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trusted-transcription

by Guillain-RDCDE
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    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.1/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool maps to a distinct stage in the transcription workflow: transcribe, detect hallucinations, repair, score, and estimate cost. There is no functional overlap or ambiguity about which tool to select.

    Naming Consistency4/5

    Most tools follow a verb_noun pattern (detect_hallucinations, estimate_cost), while transcribe, repair, and score are single verbs. The naming is still consistent in style and domain, with no mixed casing or confusing variations.

    Tool Count5/5

    Five tools is well-scoped for an audio transcription quality pipeline. Each tool serves a clear purpose and the set is neither bloated nor thin.

    Completeness4/5

    The toolset covers the full core pipeline: transcription, hallucination detection, LLM-based repair, quality scoring, and cost estimation. A minor gap is the lack of separate transcript retrieval or manual editing tools, but repair covers corrections reasonably.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources