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hzy9981

hzy9981

by hzy9981
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Python
Hybrid

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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

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    B3.1/5.0

    Scored across 12 tools

    Disambiguation4/5

    Most tools have distinct purposes: prompt CRUD, data-driven optimization workflow, and few-shot optimization. However, 'call_dashscope_mcp' is a generic MCP caller that overlaps with the optimization tools' intent, and 'get_token_usage_stats' is unrelated, causing minor ambiguity.

    Naming Consistency3/5

    Prompt tools follow a consistent CRUD pattern (create/delete/list/read/update_prompt). Optimization tools mix styles: 'run_data_driven_optimize' and 'run_few_shot_optimization' are consistent, but 'analyze_data_driven_optimize_results', 'write_data_driven_optimize_config', and 'generate_html_report' are long and vary in structure. 'call_dashscope_mcp' uses a different verb_noun pattern.

    Tool Count5/5

    With 12 tools, the set covers two main domains (prompt management and prompt optimization) without being overwhelming. Each tool contributes to a clear workflow, and the count is appropriate for the scope.

    Completeness4/5

    Prompt management has full CRUD coverage. The optimization workflow includes setup, execution, analysis, and report generation. Missing features like job cancellation or monitoring are covered by links to the Vertex AI console. The addition of generic utilities ('call_dashscope_mcp', 'get_token_usage_stats') does not detract from domain completeness.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources