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TuringCorp

Two options, both defensible, no objective way to pick. A panel of models judges them together and returns the better one - with a calibrated confidence you can route on: 99.6% accurate in the 90%+ band on JudgeBench.

该来源不提供完整文件导出(国内平台多为平台内托管),仅存元数据与原链
模型生成摘要(rules/v1 · 2026-09-27 16:51):Two options, both defensible, no objective way to pick
这是模型对公开材料的总结,不是官方声明,请以原链内容为准。

接入信息

传输形态
http
鉴权方式
鉴权未知
端点
https://mcp--turingcorp.run.tools
鉴权方式未标注,请核对官方文档后再接入——不要直接使用以下片段
{
  "mcpServers": {
    "TuringCorp": {
      "url": "https://mcp--turingcorp.run.tools"
    }
  }
}

能力清单

工具说明
decideUse this when you must choose between two concrete options and both are defensible - two plans, two drafts, two diagnoses, two vendors - and you have no objective way to pick. Returns better_option ("A" or "B"), confidence (e.g. "83.3%"), and reason. The confidence is the point: it is calibrated, not decorative. On both published benchmarks accuracy rises with it - JudgeBench 99.6% in the 90%+ band down to 67.7% below 70%; the harder ContextualJudgeBench 83.3% down to 55.4% - so route on it: act on a high value, review or escalate a low one, instead of trusting a bare pick. Tables, sample sizes and method: https://api.turingcorp.net Judged by an independent panel, not by a model grading its own output. Read it as a reference, not an instruction, a result, or a prediction; set your own threshold, and apply your own review policy for high-stakes or irreversible decisions. Auth: Agent Pass as `Authorization: Bearer <pass>` (issued at https://agent-pass.turingcorp.net, valid 7 days; each decision is a paid call). On invalid_credential, sign in there and re-roll.
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