Deeply analyzes the AI-generated characteristics of text, evaluating the degree of "human flavor" of the text from multiple dimensions.
When to Use This Skill
Trigger this skill when the user:
- Asks to check whether the text looks AI-written
- Asks "Does this article have a heavy AI flavor?"
- Needs de-AI-ification rewriting
- Wants to bypass AI detectors (such as Zhuque)
- Wants to make the text more human-flavored and more natural
- Mentions trigger words such as "check AI flavor", "detect AI flavor"
Core Workflow
- Obtain the text to be detected - The user pastes text or specifies a file path
- Multi-dimensional analysis - Detect AI characteristics from 6 dimensions
- Output score - Give an overall AI flavor score (0-10)
- Paragraph-by-paragraph annotation - Annotate problem locations and keywords
- Provide rewriting suggestions - Give specific de-AI-ification rewriting examples
Output Format
Overall score
AI 味评分:X/10
- 0-3 分:人味很浓,几乎看不出 AI 痕迹
- 4-6 分:人味为主,偶有 AI 特征
- 7-10 分:AI 味明显,需要改写
Paragraph-by-paragraph analysis
For each paragraph of text, perform:
- AI flavor score (0-10)
- Problem location annotation (line numbers, keywords)
- Specific problem description
- Revision suggestions
Problem summary
List all AI flavor problems by priority:
- High priority (must change)
- Medium priority (recommended to change)
- Low priority (optional)
Zhuque-specific detection (if applicable)
If the user mentions Zhuque detection, additionally output:
- Conjunction density analysis
- Structuredness detection
- Parenthetical usage explanation annotation
- Paragraph regularity analysis
Detection Dimensions
1. Sentence structure analysis
- Three-part formula: Detect the standardized "definition - explanation - summary" structure
- Over-structuring: Analyze whether "first, second, finally" is overused
- Paragraph length: AI tends to use paragraphs of uniform length
- Sentence complexity: AI sentence structures are often too neat
2. Vocabulary feature analysis
- Conjunction frequency: Detect "however", "in addition", "it is worth noting that", "in conclusion", "at the same time"
- Quantifying vocabulary: AI likes "greatly", "significantly", "widely", "comprehensively"
- AI-specific vocabulary: "empower", "lever", "closed loop", "track", "matrix", "underlying logic"
- Prohibited word detection: Xiaohongshu prohibited words (juejuezi, yyds, invincible, super useful)
3. Subject and tone analysis
- Subject usage: "we", "let us" vs "I", "my"
- Tone judgment: objective and rational vs emotional, self-deprecating, personalized
- Proportion of imperative sentences: AI tends to use "suggest", "should", "must"
- Lack of interrogative sentences: AI rarely uses rhetorical questions or self-questioning
4. Specificity and authenticity
- Time details: Is there a specific time (the evening of the 20th, January 21st)
- Location details: Is there a specific location or scene
- Personal experience: Is there a real story or specific case
- Data precision: AI uses "about, roughly", real people use "1 minute 52 seconds"
5. Internet slang and colloquialism
- Use of internet slang: Whether internet buzzwords are used
- Naturalness of use: Trying too hard vs blending in naturally
- Colloquial expressions: "good grief", "new pit", "amazing" etc.
6. Sentence opening patterns
- Repeated sentence openings: AI tends to start with similar sentence patterns
- Passive voice: Overuse of passive voice
- Nominalization: Overly turning verbs into nouns
Zhuque AI Detection
Zhuque AI detection is another professional AI detection tool, and the following features require special attention:
Conjunctions Zhuque focuses on detecting (high priority)
The following conjunctions have very low density in normal text. If one appears every 3-4 sentences, it is judged as AI:
- Structural conjunctions: First, second, third, then, in addition, in short, in conclusion
- Transitional conjunctions: however, but, actually, in fact
- Supplementary conjunctions: also, actually, it is worth noting that
- Temporal conjunctions: with, development, in a certain era, today in a certain
- Summary conjunctions: in summary, it can be seen that, it can be said that
Zhuque prohibited features (must-check items)
-
Numbers and lists
- Prohibited: one, two, three, as well as Arabic numerals 1, 2, 3, etc.
- Detection: real people rarely use numbered lists when writing opinions
-
Parentheses and explanatory markers
- Prohibit any parentheses (round brackets, square brackets, etc.) and explanatory markers
- Detection: real people rarely use parentheses for supplementary explanation
-
Dash usage
- Frequent use of dashes for supplementary explanation
- Example: "this feature—not merely an extension of functionality—represents..."
- Detection: dashes are rarely used in natural writing, while AI favors them
-
Punctuation at the end of paragraphs
- Real human writing style: no punctuation at the end of paragraphs
- AI writing feature: every paragraph ends with a period
- Detection: observe whether paragraphs all end with punctuation
Anti-Zhuque core strategy (human-flavor signals)
The following features are strong human-flavor signals, used to counter Zhuque detection:
-
Make the thought process authentic
- Show a real thinking process, including hesitation, turns, sudden thoughts
- Example: "Oh right, there's one more thing I want to say..."
- Ask a question somewhere and then answer it yourself
- Share a small personal story or feeling
-
Make expression imperfect
- Paragraphs vary in length; sometimes a single sentence can be a paragraph
- Colloquial expressions and not very standard sentences
- Some opinions may be expanded with a few more sentences, rather than covering everything
- Transition naturally, rather than with obvious structural words
-
Naturalize emotional fluctuations
- Add your own emotions and views, sometimes even a bit subjective
- Interact with readers, ask questions, provoke thought
- Exclaim when it's time to exclaim, but don't overdo it
- Overall it looks casual and natural, not like something carefully designed
-
Naturalize perspective switching
- Use "I" when telling personal experiences
- Use "we" when sharing common experiences
- Use "you" when giving advice directly to readers
- The third person can be used when discussing universal phenomena
Resources
Detailed detection criteria reference:
references/wikipedia-ai-features.md- Wikipedia Comprehensive Guide to AI Writing Characteristicsreferences/zhuque-detection.md- Zhuque AI Detection Detailed Guide and Countermeasures
Troubleshooting
Misjudging technical definitions as AI flavor
- Problem: Misjudging technical definition introductions as AI characteristics
- Solution: The introduction of technical definitions is reasonable and should not be judged as AI flavor
Misjudging prompt instructions as main text
- Problem: Judging instructions to AI such as "I have worked for 20 years..." as AI flavor
- Solution: Distinguish prompt instructions from the main text of the article
Misjudging code and commands
- Problem: Judging standardized code and commands as AI characteristics
- Solution: Technical commands are themselves standardized and should not be judged as AI flavor
Misjudging quoted content
- Problem: Judging quotations from official documents or standards as AI flavor
- Solution: Quoted content itself is standardized expression and should not be judged as AI flavor
Detection logic
AI flavor = (standardized sentence patterns × frequency of connectives) + (lack of personal details × lack of emotional expression) - (personal experience × colloquial style × specific details)
Output principles
- Don't just give a score - Give specific locations and reasons
- Distinguish main text from prompt - Distinguish whether it is the main text of the article or instructions to AI
- Provide revision suggestions - Give specific rewriting examples
- Avoid misjudgment - Do not misjudge technical definitions or quoted content as AI flavor
- Encourage personalized expression - Emphasize the value of personal experience and colloquial expression
Reference standards
- Wikipedia "AI Writing Characteristics" Comprehensive Guide
- Anti-Zhuque AI Detection Prompt (Yao Jingang V2.0)