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Random-Stack-Random-Day

RepStack

by Random-Stack-Random-Day
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Python
Remote

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    Deploy Server
    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

    A4.4/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: ingest_log parses and normalizes workout data, compute_metrics derives analytics from canonical data, and search_exercises queries the exercise registry. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern: ingest_log, compute_metrics, search_exercises. The naming is predictable and clearly indicates what each tool does.

    Tool Count5/5

    Three tools is well-scoped for a stateless workout log processing server. Each tool covers a necessary step in the workflow without redundancy or bloat.

    Completeness5/5

    The tool set covers the full intended pipeline: ingest raw logs into canonical JSON, compute metrics from canonical sessions, and search exercises for enrichment or validation. Since the design is explicitly stateless, no persistence/retrieval tools are needed.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources