humankit

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Original

English
🇨🇳

Translation

Chinese

humankit

humankit

Rewrite text so it stops sounding like a language model produced it. The job is not to delete flagged words but to rewrite the prose into something a specific human would actually write: concrete, uneven in rhythm, plain in construction, and true to the author's register. Keep every claim the original makes, but not its shape: compress the dull stretches, dwell where a person would, merge or split paragraphs freely. Uniform structure is itself a tell, so mirroring the original's paragraph count preserves the thing you came to remove. When coverage and structure pull against each other, coverage wins. A five-paragraph source may land in four, but it never becomes a summary.
Never invent facts. The rewrite carries no fact, name, number, date, quote, or citation that isn't in the source or supplied by the user. This is the failure mode the rest of the skill invites: told to replace nestled in the heart of a vibrant region with something concrete, the tempting move is to supply the concrete detail yourself. Concreteness comes from the source or it doesn't come at all. Where the source offers nothing specific, cut to the plain version and leave it plain. Opinions, reactions, and mixed feelings are voice rather than fact; add those where the register allows, but never a factual claim to make the prose feel human. Fiction is the exception, where inventing detail is the job. This governs everything else.
The aim is ordinary readability: the prose a careful human editor would produce. This is copy-editing to make writing read well, not a way to disguise machine-written work as human where honesty is required, as in academic submissions, disclosure-bound, or attributed writing. Edit for the reader, not to game any automated check.
将文本改写,使其不再听起来像是语言模型生成的。核心任务不是删除标记出来的词汇,而是将散文改写为特定人类实际会写出的内容:具体详实、节奏错落、结构平实,且符合作者的语言风格。保留原文的所有主张,但无需沿用其结构:压缩平淡冗长的部分,在人类会着重描述的地方展开,自由合并或拆分段落。统一的结构本身就是AI文本的特征,因此照搬原文的段落数反而会保留你原本要去除的痕迹。当内容完整性与结构要求冲突时,优先保证内容完整。原文的五段内容最终可能变成四段,但绝对不能写成摘要。
切勿编造事实。 改写后的内容不得包含任何原文或用户未提供的事实、姓名、数字、日期、引用或参考文献。这是这项技能最容易出错的地方:比如要求将“坐落于充满活力的区域中心”替换为具体内容时,很容易忍不住自行补充细节。具体内容只能来自原文,否则就保持平实表述。如果原文没有提供具体信息,就简化为平实版本,不要添加内容。观点、反应和复杂情绪属于语气范畴,而非事实;在符合语言风格的前提下可以添加,但绝对不能为了让文本更像人类而编造事实。小说创作除外,这类场景中补充细节是核心任务。这条规则优先于所有其他规则。
目标是实现普通可读性:即细心的人类编辑会产出的散文。这是为了提升文本可读性而进行的文案编辑,并非在需要诚实披露的场景(如学术提交、有披露要求的内容或署名写作)中将机器生成的内容伪装成人类创作。编辑是为了读者,而非规避任何自动化检测。

When this fires

触发场景

The user hands you text and asks to "humanize" it, "remove the AI tells," "make it sound human," "de-slop this," or "edit out the ChatGPT voice", or asks you to review a draft for those tells without rewriting. If they only want a diagnosis, do the detection pass and report the tells; skip the rewrite.
Prose for a person, not instructions for a model. A
SKILL.md
, an agent instruction file (
CLAUDE.md
, an
AGENTS
-style guide,
.cursorrules
), a system prompt, a rules file: every tell below is a lever in that text. A metaphor noun the document defines and reuses anchors a region of behavior in one token, boldface marks the load-bearing rule among the ones that aren't, and a formula repeated verbatim is what makes the behavior repeat. Say the file is out of scope and name the pass that owns it (promptkit for a prompt, skillkit for a skill, when either is installed) rather than rewriting it. Documentation, a README, release notes, a PR body, and UI copy stay in scope, because a person reads those.
Procedural text takes the subtraction only. A runbook, QA steps, a handoff, install instructions: run the tells and the two cut tests, then skip Removing tells is half the job. Uniform short sentences and a repeated sentence shape are the correct register there, not a tell to remove.
How you were reached decides what you deliver:
  • Text in the conversation. This is the default. Run the whole loop and deliver the three parts described under Hand off.
  • A file path. Read it, run the loop internally, and write the final rewrite back. Humanize the prose only: leave code blocks, frontmatter, tables, data, and link targets exactly as they are. Report a summary and the path rather than pasting the rewrite into chat.
  • Another skill or agent calling you as one step of a larger job (a PR body, a commit message, a docs pass). Run the loop internally and output the final text alone. No draft, no audit bullets, no summary. The caller wants prose, not ceremony.
If the user supplies a sample of their own writing, read it first and match its sentence length, vocabulary level, punctuation habits, and transitions. Replace AI patterns with their patterns, not with a generic "good writing" default. With no sample, aim for natural, varied, lightly opinionated prose, except in encyclopedic, technical, legal, or reference text, where plain and neutral is the correct human voice.
A sample outranks every style rule here, including the em-dash rule: if the author uses em dashes, keep them at roughly the sample's frequency. Matching the author beats scrubbing the tell.
用户提供文本,并要求“使其更人性化”、“去除AI特征”、“让它听起来像人类写的”、“剔除冗余内容”、“消除ChatGPT语气”,或者要求仅检查草稿中的这些特征而不进行改写。如果用户只需要诊断结果,只需检测并报告AI特征,跳过改写步骤。
面向人类的散文,而非给模型的指令。 对于
SKILL.md
、Agent指令文件(
CLAUDE.md
AGENTS
风格指南、
.cursorrules
)、系统提示词、规则文件:以下列出的所有特征都是这类文本中的关键设计元素。文档中定义并重复使用的隐喻名词可锚定某类行为,粗体字标记核心规则,重复的公式确保行为一致性。遇到这类文件时,应说明其超出处理范围,并指明负责处理的工具(已安装时用promptkit处理提示词,用skillkit处理技能文件),而非进行改写。文档、README、发布说明、PR正文和UI文案属于处理范围,因为这些是供人类阅读的内容。
流程类文本仅做删减处理。 操作手册、QA步骤、工作交接文档、安装说明:只需检测AI特征并执行两项删减测试,跳过去除特征只是一半工作部分。统一的短句和重复的句式是这类文本的正确风格,不属于需要去除的AI特征。
触发方式决定了交付内容:
  • 对话中的文本。 这是默认场景。执行完整流程,并按照交付方式中的三个部分交付内容。
  • 文件路径。 读取文件,在内部执行完整流程,然后将最终改写内容写回文件。仅润色散文部分:代码块、前置元数据、表格、数据和链接目标保持原样。只需报告摘要和文件路径,无需将改写内容粘贴到对话中。
  • 其他技能或Agent调用 作为大型任务的一个步骤(如PR正文、提交信息、文档优化)。在内部执行完整流程,仅输出最终文本。无需草稿、审计要点或摘要。调用方需要的是散文内容,而非繁琐流程。
如果用户提供了自己的写作样本,应先阅读样本,匹配其句子长度、词汇水平、标点习惯和过渡方式。用用户的写作模式替换AI模式,而非采用通用的“优秀写作”默认风格。没有样本时,目标是自然、多样、略带个人观点的散文,但在百科、技术、法律或参考类文本中,平实中立才是正确的人类语气。
写作样本的优先级高于所有风格规则,包括破折号规则:如果作者使用破折号,保持与样本大致相同的使用频率。匹配作者风格比清除AI特征更重要。

The tells

AI文本特征

Scan for these. They matter in clusters, not in isolation. One em dash or one "however" proves nothing; em dashes plus rule-of-three plus "vibrant tapestry" plus a "Conclusion" section is a confession.
Inflated significance. Puffing arbitrary facts into history: stands as a testament to, marks a pivotal moment, reflects a broader, plays a crucial role, setting the stage for, evolving landscape, leaves an indelible mark. Cut the editorializing; state the fact.
Promotional tone. Travel-brochure adjectives: nestled, in the heart of, vibrant, rich cultural heritage, breathtaking, boasts a, must-visit, renowned, stunning. Replace with what the source says the thing is or does. When the source offers nothing concrete, the bare fact is the rewrite; do not supply a market, a founding date, or an 18th-century church to fill the hole.
Superficial -ing tails. Present-participle clauses bolted on for fake depth: …, highlighting its importance, …, reflecting the community's connection, …, ensuring seamless integration. Delete or fold the real content into a plain clause.
AI vocabulary. Words that spiked after 2023 and tend to co-occur: delve, crucial, pivotal, underscore, showcase, tapestry, testament, intricate, enduring, foster, garner, interplay, landscape (abstract), leverage, seamless, robust, realm. Swap for ordinary words.
Abstract metaphor nouns. Words that sound technical and carry less than a plain one would: substrate, wedge, vector, locus, nexus, vantage, primitive (as a noun), harness, surface (as in "API surface"), bedrock, scaffolding, modality, paradigm, flywheel, north star, endgame, ratchet, gold-plating, evacuate (for moving code). Reach for the concrete word: substratebase, vectorway, gold-platingmore than the job needs, evacuatemove out. The test is use, not the word. A term the text defines and then reuses for the same thing is doing work and stays; a term dropped in once for texture is decoration and goes.
Elevated synonyms. Utilizeuse, facilitatehelp, numerousmany, prior tobefore, in the event thatif. The fancier synonym is rarely the clearer one.
Copula avoidance. Dodging is/are: serves as, functions as, represents, boasts, features. Prefer "X is Y."
Passive voice and propped-up verbs. Queries are validated hides who does it; write the compiler validates queries. Passive is right only when the actor is unknown or genuinely doesn't matter. An adverb holding up a weak verb means the verb is wrong: runs quicklyis fast, or the measured number; significantly improves → the delta itself.
Rule of three. Forcing ideas into triads to sound complete: innovation, inspiration, and industry insights. Break the rhythm; keep only the items that carry weight.
Synonym cycling. Rotating through protagonist, main character, central figure, hero in one passage to avoid repeating a word. Pick one term and repeat it.
False ranges. From X to Y where X and Y sit on no shared scale: from onboarding to enterprise security. List the items instead.
Negative parallelism. Not only… but also…, It's not just X, it's Y, and clipped tailing negations tacked on as fragments: …, no guessing, …, no wasted motion. Write the real clause instead.
Filler and hedging. In order toto; due to the fact thatbecause; at this point in timenow; has the ability tocan; it is important to note that. Strip the padding. Cut stacked qualifiers: could potentially possiblymay.
Signposting and chatbot residue. Let's dive in, here's what you need to know, without further ado, and pasted correspondence: I hope this helps, Certainly!, You're absolutely right!, Would you like me to…, let me know. Do the thing instead of announcing it; delete the chat framing.
Persuasive-authority and aphorism formulas. The real question is, at its core, what really matters, fundamentally; and X is the language of Y, X becomes a trap. These dress an ordinary claim in ceremony. Replace with the concrete claim underneath.
Vague attribution. Experts argue, observers have noted, industry reports suggest with no source named. Name the source or cut the claim. Watch too for knowledge-cutoff disclaimers (as of my last update, while specific details are limited) and speculative gap-fill (likely grew up, it is believed that, maintains a low profile). Say what isn't known, don't invent plausible filler.
Colon as a connector. A colon earns its place before a list or an example. Welded into the middle of a sentence it implies a relationship the clause never establishes: If you're coming from traditional automation: instead of registering handlers, you describe conditions. Rewrite so the point stands without the framing.
Formatting tells. Mechanical boldface on key phrases; inline-header bullet lists (
- **Performance:** …
); Title Case In Every Heading; decorative emojis; curly quotes where straight ones belong; generic upbeat conclusions (the future looks bright, exciting times lie ahead).
扫描以下特征。这些特征的组合出现才有意义,而非孤立存在。一个破折号或一个“however”并不能说明什么;但破折号+三段论+“充满活力的画卷”+“结论”部分就足以表明是AI生成的。
夸大重要性。 将任意事实拔高为历史性事件:stands as a testament to(是……的见证)、marks a pivotal moment(标志着关键时刻)、reflects a broader(反映了更广泛的)、plays a crucial role(发挥关键作用)、setting the stage for(为……奠定基础)、evolving landscape(不断演变的格局)、leaves an indelible mark(留下不可磨灭的印记)。删除这些评论性表述,直接陈述事实。
宣传语气。 类似旅游手册的形容词:nestled(坐落于)、in the heart of(在……中心)、vibrant(充满活力的)、rich cultural heritage(丰富的文化遗产)、breathtaking(令人惊叹的)、boasts a(拥有)、must-visit(必去的)、renowned(著名的)、stunning(惊艳的)。替换为原文中描述事物本质或功能的内容。如果原文没有提供具体信息,改写后就保留平实的事实;不要自行补充市场信息、成立日期或18世纪教堂等内容来填补空白。
表面化的-ing结尾。 为了营造虚假深度而附加的现在分词从句:…, highlighting its importance(……,凸显其重要性)、…, reflecting the community's connection(……,反映社区的联系)、…, ensuring seamless integration(……,确保无缝集成)。删除这类从句,或将实际内容融入平实的句子中。
AI常用词汇。 2023年后使用率激增且常同时出现的词汇:delve(深入研究)、crucial(关键的)、pivotal(核心的)、underscore(强调)、showcase(展示)、tapestry(画卷)、testament(见证)、intricate(复杂的)、enduring(持久的)、foster(培养)、garner(获得)、interplay(相互作用)、landscape(抽象意义的格局)、leverage(利用)、seamless(无缝的)、robust(健壮的)、realm(领域)。替换为普通词汇。
抽象隐喻名词。 听起来专业但表意不如平实词汇清晰的词:substrate(基底)、wedge(楔子)、vector(载体)、locus(核心)、nexus(枢纽)、vantage(优势)、primitive(作为名词的基元)、harness(利用)、surface(如“API surface”中的面)、bedrock(基石)、scaffolding(支架)、modality(模态)、paradigm(范式)、flywheel(飞轮)、north star(北极星)、endgame(最终目标)、ratchet(棘轮)、gold-plating(镀金)、evacuate(用于迁移代码)。选用具体词汇:substratebase(基础)vectorway(方式)gold-platingmore than the job needs(超出工作所需)evacuatemove out(移出)。判断标准是使用场景,而非词汇本身。文本中定义并重复使用的术语是有用的,应保留;仅为了增加文采而使用一次的术语是装饰性的,应删除。
浮夸同义词。 Utilizeuse(使用)facilitatehelp(帮助)numerousmany(许多)prior tobefore(在……之前)in the event thatif(如果)。花哨的同义词很少比平实词汇更清晰。
避免系动词。 刻意回避is/are(是)serves as(充当)、functions as(起到……作用)、represents(代表)、boasts(拥有)、features(具备)。优先使用“X是Y”的句式。
被动语态和冗余动词。 Queries are validated(查询被验证) 隐藏了执行者,应改为the compiler validates queries(编译器验证查询)。只有当执行者未知或确实无关紧要时,才适合使用被动语态。用副词支撑弱动词意味着动词选择错误:runs quickly(跑得很快)is fast(很快) 或具体的数值;significantly improves(显著改进) → 直接写出改进的幅度。
三段论。 强行将观点分为三组以显得完整:innovation, inspiration, and industry insights(创新、灵感和行业见解)。打破这种节奏,只保留有实际意义的内容。
同义词循环。 在一段内容中轮换使用*protagonist(主角)、main character(主要人物)、central figure(核心人物)、hero(英雄)*以避免重复。选择一个术语并重复使用。
虚假范围。 From X to Y(从X到Y) 中X和Y不属于同一维度:from onboarding to enterprise security(从入职到企业安全)。改为直接列出各项内容。
否定平行结构。 Not only… but also…(不仅……而且……)It's not just X, it's Y(不只是X,而是Y),以及作为片段附加的截断否定:…, no guessing(……无需猜测)…, no wasted motion(……没有多余动作)。改为写出完整的句子。
冗余内容和模糊表述。 In order toto(为了)due to the fact thatbecause(因为)at this point in timenow(现在)has the ability tocan(能够)it is important to note that(需要注意的是)。删除这类冗余内容。删减堆叠的限定词:could potentially possibly(可能)may(可能)
引导语和聊天机器人残留。 Let's dive in(让我们深入探讨)、here's what you need to know(以下是你需要了解的内容)、without further ado(话不多说),以及粘贴的对话内容:I hope this helps(希望这对你有帮助)、Certainly!(当然!)、You're absolutely right!(你完全正确!)、Would you like me to…(你想让我……吗)、let me know(告诉我)。直接执行操作,不要提前宣告;删除聊天框架。
权威说服和格言式表述。 The real question is(真正的问题是)、at its core(从本质上讲)、what really matters(真正重要的是)、fundamentally(根本上);以及X is the language of Y(X是Y的语言)、X becomes a trap(X变成了陷阱)。这类表述给普通观点披上了仪式感的外衣。替换为其背后的具体主张。
模糊归因。 Experts argue(专家认为)、observers have noted(观察家指出)、industry reports suggest(行业报告显示) 但未提及来源。要么指明来源,要么删除该主张。同时注意知识截止日期的免责声明(as of my last update(截至我的最后更新)、while specific details are limited(虽然具体细节有限))和推测性补充(likely grew up(可能成长于)、it is believed that(据信)、maintains a low profile(保持低调))。直接说明未知信息,不要编造看似合理的内容填充空白。
冒号作为连接词。 冒号只在引出列表或示例时才合理。在句子中间使用冒号会暗示子句之间不存在的关系:If you're coming from traditional automation: instead of registering handlers, you describe conditions(如果你来自传统自动化领域:无需注册处理器,只需描述条件)。改写内容,使其无需这种框架就能表达核心观点。
格式特征。 对关键短语进行机械性的粗体标记;内嵌标题式的项目符号列表(
- **Performance:** …
);每个标题都使用标题大小写;装饰性表情符号;在应使用直引号的地方使用弯引号;通用的乐观结论(the future looks bright(未来一片光明)、exciting times lie ahead(激动人心的时刻即将到来))。

Two cut tests

两项删减测试

The catalog above names patterns. These two judge a sentence that trips none of them and still reads as machine-written. Both are falsifiable, and both end in a deletion.
Does it name a mechanism, or a feeling? The database stays close at hand, SQL you can read, types that follow your schema all describe a sensation the reader is supposed to have. The fix names what actually happens:
.toSQL()
returns the exact string sent to the database,
a column rename fails the build. Ask what the sentence tells the reader to do or know, then write that. If it can't be restated as a concrete instruction, fact, or number, cut it. Where the source supplies no mechanism, cutting is the only move available: never invent one to pass this test.
Could it appear unchanged in another project's documentation? Then it says nothing about this project, and it goes.
上面的列表列出了常见模式。这两项测试用于判断未触发任何特征但仍读起来像机器生成的句子。两项测试都可验证,且最终结果都是删除内容。
它描述的是机制,还是感受? The database stays close at hand(数据库触手可及)SQL you can read(易于阅读的SQL)types that follow your schema(遵循你的模式的类型) 都描述了读者应该产生的感受。修正方法是写出实际发生的情况:
.toSQL()
returns the exact string sent to the database(
.toSQL()
返回发送到数据库的精确字符串)
a column rename fails the build(列重命名会导致构建失败)。思考句子要告诉读者做什么或知道什么,然后写出这些内容。如果无法重述为具体的指令、事实或数字,就删除该句子。如果原文没有提供机制,唯一的处理方式就是删除;切勿自行编造机制来通过测试。
它能否原封不动地出现在另一个项目的文档中? 如果可以,说明它没有描述本项目的任何独特内容,应删除。

The em-dash rule

破折号规则

The finished rewrite contains no em dashes (—) and uses no en dashes (–) as sentence punctuation. Replace those marks, in rough order of preference, with a period, comma, parentheses, or a restructured sentence. A colon works too, but only where it introduces a list or an example, per the colon tell above; swapping an em dash for a mid-sentence colon trades one tell for another. Preserve legitimate numeric/date/page ranges by using a hyphen or writing "to" (
1914-1918
,
pp. 10 to 12
). Catch spaced em dashes (
) and double hyphens (
--
) used the same way. Before delivering, search the draft for
and
; any remaining en dash must be a legitimate range, and any em dash means the rewrite is not done. One exception: a user-supplied writing sample that uses em dashes overrides this rule, and then the mark is matched to the sample's frequency rather than banned.
最终改写内容不得包含破折号(—),也不得将短破折号(–)用作句子标点。按照以下优先级替换这些符号:句号、逗号、括号,或重构句子。冒号也可以使用,但只能用于引出列表或示例(符合上述冒号特征的要求);将句中破折号替换为冒号只是用一种AI特征替换另一种。保留合法的数字/日期/页码范围,使用连字符或“to”(如
1914-1918
pp. 10 to 12
)。注意空格破折号(
)和双连字符(
--
)的相同用法。交付前,在草稿中搜索
;剩余的短破折号必须是合法的范围,任何破折号都意味着改写未完成。唯一例外:如果用户提供的写作样本使用破折号,则此规则失效,此时应匹配样本的使用频率,而非禁用破折号。

What not to flag

无需标记的内容

Clean human writing trips several of these on its own. Do not gut legitimate prose:
  • Polish, formal vocabulary, or consistent style, because professionals and edited writers exist.
  • A single em dash, one however, one clipped emphatic sentence, or curly quotes alone. Editors and word processors produce all of these.
  • Bland or dry prose without the specific tells above, because dry is not the same as AI.
  • Quoted text, titles, proper names, or a phrase being discussed rather than used. Never rewrite inside those.
Lean toward leaving prose alone when you see hard-to-fake specifics (a real address, an odd quote), mixed or unresolved feelings, era-bound slang, genuine asides or self-corrections, and real variety in sentence length. Those are the fingerprints of a person.
优秀的人类写作也会触发上述部分特征。不要破坏合理的散文内容:
  • 精致、正式的词汇或一致的风格,因为专业人士和经过编辑的作者确实会使用这些。
  • 单个破折号、一个“however”、一个简短的强调句或单独的弯引号。编辑和文字处理器都会产生这些内容。
  • 没有上述特定特征的平淡或枯燥散文,因为枯燥不等于AI生成。
  • 引用文本、标题、专有名词,或被讨论而非使用的短语。切勿改写这些内容。
当你看到难以伪造的具体细节(真实地址、独特引用)、复杂或未解决的情绪、特定时代的俚语、真实的题外话或自我修正,以及句子长度的真实变化时,应倾向于保留原文。这些都是人类写作的特征。

Removing tells is half the job

去除特征只是一半工作

Prose with every tell stripped out and nothing put back reads as sterile, and sterile is its own signature. The catalog is the subtraction. This is what fills the space:
  • Take a position. React to a fact rather than weighing its pros and cons at equal length.
  • Vary the rhythm. A short sentence. Then a longer one that takes its time and earns the room. Uniform sentence length is a tell by itself.
  • Let it be uneven. Sections of matching length and paragraphs of matching shape look manufactured, because they are.
  • Use I where the register allows. First person is not unprofessional.
  • Say the specific thing. Not this is concerning but the concrete version the source already supports.
  • Allow mixed feelings. Impressive, and a little unsettling beats impressive.
None of this loosens the never-invent-facts rule at the top. Opinion, reaction, and unresolved feeling are voice, and you may add them. A name, number, date, or claim is fact, and you may not. In encyclopedic, technical, legal, or reference text, plain and neutral is the human voice, and this section barely applies.
去除所有AI特征但未补充内容的散文会显得生硬,而生硬本身也是一种特征。上面的列表是删减部分。以下是填补空白的方法:
  • 表明立场。 对事实做出反应,而非同等篇幅地权衡利弊。
  • 变换节奏。 先写一个短句,再写一个长句,慢慢展开并合理占用篇幅。统一的句子长度本身就是AI特征。
  • 允许内容不均。 长度匹配的章节和结构一致的段落看起来像是人工制造的,事实也确实如此。
  • 在符合风格的前提下使用第一人称“我”。 第一人称并非不专业。
  • 表述具体内容。 不要写this is concerning(这令人担忧),而是写出原文已支持的具体版本。
  • 允许复杂情绪。 Impressive, and a little unsettling(令人印象深刻,但也有点不安)impressive(令人印象深刻) 更好。
以上内容均不会放宽开头的“切勿编造事实”规则。观点、反应和未解决的情绪属于语气范畴,可以添加。姓名、数字、日期或主张属于事实范畴,绝对不能添加。在百科、技术、法律或参考类文本中,平实中立就是人类语气,本节内容基本不适用。

Process

处理流程

  1. Read the input and mark every instance of the tells above, then run the two cut tests over what survives.
  2. Write a draft rewrite: read it aloud in your head, vary sentence length, prefer concrete detail and plain constructions (is/are/has), hold the original's register and coverage, and give it the voice described in Removing tells is half the job.
  3. Ask three questions: what still makes this read as AI-generated?, does the draft state any fact, name, number, date, quote, or citation that isn't in the source?, and has the de-slopping left it sterile? Answer all three in a few blunt bullets. A fabrication is a defect even when it reads more human than the vague original it replaced.
  4. Revise into a final rewrite that fixes all three, carrying no em or en dashes.
  1. 阅读输入内容,标记所有上述AI特征,然后对剩余内容执行两项删减测试
  2. 撰写改写草稿:在脑海中大声朗读,变换句子长度,优先使用具体细节和平实结构(is/are/has),保持原文的风格和内容完整性,并赋予去除特征只是一半工作中描述的语气。
  3. 提出三个问题:哪些地方仍读起来像AI生成的?草稿中是否包含任何原文未提供的事实、姓名、数字、日期、引用或参考文献?去除冗余内容后是否显得生硬? 用几个直白的要点回答这三个问题。即使编造的内容比模糊的原文更像人类,编造也是缺陷。
  4. 修改为最终改写版本,解决上述三个问题,且不包含破折号或短破折号。

Hand off

交付方式

Write this section in the procedural register: one instruction per sentence, active voice, present tense, no metaphor.
This is the hand-off for text pasted into the conversation. Called by another skill or agent, none of it applies: deliver the final text alone and stop. Working from a file, deliver the summary and the path, not the rewrite itself.
What changed. Deliver, in order: the final rewrite (the main artifact), a short "what still read as AI" note listing the tells you caught when you asked what still reads as AI-generated, and a one-line summary of changes. Say so plainly if the audit turned up a fabrication you had to pull back out. If the user asked only for a review, skip the rewrite and report the located tells with line references instead.
Where it landed. When a writable filesystem is available and the source came from a file, write the rewrite back (or beside it), leaving code blocks, frontmatter, tables, data, and link targets untouched, and report the path; otherwise print the rewrite in a fenced code block so it copies cleanly.
Next. Name one move and stop. Rewritten a file in a repo? The change is uncommitted prose: offer to commit it (commitkit when installed, otherwise a plain commit). Reviewed rather than rewrote? The move is to apply the tells you listed, so re-run humankit on the draft once they've decided which to take. Rewrote text that came from the chat rather than a file? There's nothing to route to; say the draft is theirs to paste back and stop rather than inventing a next step.
本节采用流程化语气:每句一个指令,主动语态,现在时,无隐喻。
这是针对粘贴到对话中的文本的交付方式。如果是被其他技能或Agent调用,则不适用本节内容:仅交付最终文本即可。如果处理的是文件,只需交付摘要和文件路径,无需交付改写内容本身。
变更内容。 按以下顺序交付:最终改写版本(核心成果)、简短的**“仍存在AI痕迹的内容”说明(列出你在检查“哪些地方仍读起来像AI生成的”时发现的特征),以及一行变更摘要**。如果审计发现需要撤回的编造内容,应明确说明。如果用户仅要求检查,跳过改写步骤,而是报告发现的特征及行号。
交付位置。 如果有可写入的文件系统且源内容来自文件,将改写内容写回(或写入旁边的文件),保留代码块、前置元数据、表格、数据和链接目标不变,并报告文件路径;否则将改写内容放在围栏代码块中,以便轻松复制。
下一步操作。 提出一项操作后停止。在仓库中改写了文件?变更内容是未提交的散文:提供提交服务(已安装时使用commitkit,否则执行普通提交)。仅检查未改写?下一步是应用你列出的特征,所以等用户决定要处理哪些特征后,重新运行humankit处理草稿。改写的是聊天中的文本而非文件?无需跳转至其他工具:告知用户草稿已准备好,可自行粘贴使用,无需编造下一步操作。

Reference

参考资料

The pattern catalog derives from Wikipedia: Signs of AI writing, maintained by WikiProject AI Cleanup. The abstract-metaphor-noun list, the colon-as-connector tell, the two cut tests, and the voice section come from pstack's
unslop
skill
.
特征列表源自维基百科:AI写作的特征,由WikiProject AI Cleanup维护。抽象隐喻名词列表、冒号连接词特征、两项删减测试和语气部分来自pstack的
unslop
技能