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MARKET_AI_HUB

MARKET_AI_HUB

by fishke22
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    TDQS

    C2.9/5.0

    Scored across 21 tools

    Disambiguation3/5

    Most tools target distinct resource/action pairs, but several status/snapshot tools overlap (health_check vs get_system_info, get_data_source_status vs get_official_release_snapshot vs get_data_coverage), and analyze_taiwan_stock/analyze_osaka_nikkei vs get_analysis_packet have unclear boundaries. The detailed descriptions help, but the tool set is not immediately unambiguous.

    Naming Consistency4/5

    The dominant patterns get_<noun>, predict_<model>, and analyze_<market> are consistent and readable. Minor deviations like health_check, backtest, and run_ts_validation break the pattern slightly but do not create serious confusion.

    Tool Count3/5

    21 tools is on the heavy side for an MCP surface, with several status/coverage/snapshot tools that could plausibly be consolidated. The broad hub scope makes the count defensible, but it is borderline and requires agents to absorb a large tool list.

    Completeness4/5

    The surface covers health, data ingestion, prediction, backtesting, time-series validation, market analysis, and monitoring/archive status. Minor gaps exist around triggering forward tests and retrieving raw prediction outputs, but the core workflows are represented without major dead ends.

    Maintenance

    ActivityNo data
    ResponsivenessSyncing

    Resources