGDiMaggio

generate_maintenance_recommendations

Produces maintenance recommendations based on ISO zone severity and detected fault types, delivering actionable advisory for bearing and machinery faults.

Instructions

Generate maintenance recommendations based on severity and detected faults.

    Combines ISO zone-based urgency with fault-specific maintenance
    actions. This tool intentionally does NOT accept a confidence
    value: any number supplied by the caller would be echoed into
    advisory output without evidential basis.

    Args:
        ctx: MCP context for user communication.
        severity_zone: ISO zone letter — "A", "B", "C", or "D".
        fault_types: Detected fault types from the closed canonical
            vocabulary — outer_race/inner_race/ball/cage for bearings
            (NOT the BPFO/BPFI/BSF/FTF acronyms) plus misalignment/
            unbalance/looseness. None for zone-only advice.

    Returns:
        Formatted string listing all maintenance recommendations.

    Raises:
        ValueError: If any fault type is outside the canonical
            vocabulary (the message lists the allowed values —
            unknown values are never dropped silently).
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fault_typesNo
severity_zoneYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations were provided, so the description fully carries the burden. It discloses that unknown fault types raise ValueError with a helpful message, explains why confidence is not accepted, and states the return type (formatted string). This is thorough and honest.

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 well-structured with a clear opening, bulleted details, and a Raises section. It is not overly verbose, but the inclusion of a full Args/Returns/Raises block adds length. Most sentences earn their place.

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

Completeness4/5

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

For a tool with 2 parameters and no annotations, the description covers purpose, parameters, error handling, and return format. It lacks mention of prerequisites (e.g., prior severity assessment) but is generally sufficient. The presence of an output schema (not shown) reduces the need to detail return structure.

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 description adds crucial details: it defines severity_zone as ISO zone letters, explains fault_types from a canonical vocabulary, warns against using BPFO/BPFI acronyms, and clarifies that None gives zone-only advice. This fully compensates for lacking schema descriptions.

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 maintenance recommendations combining ISO zone-based urgency with fault-specific actions. This differentiates it from sibling tools like generate_iso_report or diagnose_vibration.

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 the tool's role (combining severity and faults) and explicitly states what it does NOT accept (confidence value). However, it does not provide explicit when-to-use or when-not-to-use guidance relative to similar tools.

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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