Kimi-K3
Kimi K3 is an open-weight, 2.8T-parameter native multimodal agentic model with a 1M-token context window, designed for frontier coding, knowledge work, and reasoning tasks.
它基于一次受控的盲测实验(4 种改写策略 × 4 位评委),结果显示加入可追溯的个人素材后得分从 5.9 跃升至 8.6,远胜纯删除法。
人味不是删出来的。 De-slop your writing with evidence, not word blacklists.
AI编细节是为论点服务的, 不会把细节浪费在用不上的电车站上。
为什么叫电车站 · 它凭什么不一样 · 两种用法 · 安装 · English
一次四版本盲测:同一篇文章的四个版本,匿名乱序,交给一位审过上千篇AI投稿、患有重度「AI疑心病」的编辑,让他赌哪版是真人手笔。
他赌中了。理由不是文笔,是一个对论证毫无用处的细节——作者在维也纳除了弗洛伊德博物馆,还去看了阿德勒的电车站。
那个电车站是作者两年前真实发过的动态。这个skill帮你的文字找回它的电车站。
市面上的去AI味工具几乎都是「删」派:禁词表、句式黑名单、破折号计数。这个skill的方法论来自一次真实的对照实验(四版本改写×四评委盲测,数据在 references/evidence.md):
| 方法 | 盲测得分(像真人,1-10) |
|---|---|
| 原稿 | 5.5 |
| 纯删法(结构手术) | 5.9 —— 评委:「干净得像消过毒」 |
| 删法 + 真实素材注入 | 8.6,四票全胜 |
结论写在名字里:人味不是删出来的。AI味分四层(词汇
MIT — 随便用,随便改,随便造。
作者的其他项目 · also by 花叔
女娲.skill — 蒸馏任何人的思维方式 · 弗洛伊德.skill — 给AI做心理分析 · 达尔文.skill — 让 Skill 无限进化
Tramstop Skill is an evidence-based de-slop skill for AI-assisted writing. Its method comes from a controlled experiment (4 rewrite strategies × 4 blind judges): word blacklists and structure surgery alone barely moved the needle (5.5 → 5.9 on a 10-point "reads human" scale), while injecting traceable personal material scored 8.6 with a unanimous vote.
The name: a judge with severe "AI suspicion" correctly identified the human-sounding version by one detail useless to the argument — the author had visited Adler's tram stop in Vienna. AI invents details that serve the point; humans remember details that serve nothing.
What it does differently:
[TODO] placeholders.Install: `git clone https://github.com/alchaincyf/tramstop-skill.git ~/.claude/skil
电车站.skill — 人味不是删出来的。Evidence-based de-slop skill: 四层AI味模型+真实素材注入,来自四版本盲测实验
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