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LGDiMaggio

Predictive Maintenance MCP Server

by LGDiMaggio

get_report_info

Extract metadata from HTML report files to understand signal details and detected peaks without loading the entire HTML content.

Instructions

    Get metadata from HTML report without loading entire file.

    Extracts metadata JSON from HTML report file. This allows LLM to
    understand report content without consuming tokens for HTML.

    Args:
        file_name: Report filename in reports/ directory

    Returns:
        Dictionary with metadata (NO HTML content)

    Example:
        >>> info = get_report_info("fft_spectrum_baseline_1.html")
        >>> print(f"Signal: {info['metadata']['signal_file']}")
        >>> print(f"Peaks detected: {info['metadata']['num_peaks']}")
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries full burden. It explicitly states it extracts only metadata JSON, not HTML content, and mentions token efficiency. This provides clear behavioral expectations.

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, well-structured with a docstring format, and includes an example. Every sentence adds value without redundancy.

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?

Given the tool's simplicity (one parameter) and presence of output schema, the description is complete. It covers input, output, and purpose adequately.

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 schema has 0% description coverage, so the description must compensate. It adds 'Report filename in reports/' directory context, giving meaningful guidance beyond the schema's title and type.

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 it gets metadata from an HTML report without loading the file, distinguishing it from sibling tools that analyze signals or generate reports. It specifies the purpose of token-efficient understanding.

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 when to use (to get metadata before loading HTML) but does not explicitly exclude alternatives or provide when-not-to-use guidance. However, the context from sibling tools implies it is for lightweight pre-processing.

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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