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寫給誰看:技術採購方 · 可信度:通篇都是沒有支撐的斷言

投資人或客戶會不會接著讀下去?

Jev 讀到的 state

Jev is a System One model: it doesn't write prose, it returns typed decisions with calibrated probabilities. Paste any text below and watch nine of them come back in a single request — charted, shareable, and impossible to parse wrong.

9
問題
1
次請求
324 毫秒
往返耗時
753
輸入 token
US$0.000032
費用
jev-1.13.0
模型

領銜的幾則解讀

價值是否清楚

Score

一個陌生人讀一遍能不能明白。

52%
3.43 滿分 4 · 讀到第二句時

寫給誰看

Choice

這段文字假定的讀者是誰。

86%
技術採購方 佔 88%,共 5 個選項
88% 技術採購方

可信度

Score

這些主張有沒有被撐住。

87%
0.16 滿分 4 · 通篇都是沒有支撐的斷言

同一次請求裡的其餘部分

差異化

Score

競爭對手能不能直接複製貼上這段話。

86%
2.92 滿分 4 · 一個清晰、具體的差異

用了真數字

Noul

成長、定價、規模。

幾乎肯定是
答案為「是」的機率
95%
擲硬幣

點明了問題

Noul

開藥方之前有沒有先說痛點。

確實說不準
接近擲硬幣——別只憑這一個分支
46%
擲硬幣

行話過重

Noul

用品類黑話頂替實質內容。

偏向是
答案為「是」的機率
67%
擲硬幣

有明確訴求

Noul

讀者接下來該做什麼。

確實說不準
接近擲硬幣——別只憑這一個分支
49%
擲硬幣

會收到回覆

Noul

陌生開發信的試金石。

偏向否
答案為「是」的機率
35%
擲硬幣

分享這則解讀

拿到連結的人都看得到,而且會出現在「瀏覽」裡。

發到 X
產生這則結果的確切請求

POST https://api.typesafe.ai/v1/systemone

{
  "state": "Jev is a System One model: it doesn't write prose, it returns typed decisions with calibrated probabilities. Paste any text below and watch nine of them come back in a single request — charted, share…",
  "model": "jev-latest",
  "questions": {
    "value_clarity": {
      "type": "score",
      "instructions": "How quickly does a reader understand what this offers?",
      "criteria": [
        "Never — the value is never stated",
        "Only after several reads",
        "By the end of the paragraph",
        "By the second sentence",
        "Immediately, in the first line"
      ]
    },
    "audience": {
      "type": "choice",
      "instructions": "Who is this pitch written for?",
      "criteria": {
        "Investors": "Framed around market, traction, and returns",
        "Technical buyers": "Framed around how it works and integrates",
        "Business buyers": "Framed around outcomes, cost, and risk",
        "Consumers": "Framed around personal benefit",
        "Nobody in particular": "Too generic to identify a reader"
      }
    },
    "credibility": {
      "type": "score",
      "instructions": "How well are the claims in this pitch supported?",
      "criteria": [
        "Unsupported assertions throughout",
        "Mostly claims, one soft proof point",
        "A mix of claims and evidence",
        "Most claims carry specifics",
        "Every claim has a number or a name behind it"
      ]
    },
    "differentiation": {
      "type": "score",
      "instructions": "How clearly does this distinguish itself from alternatives?",
      "criteria": [
        "Any competitor could have written it",
        "A vague gesture at being different",
        "A stated difference, unproven",
        "A clear, specific difference",
        "A difference that is hard to copy and easy to verify"
      ]
    },
    "has_numbers": {
      "type": "noul",
      "instructions": "Does the pitch contain specific numbers?"
    },
    "names_the_problem": {
      "type": "noul",
      "instructions": "Does the pitch clearly state the problem it solves?"
    },
    "jargon_heavy": {
      "type": "noul",
      "instructions": "Is the pitch obscured by jargon?"
    },
    "has_ask": {
      "type": "noul",
      "instructions": "Does the pitch make a clear ask of the reader?"
    },
    "would_reply": {
      "type": "noul",
      "instructions": "If this arrived cold, would the intended reader reply?"
    }
  }
}

把 Jev 指向你自己的文字

九個型別化答案,一次請求,大約半秒。挑一個鏡頭,或者自己寫問題。