Predictive Maintenance MCP Server

analyze_signal_trend

Assess equipment health by analyzing trend of chosen signal feature over time. Detects increasing or decreasing behavior to identify potential faults.

Instructions

Analyze the trend of a feature extracted from a signal over time.

    Segments the signal, extracts the requested feature per segment,
    and fits a linear trend to detect increasing/decreasing behavior.

    Args:
        ctx: MCP context for user communication.
        signal_file: CSV signal file in the data directory.
        feature_name: Time-domain feature to analyze (default: "rms").
        sampling_rate: Signal sampling rate in Hz (auto-detect if None).
        segment_duration: Duration of each segment in seconds.
        overlap_ratio: Overlap between segments (0-1).

    Returns:
        TrendAnalysisResult with slope, direction, and fit quality.

Input Schema

TableJSON Schema

Name	Required	Default
`signal_file`	Yes
`feature_name`	No	rms
`sampling_rate`	No
`segment_duration`	No
`overlap_ratio`	No

Output Schema

TableJSON Schema

Name	Required	Description
`feature_name`	Yes	Feature analyzed
`slope`	Yes	Trend slope per segment
`intercept`	Yes	Trend intercept
`r_squared`	Yes	R-squared goodness of fit
`trend_direction`	Yes	increasing, decreasing, or stable
`p_value`	Yes	Statistical significance
`num_segments`	Yes	Number of segments analyzed

Tool Definition Quality

A4.3/5.0

Behavior4/5

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

No annotations are provided, so the description carries full burden. It describes the algorithm: segmentation, feature extraction per segment, linear trend fitting. It also notes auto-detection of sampling rate. However, it does not discuss error handling or side effects (e.g., file not found), which would be useful.

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 concise (8 lines) with the main purpose front-loaded. The Args and Returns sections are structured and add necessary detail without redundancy. Every sentence adds value.

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?

Given the tool's complexity (segmentation, feature extraction, linear fit) and the presence of an output schema, the description covers the algorithm, parameters, and return type. It lacks explicit mention of file existence prerequisites or dependencies, but overall it is complete.

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 provides detailed explanations for each parameter via the Args section (e.g., signal_file: 'CSV signal file in the data directory', sampling_rate: 'auto-detect if None'). This adds significant meaning beyond the schema's basic type/default info.

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: 'Analyze the trend of a feature extracted from a signal over time.' It uses a specific verb (analyze) and resource (signal trend), and the process of segmentation and linear fitting distinguishes it from sibling tools like analyze_fft or analyze_statistics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains what the tool does but does not explicitly state when to use it versus alternative tools such as analyze_statistics or detect_signal_degradation_onset. Usage context is implied but no exclusions or alternatives are mentioned.

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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