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LassiB999

tooldash-mcp

by LassiB999

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    TDQS

    A4.2/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool targets a distinct action: reading PDF metadata, merging PDFs, extracting pages, and normalizing text. There is no overlap or boundary ambiguity, so an agent can select the right tool confidently.

    Naming Consistency4/5

    Three tools follow a clear verb_object pattern (merge_pdfs, extract_pdf_pages, clean_text), while pdf_info uses noun_noun rather than a verb-first form. This is a minor inconsistency in an otherwise predictable and readable naming scheme.

    Tool Count4/5

    Four tools is a reasonable size for a focused utility server, and none of the tools feel redundant. The mix of PDF operations with a standalone text cleaner makes the scope slightly broad, but the count itself is not too thin or bloated.

    Completeness4/5

    The PDF workflow covers the key needs of inspection, merging, and page extraction, while clean_text works as a self-contained text utility. Missing operations like PDF text extraction, rotation, or encryption are plausible additions, but agents can complete core merge, extract, and cleanup tasks without dead ends.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues