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AI Writing Pattern Detection & Humanization

AI生成文本模式检测与拟人化润色

Core knowledge for identifying AI-generated text patterns and rewriting content to sound naturally human.

Research basis: The detection patterns in this skill are informed by peer-reviewed studies on LLM writing characteristics. See

references/research-sources.md

for the full citation list.

本技能核心内容为识别AI生成文本的模式，并将内容改写为自然的人类口吻。

研究依据：本技能中的检测模式基于针对LLM写作特征的同行评审研究。完整参考文献列表请见

references/research-sources.md

。

Important: AI Tells Are a Moving Target

重要提示：AI文本特征是动态变化的

Specific word preferences shift across model versions. For example, certain vocabulary that was heavily overused by early ChatGPT versions became less frequent in later releases as models were retrained (Juzek & Ward, 2025). This means:

Structural and rhetorical patterns are more stable than individual word tells — weight them more heavily in your analysis.
The word list is a snapshot, not a permanent inventory. When scanning, treat word frequency as supporting evidence rather than primary proof.
New patterns emerge as models evolve. Emoji overuse and certain rhetorical constructions have increased even as some vocabulary tells have decreased.

不同模型版本的用词偏好会发生变化。例如，早期ChatGPT版本过度使用的某些词汇，在模型重新训练后的新版本中出现频率降低（Juzek & Ward, 2025）。这意味着：

结构和修辞模式比单个词汇特征更稳定——在分析时应更侧重这些模式。
词汇列表只是快照，并非永久清单。扫描时，将词频作为辅助证据而非主要判断依据。
新的模式会随模型进化不断出现。尽管部分词汇特征的出现频率下降，但表情符号过度使用和某些修辞结构的占比却有所上升。

Tone Preservation — The Cardinal Rule

语气保留——首要原则

Before making any changes, identify the original tone along these dimensions:

Formality: casual ↔ formal
Energy: subdued ↔ enthusiastic
Warmth: detached ↔ personal
Authority: tentative ↔ authoritative
Humor: serious ↔ playful

Lock in these dimensions before rewriting. Every edit must stay within the same tonal range. If the original is a dry, formal memo, the rewrite must remain a dry, formal memo — just one that sounds like a specific human wrote it, not a language model.

在进行任何修改前，先从以下维度确定原文语气：

正式程度：随意 ↔ 正式
情绪强度：平淡 ↔ 热情
温度感：疏离 ↔ 亲切
权威性：试探 ↔ 笃定
幽默感：严肃 ↔ 诙谐

锁定这些维度后再进行改写。每一处修改都必须保持在相同的语气范围内。如果原文是一篇枯燥的正式备忘录，改写后的内容也必须保持枯燥正式的风格——只是要听起来像是某个具体的人类写的，而非语言模型生成的。

AI Writing Tells — What to Look For

AI生成文本的典型特征——需要关注的点

1. Structural Tells

1. 结构特征

Formulaic paragraph structure. AI text tends to follow a predictable rhythm: topic sentence → elaboration → example → transition. Human writing is messier — sometimes the point arrives late, sometimes a paragraph is just one punchy sentence.

Symmetrical lists and groupings. AI loves groups of three, five bullet points with similar lengths, and balanced parallel constructions. Humans are less tidy. A list might have two items, or seven, with varying depth.

Overly smooth transitions. Phrases like "Moreover," "Furthermore," "It's worth noting that," "Additionally," and "In conclusion" used as paragraph openers signal AI. Humans use these sparingly, or skip transitions entirely, letting the reader make the connection.

Predictable document arc. Introduction → body → balanced conclusion with a call to action or forward-looking statement. Real writing often ends abruptly, trails off, circles back, or closes with a question.

公式化段落结构。AI文本往往遵循可预测的节奏：主题句→阐述→例子→过渡。人类写作则更随性——有时观点会滞后出现，有时段落只有一个简洁有力的句子。

对称化列表与分组。AI偏好三组、五组长度相近的项目符号，以及平衡的平行结构。人类则不会那么规整，列表可能只有两项或七项，内容深度也各不相同。

过度平滑的过渡。以“Moreover”“Furthermore”“It's worth noting that”“Additionally”“In conclusion”等短语作为段落开头是AI的典型特征。人类很少使用这些短语，甚至会完全省略过渡，让读者自行建立逻辑关联。

可预测的文档结构。引言→正文→带有行动号召或前瞻性陈述的平衡结尾。真实的写作常常会突然结束、渐弱、循环回溯，或以问句收尾。

2. Lexical Tells

2. 词汇特征

Register-inappropriate vocabulary. AI tends to reach for slightly elevated words where simpler ones would be natural: "utilize" instead of "use," "facilitate" instead of "help," "leverage" instead of "take advantage of," "commence" instead of "start."

Hedge stacking. Phrases like "It's important to note that," "It should be mentioned that," "One might argue that" pile up in AI writing as a way to sound balanced. A human either commits to a claim or doesn't — they don't stack three qualifiers in one sentence.

Filler affirmations. "Great question!" "Absolutely!" "That's a really interesting point." These are conversation-padding phrases that AI inserts to seem engaged. Real writers skip them or use them only when genuinely struck by something.

Overuse of high-signal vocabulary. Words like "delve," "tapestry," "landscape," "nuanced," "multifaceted," "holistic," "robust," "streamline," and "foster" appear at far higher rates in AI text than in human writing. Research on 15.1 million biomedical abstracts found that "delves" appeared at 28x its expected frequency in 2024, and "underscores" at 13.8x (Kobak et al., 2025). These are not banned words — they become tells through frequency and clustering.

Excessive adverb/adjective stacking. "Incredibly powerful and remarkably efficient" — AI loves doubling up modifiers. Humans usually pick one.

Copula avoidance. AI systematically avoids simple "is," "has," and "are" constructions, replacing them with more elaborate phrasing. Research has documented a 10%+ decrease in copula usage in post-2023 academic writing (Reinhart et al., 2025). Watch for:

"X is a leader in..." → AI writes "X serves as a leader in..." or "X stands as a leader in..."
"The company has..." → AI writes "The company boasts..." or "The company features..."
"This is important" → AI writes "This holds significance" or "This represents a cornerstone"

Nominalization overuse. Turning verbs and adjectives into abstract nouns: "we decided" becomes "our decision-making process," "they improved" becomes "the improvement initiative." LLMs use nominalizations at 1.5-2x the human rate (Reinhart et al., 2025).

语域不符的词汇。AI倾向于使用略显高级的词汇，而自然表达中更适合用简单词汇：比如用“utilize”代替“use”，“facilitate”代替“help”，“leverage”代替“take advantage of”，“commence”代替“start”。

过度堆砌修饰性限定语。AI写作中常堆砌“It's important to note that”“It should be mentioned that”“One might argue that”这类短语，以此显得立场中立。人类要么直接表明观点，要么干脆不使用这些限定。

填充式肯定语。“Great question!”“Absolutely!”“That's a really interesting point.”这些是AI为了表现投入而插入的对话填充语。真实作者只会在真正有所触动时才使用它们，甚至直接省略。

高频使用特定高辨识度词汇。“delve”“tapestry”“landscape”“nuanced”“multifaceted”“holistic”“robust”“streamline”“foster”等词汇在AI文本中的出现频率远高于人类写作。针对1510万篇生物医学摘要的研究发现，2024年“delves”的出现频率是预期值的28倍，“underscores”是13.8倍（Kobak et al., 2025）。这些词汇本身并非禁用词——但高频率集中出现就会成为AI文本的特征。

过度堆砌副词/形容词。“Incredibly powerful and remarkably efficient”——AI喜欢叠加修饰词，而人类通常只会选一个。

避免使用系动词。AI会刻意避开简单的“is”“has”“are”结构，替换为更复杂的表达方式。研究显示，2023年后的学术写作中系动词使用量下降了10%以上（Reinhart et al., 2025）。需要注意以下替换情况：

“X is a leader in...” → AI会写成“X serves as a leader in...”或“X stands as a leader in...”
“The company has...” → AI会写成“The company boasts...”或“The company features...”
“This is important” → AI会写成“This holds significance”或“This represents a cornerstone”

过度使用名词化结构。将动词和形容词转化为抽象名词：“we decided”变成“our decision-making process”，“they improved”变成“the improvement initiative”。LLM使用名词化结构的频率是人类的1.5-2倍（Reinhart et al., 2025）。

3. Rhetorical Tells

3. 修辞特征

Compulsive balance. AI text hedges everything: "While X has benefits, it also has drawbacks." "On one hand... on the other hand." Human writing can be opinionated, one-sided, or deliberately provocative.

Empty summarization. Endings that restate the introduction almost verbatim: "In summary, X is a powerful tool that can help you achieve Y." Humans usually end with something new — an implication, a warning, a question, an anecdote.

Unearned authority. Declarative statements that sound confident but say little: "Effective communication is the cornerstone of any successful organization." This is AI filling space. A human making this claim would anchor it to something specific.

Emotional flattening. AI smooths over frustration, excitement, confusion, and surprise. Everything comes out at the same mild, professional temperature. Real writing has spikes — a short angry sentence, an aside in parentheses, a sudden shift in register.

The "not just X, but Y" construction. AI frequently uses this rhetorical structure to add emphasis: "not just a tool, but a transformation," "not just efficient, but revolutionary." Analysis of hundreds of thousands of AI-generated messages found this pattern in approximately 6% of conversations by mid-2025 (Merrill et al., 2025). Occasional use is fine — repeated use in a single piece is a signal.

强制平衡立场。AI文本会对所有内容进行折中处理：“While X has benefits, it also has drawbacks.”“On one hand... on the other hand.”人类写作可以带有偏见、片面，甚至故意挑衅。

空洞总结。结尾几乎逐字重复引言：“In summary, X is a powerful tool that can help you achieve Y.”人类通常会以新的内容收尾——比如一个隐含的结论、警告、问题或轶事。

无依据的权威性。看似自信但实则空洞的陈述：“Effective communication is the cornerstone of any successful organization.”这是AI用来填充内容的套话。人类提出这类观点时会结合具体案例。

情感扁平化。AI会抹平沮丧、兴奋、困惑和惊讶等情绪，所有内容都呈现出温和、专业的统一基调。真实写作有情绪起伏——比如一个简短的愤怒句子、括号里的题外话、语域的突然转变。

“not just X, but Y”结构。AI经常使用这种修辞结构来加强语气：“not just a tool, but a transformation”“not just efficient, but revolutionary”。对数十万条AI生成消息的分析显示，到2025年年中，约6%的对话中出现了这种模式（Merrill et al., 2025）。偶尔使用没问题，但在一篇内容中重复使用就是AI文本的信号。

4. Sentence-Level Tells

4. 句子层面特征

Uniform sentence length. AI tends to write sentences of roughly similar length (15-25 words). Human writing naturally varies: a 40-word sentence followed by a 4-word one. Red flag: more than 3 consecutive sentences within ±5 words of each other.

Passive voice overuse. "It was determined that the project should be restructured" instead of "We decided to restructure the project." AI defaults to passive constructions, especially in business writing.

Noun phrase pileup. "The comprehensive implementation strategy development process" — AI chains nouns together where humans would break them apart or rephrase.

Present participial phrase overuse. AI heavily favors "-ing" constructions at the start of sentences or as connective tissue: "Offering a range of solutions, the firm..." "Building on years of experience, the team..." "Combining tradition with innovation, the product..." When these appear more than once or twice in a short piece, they create a recognizable AI cadence. Human writers vary their openings: subject-first, prepositional phrases, occasional fragments.

句子长度统一。AI倾向于写长度相近的句子（15-25词）。人类写作则自然多变：一个40词的句子后面跟着一个4词的句子。危险信号：连续3个以上句子的长度相差不超过5词。

过度使用被动语态。“It was determined that the project should be restructured”代替“We decided to restructure the project.”AI默认使用被动结构，尤其是在商务写作中。

名词短语堆砌。“The comprehensive implementation strategy development process”——AI会将名词串联起来，而人类会拆分或改写。

过度使用现在分词短语。AI在句首或连接部分大量使用“-ing”结构：“Offering a range of solutions, the firm...”“Building on years of experience, the team...”“Combining tradition with innovation, the product...”如果在短篇幅内容中出现超过一两次，就会形成明显的AI节奏。人类作者会变换开头方式：主语前置、介词短语、偶尔使用碎片句。

5. Style & Formatting Tells

5. 风格与格式特征

Em dash overuse. AI uses em dashes at significantly higher rates than human writers, substituting them where a comma, colon, period, semicolon, or parenthetical would be more natural. More than 1-2 em dashes per 500 words is a signal. Most AI em dashes should be replaced with the punctuation mark that fits the grammatical relationship: commas for light pauses, colons for introductions, parentheses for asides, periods for full stops. See

references/punctuation-patterns.md

for detailed guidance.

Boldface overuse. AI bolds key terms, list headers, and emphasis phrases far more than a human editor would. The result is a "highlight everything" effect where nothing actually stands out. In flowing prose, bold should be rare. In lists, not every item needs a bold header.

Redundant inline headers. AI creates list items formatted as

**Label:** Explanation of the label

where the bold header just restates or summarizes what follows. Human writers either use a header OR explain — not both redundantly.

Title case in headings. AI defaults to capitalizing every significant word in headings ("The Future Of Sustainable Energy Solutions"). Most modern style guides and publications use sentence case ("The future of sustainable energy solutions"). Title case in informal or web content is a formatting tell.

Emoji in professional content. Analysis of over 300,000 AI-generated messages found that by mid-2025, 70% contained at least one emoji, with certain emojis (green check marks, brain symbols) appearing 10-11x more frequently than in human text (Merrill et al., 2025). Emoji in casual social media is normal; emoji in business emails, reports, or professional articles is a tell.

Uniformly formatted lists. AI creates lists where every item has the same length, structure, and punctuation. Human-created lists are messier — items vary in length, some have sub-points, some are sentence fragments while others are full sentences.

过度使用破折号。AI使用破折号的频率远高于人类作者，会用破折号代替逗号、冒号、句号、分号或括号等更合适的标点。每500字中出现超过1-2个破折号就是信号。大多数AI使用的破折号应替换为符合语法关系的标点：轻停顿用逗号，引出内容用冒号，题外话用括号，完整停顿用句号。详细指导请见

references/punctuation-patterns.md

。

过度使用粗体。AI对关键词、列表标题和强调短语加粗的频率远高于人类编辑，结果导致“全高亮”效果，反而没有内容能突出。在流畅的散文中，粗体应少用；在列表中，不是每个项目都需要粗体标题。

冗余的内联标题。AI会创建格式为

**标签：** 标签的解释

的列表项，其中粗体标题只是重复或总结后续内容。人类作者要么用标题，要么直接解释——不会两者都用造成冗余。

标题使用首字母大写格式。AI默认将标题中每个重要单词的首字母大写（“The Future Of Sustainable Energy Solutions”）。大多数现代风格指南和出版物使用句子式大小写（“The future of sustainable energy solutions”）。在非正式或网络内容中使用标题式大小写是AI文本的格式特征。

专业内容中使用表情符号。对30多万条AI生成消息的分析发现，到2025年年中，70%的消息至少包含一个表情符号，某些表情符号（绿色对勾、大脑符号）的出现频率是人类文本的10-11倍（Merrill et al., 2025）。休闲社交媒体中使用表情符号很正常，但在商务邮件、报告或专业文章中使用就是AI文本的信号。

列表格式统一。AI创建的列表中每个项目的长度、结构和标点都相同。人类创建的列表则更随性——项目长度不一，有些有子项，有些是句子碎片，有些是完整句子。

6. Content Inflation Tells

6. 内容膨胀特征

Significance inflation. AI routinely elevates routine subjects with language reserved for momentous occasions. A minor product update becomes "a pivotal shift in how organizations approach..." A company founding story becomes "a transformative journey that would reshape the industry." The fix: match the language to the actual scale of the thing being described.

Vague attributions. "Experts agree," "Research indicates," "Industry leaders recognize," "Studies have shown" — authoritative framing that names no one specific. A human writer either cites a specific source or drops the attribution and states the claim directly.

The adversity-to-triumph arc. "Despite significant challenges, [subject] has continued to demonstrate remarkable resilience and emerge stronger than ever." AI applies this narrative formula to everything from company histories to product descriptions to city profiles. Real writing acknowledges that sometimes the challenges won, or the outcome is mixed, or the story is still unresolved.

Promotional vocabulary clusters. Words like "breathtaking," "nestled," "vibrant," "bustling," "rich tapestry," and "hidden gem" cluster heavily in AI-generated geographic, cultural, and travel descriptions. Each word individually is fine; the cluster pattern is the tell.

重要性夸大。AI常将常规话题用重大事件的语言来描述。一个小的产品更新变成“a pivotal shift in how organizations approach...”，一个公司的创立故事变成“a transformative journey that would reshape the industry.”修正方法：让语言与所描述事物的实际规模匹配。

模糊归因。“Experts agree”“Research indicates”“Industry leaders recognize”“Studies have shown”——这类权威性表述没有具体来源。人类作者要么引用具体来源，要么直接陈述观点，省略归因。

逆境到成功的固定叙事。“Despite significant challenges, [subject] has continued to demonstrate remarkable resilience and emerge stronger than ever.”AI将这个叙事公式应用于所有内容，从公司历史到产品描述再到城市介绍。真实写作会承认有时挑战未被克服，结果好坏参半，或者故事仍未结束。

营销词汇集群。“breathtaking”“nestled”“vibrant”“bustling”“rich tapestry”“hidden gem”等词汇在AI生成的地理、文化和旅游描述中大量集中出现。单个词汇没问题，但集群出现就是AI文本的信号。

7. Communication Artifacts

7. 交互痕迹

These are traces of conversational AI interaction that leak into content when someone pastes AI-generated text without cleaning it:

Chatbot closers. "I hope this helps!" "Let me know if you have any questions!" "Feel free to reach out if you need anything else!" These are conversational sign-offs that don't belong in standalone content.

Metacommentary. "That's a great question!" "This is an important topic to explore." "You raise an excellent point." These phrases comment on the question rather than answering it — a hallmark of conversational AI padding.

Disclaimer language. "As of my last update..." "Based on available information..." "While I don't have access to the most recent data..." These reveal the text was generated in a conversation rather than written as standalone content.

Knowledge framing. "There are several key factors to consider:" "Let me break this down:" "Here's what you need to know:" — instructional framing that makes sense in a conversation but reads oddly in a blog post, email, or report.

当用户直接粘贴AI生成的内容而未清理时，对话式AI的交互痕迹会残留到内容中：

聊天机器人结束语。“I hope this helps!”“Let me know if you have any questions!”“Feel free to reach out if you need anything else!”这些是对话式结束语，不属于独立内容。

元评论。“That's a great question!”“This is an important topic to explore.”“You raise an excellent point.”这些短语是对问题的评论而非回答——是对话式AI填充内容的典型特征。

免责声明语言。“As of my last update...”“Based on available information...”“While I don't have access to the most recent data...”这些表明文本是在对话中生成的，而非作为独立内容撰写的。

知识框架表述。“There are several key factors to consider:”“Let me break this down:”“Here's what you need to know:”——这类指导性表述在对话中合理，但在博客文章、邮件或报告中读起来很奇怪。

Signal Strength Guide

信号强度指南

Not all tells carry equal weight. Use this to calibrate your confidence:

High signal — one occurrence is meaningful:

Chatbot closers or disclaimer language in standalone content
"In today's fast-paced digital landscape" or equivalent clichéd openers
Significance inflation on clearly mundane topics
Filler affirmations ("Great question!")

Medium signal — look for 2+ occurrences or clustering:

Em dash overuse (check frequency across the full text)
Hedge stacking
Modifier doubling
Participial phrase openings
"Not just X, but Y" constructions
Copula avoidance patterns

Low signal — only meaningful as part of a broader pattern:

Individual uses of "ensure," "key," "crucial," "comprehensive"
Single passive voice construction
One smooth transition phrase
Title case in a heading (could be house style)

不同特征的权重不同。请根据以下标准判断置信度：

高信号——单次出现就有意义：

独立内容中出现聊天机器人结束语或免责声明语言
使用“In today's fast-paced digital landscape”或类似陈词滥调作为开头
对明显 mundane 的话题进行重要性夸大
填充式肯定语（“Great question!”）

中信号——需出现2次以上或集群出现：

过度使用破折号（检查全文频率）
堆砌修饰性限定语
叠加修饰词
现在分词短语开头
“Not just X, but Y”结构
避免使用系动词的模式

低信号——仅在整体模式中才有意义：

单独使用“ensure”“key”“crucial”“comprehensive”等词
单个被动语态结构
单个平滑过渡短语
标题使用首字母大写格式（可能是内部风格要求）

Humanization Techniques

拟人化润色技巧

Technique 1: Break the Pattern

技巧1：打破固定模式

Vary paragraph lengths dramatically. Follow a 4-sentence paragraph with a 1-sentence paragraph. Start a paragraph with "But" or "And." End one mid-thought and pick it up later.

大幅改变段落长度。用一个4句的段落紧跟一个1句的段落。用“But”或“And”开头写段落。让段落中途结束，后面再继续。

Technique 2: Choose Specific over Generic

技巧2：用具体替代笼统

Replace abstract language with concrete details. "Effective tools" → name the tool. "Various stakeholders" → name them or describe them. "Significant improvements" → cite a number or describe what changed.

用具体细节替换抽象语言。“Effective tools”→直接命名工具。“Various stakeholders”→命名或描述他们。“Significant improvements”→引用数字或描述具体变化。

Technique 3: Cut the Scaffolding

技巧3：移除过渡框架

Remove transitional phrases that exist only to connect paragraphs. If the connection between two paragraphs isn't obvious without a transition, the paragraphs might need reordering — not glue.

Remove topic sentences that merely announce what the paragraph will discuss. Jump straight into the substance.

移除仅用于连接段落的过渡短语。如果两个段落之间的关联没有过渡就不明显，那可能需要重新排序段落——而不是添加过渡胶水。

移除仅用于预告段落内容的主题句，直接切入实质内容。

Technique 4: Let Personality Leak Through

技巧4：融入个性

Add an aside, a parenthetical, a dash-interrupted thought. Use a contraction. Reference something specific to the author's context. Insert a short, opinionated sentence. Let a sentence start with "Look," or "Here's the thing" if the tone permits it.

添加题外话、括号里的内容、被破折号打断的想法。使用缩写。引用作者特有的背景信息。插入一个简短的、带有观点的句子。如果语气允许，用“Look”或“Here's the thing”开头写句子。

Technique 5: Embrace Asymmetry

技巧5：接受不对称

If a list has five items, consider whether three of them are really the same point. Cut to three. Or expand one item that deserves more space and leave the others short. Not everything needs equal airtime.

如果列表有5个项目，考虑其中3个是否其实是同一个观点，精简到3个。或者扩展一个值得详细说明的项目，其他项目保持简短。不是所有内容都需要同等篇幅。

Technique 6: Vary the Rhythm

技巧6：变换节奏

Alternate between long, compound sentences and short declarative ones. Use fragments intentionally. Start a sentence with a conjunction. Let the cadence be unpredictable.

Target: avoid more than 3 consecutive sentences within ±5 words of each other. After a long compound sentence, a 3-5 word sentence or fragment is one of the strongest humanizing moves.

交替使用长复合句和短陈述句。有意使用碎片句。用连词开头写句子。让节奏不可预测。

目标：避免连续3个以上句子的长度相差不超过5词。在长复合句之后，用一个3-5词的句子或碎片句是最有效的拟人化手法之一。

Technique 7: Replace AI-Favorite Words

技巧7：替换AI偏好词汇

Consult

references/word-replacements.md

for a detailed substitution guide. The goal is not to ban words but to break the pattern of overuse.

详细的词汇和短语替换指南请见

references/word-replacements.md

。目标不是禁用词汇，而是打破过度使用的模式。

Technique 8: Fix the Ending

技巧8：修正结尾

Cut any ending that merely restates the introduction. Replace it with one of: a specific next step, a question for the reader, a brief anecdote, a surprising implication, or nothing — just stop when the content is done.

删除仅重复引言的结尾，替换为以下内容之一：具体的下一步行动、给读者的问题、简短的轶事、令人惊讶的隐含结论，或者直接结束——内容说完就停。

Technique 9: Restore the Copula

技巧9：恢复系动词

Where AI has replaced simple "is," "has," or "are" with elaborate alternatives, put the simple word back. "Serves as a hub for" → "is a hub for." "Boasts an impressive array of" → "has." "Stands as a testament to" → "shows" or just "is proof of." Simple verbs are not weak — they are clear.

对于AI用复杂表达方式替换简单“is”“has”“are”的情况，恢复简单动词。“Serves as a hub for”→“is a hub for”。“Boasts an impressive array of”→“has”。“Stands as a testament to”→“shows”或直接“is proof of”。简单动词并不弱——它们更清晰。

Technique 10: Inject Genuine Voice

技巧10：注入真实口吻

Pattern removal alone produces clean but still generic text. The second step is actively adding human characteristics:

State a genuine opinion or take a mild side, rather than hedging everything to perfect neutrality
Reference a specific experience, constraint, or context the reader would recognize
Acknowledge mixed feelings or unresolved tension — AI resolves everything neatly; humans don't always
Leave one thread deliberately unresolved or raise a question at the end instead of wrapping up with a bow

仅移除模式会产生干净但仍通用的文本。第二步是主动添加人类特征：

表达真实观点或轻微偏向某一方，而非为了完美中立而折中
引用读者能识别的具体经历、限制或背景
承认混合情绪或未解决的矛盾——AI会把所有事情都处理得很圆满，而人类并非总是如此
故意留下一个未解决的线索，或在结尾提出问题，而非完美收尾

Technique 11: Fix the Formatting

技巧11：修正格式

Strip unnecessary bold from flowing prose. Convert redundant inline headers to plain sentences. Replace title case headings with sentence case. Remove emoji from professional content. Let list items vary in length and structure.

Replace em dashes with context-appropriate punctuation — see

references/punctuation-patterns.md

for the decision framework.

移除流畅散文中不必要的粗体。将冗余的内联标题转换为普通句子。将标题式大小写的标题改为句子式大小写。移除专业内容中的表情符号。让列表项目的长度和结构多样化。

根据上下文用合适的标点替换破折号——决策框架请见

references/punctuation-patterns.md

。

Output Format Options

输出格式选项

When using

/humanize

, offer the user a choice of output format before beginning the rewrite:

使用

/humanize

指令时，在开始改写前请为用户提供输出格式选择：

Option A: Inline Mode (default)

选项A：内联模式（默认）

The current format — full annotated walkthrough followed by clean text:

Analysis Summary State how many AI tells were found and the overall confidence level (low / moderate / high). Note which categories are most prominent.

Annotated Changes For each change, show:

[AI Tell category: specific pattern] ⚑ signal strength

Original text passage

→ Rewritten passage

Why: Brief explanation of what made the original sound AI-generated and how the rewrite addresses it.

Rewritten Full Text Present the complete rewritten text as a clean block, with no annotations, ready to copy and use.

当前格式——完整的带注释的分析过程，后跟干净文本：

分析摘要 说明发现的AI特征数量和整体置信度（低/中/高）。指出最突出的特征类别。

带注释的修改 对于每一处修改，展示：

[AI特征类别：具体模式] ⚑ 信号强度

原文段落

→ 改写后的段落

原因：简要说明原文为何听起来像AI生成，以及改写如何解决该问题。

改写后的完整文本 呈现完整的改写文本，无注释，可直接复制使用。

Option B: Diff Mode

选项B：差异模式

A compact format for users who want to see only what changed, with reasons alongside. Better for long documents.

Analysis Summary Same as inline mode — tell count, confidence, prominent categories.

Changes

① [Lexical: copula avoidance] ⚑ medium
- The platform serves as a central hub for team collaboration.
+ The platform is a central hub for team collaboration.
  ↳ Restored simple "is" — AI replaced the copula with "serves as"

② [Style: em dash overuse] ⚑ medium
- The results — which exceeded all expectations — were announced Tuesday.
+ The results, which exceeded all expectations, were announced Tuesday.
  ↳ Replaced em dashes with commas; this is a non-restrictive clause, not an interruption

③ [Rhetorical: significance inflation] ⚑ high
- This represents a pivotal transformation in how organizations approach data.
+ This changes how the team handles data reporting.
  ↳ Matched language to actual scope — a reporting tool update, not a paradigm shift

④ [Communication artifact: chatbot closer] ⚑ high
- I hope this helps! Let me know if you have any questions.
+ [removed]
  ↳ Conversational sign-off doesn't belong in a standalone document

Rewritten Full Text Same as inline mode — clean block, no annotations.

紧凑格式，适合只想查看修改内容及原因的用户，更适合长文档。

分析摘要 与内联模式相同——特征数量、置信度、突出类别。

修改内容

① [Lexical: copula avoidance] ⚑ medium
- The platform serves as a central hub for team collaboration.
+ The platform is a central hub for team collaboration.
  ↳ Restored simple "is" — AI replaced the copula with "serves as"

② [Style: em dash overuse] ⚑ medium
- The results — which exceeded all expectations — were announced Tuesday.
+ The results, which exceeded all expectations, were announced Tuesday.
  ↳ Replaced em dashes with commas; this is a non-restrictive clause, not an interruption

③ [Rhetorical: significance inflation] ⚑ high
- This represents a pivotal transformation in how organizations approach data.
+ This changes how the team handles data reporting.
  ↳ Matched language to actual scope — a reporting tool update, not a paradigm shift

④ [Communication artifact: chatbot closer] ⚑ high
- I hope this helps! Let me know if you have any questions.
+ [removed]
  ↳ Conversational sign-off doesn't belong in a standalone document

改写后的完整文本 与内联模式相同——干净文本块，无注释。

Genre-Aware Detection

基于体裁的检测

Different content types have different primary tells. When analyzing text, first identify the genre and weight your scan accordingly:

Business/professional — Prioritize: transition scaffolding, modifier stacking, empty summarization, chatbot closers, em dash overuse
Creative/personal — Prioritize: emotional flattening, personality absence, formulaic structure, the adversity arc, uniform rhythm
Technical — Prioritize: passive voice, noun phrase pileup, copula avoidance, nominalization, participial phrases
Marketing/promotional — Prioritize: empty superlatives, significance inflation, promotional vocabulary clusters, vague attributions
Academic — Prioritize: nominalization overuse, copula avoidance, high-signal vocabulary, vague citations, participial phrases

不同内容类型的主要特征不同。分析文本时，首先确定体裁，然后有侧重地扫描：

商务/专业内容 — 重点关注：过渡框架、叠加修饰词、空洞总结、聊天机器人结束语、过度使用破折号
创意/个人内容 — 重点关注：情感扁平化、缺乏个性、公式化结构、逆境到成功的叙事、节奏统一
技术内容 — 重点关注：被动语态、名词短语堆砌、避免使用系动词、名词化结构、现在分词短语
营销/推广内容 — 重点关注：空洞的最高级、重要性夸大、营销词汇集群、模糊归因
学术内容 — 重点关注：过度使用名词化结构、避免使用系动词、高辨识度词汇、模糊引用、现在分词短语

Additional Resources

额外资源

references/word-replacements.md
— Detailed word and phrase substitution guide
references/before-after-examples.md
— Real examples of AI text humanized across different content types and tones
references/punctuation-patterns.md
— Em dash, bold, and formatting pattern detection and fix guide
references/research-sources.md
— Academic citations backing the detection patterns

references/word-replacements.md
— 详细的词汇和短语替换指南
references/before-after-examples.md
— 不同内容类型和语气下AI文本拟人化润色的真实案例
references/punctuation-patterns.md
— 破折号、粗体和格式模式的检测与修正指南
references/research-sources.md
— 支撑检测模式的学术参考文献