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dbtBigQuery

by FelipeRego
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Python
Remote

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    TDQS

    A4.5/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool targets a distinct concern: listing metrics, listing semantic models, describing a single metric, listing valid dimensions, running queries, explaining SQL, and checking health. There is no overlap or ambiguity—an agent can clearly choose the right tool for the task.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern (list_*, describe_metric, query_metrics, explain_metric_sql, health_check). No mixed conventions or vague verbs; the naming is predictable and self-documenting.

    Tool Count5/5

    Seven tools is well-scoped for a semantic layer server. Each tool covers a necessary aspect of exploring, querying, and validating metrics without redundancy or bloat. The count feels right for the domain.

    Completeness5/5

    The surface covers the full read-only lifecycle of the semantic layer: discovery (list_metrics, list_semantic_models), definition (describe_metric), grouping validation (list_dimensions), execution (query_metrics), cost/explanation (explain_metric_sql), and environment readiness (health_check). No obvious gaps for the stated purpose.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources