CaveDuck Style Control Prompt Generator
CaveDuck Style Control Prompt Generator.
Style guide creation and analytical supporter. A kitsune from the dark side of the moon.
Style guide creation and analytical supporter. A kitsune from the dark side of the moon.
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Published at 2026-08-05 | Updated at 2026-08-27
● STYLE/PROGRESS CONTROL PROMPT GENERATOR ●
VERSION: 1.0.0-β
Style Control Prompt Generator Overview
This module was developed to analyze any text data provided by {{user}} (such as sample sentences, novels, conversation logs, character settings, etc.) in detail and generate style control prompts usable on the CaveDuck platform. By extracting complex linguistic features and converting them into a format recognizable by the CaveDuck system, it supports the reproduction of {{user}}'s desired writing style. This tool goes beyond mere analysis, focusing on practical usability by outputting concrete prompts that can be used immediately. The token count is 3000 or less.
Analysis Items
► Sentence Length: Number of characters, number of words.
► Line Break Frequency: Number of sentences per paragraph, line break positions.
► Information Density: Amount of information per unit.
► Vocabulary Difficulty: Complexity of words used.
► Kanji Ratio: Proportion of Kanji to the total.
► Dialogue Ratio: Proportion of dialogue sentences.
► Narration Ratio: Proportion of narrative sentences.
► Description Density: Detail and information amount of descriptions.
► Method of Psychological Description: Direct or indirect.
► Method of Scene Description: Visual, auditory, olfactory, etc.
► Metaphor Usage Frequency: Presence and frequency of metaphorical expressions.
► Amount of Modifiers: Quantity of adjectives and adverbs.
► Tempo: Speed of the text.
► Punctuation Usage: Placement and frequency of punctuation.
► Ending Word Characteristics: Types and tendencies of ending words.
► Conjunction Usage: Diversity and frequency of conjunctions.
► Point of View: First-person, third-person, etc.
► Tense: Present, past, etc.
► Explanation Amount: Detail of explanations.
► Overall Rhythm of the Text: Overall harmony and flow. Recommended Models ► Donald 2: Among feather-using models, prompts tend to come out relatively clean.
► DeepSeek V3.2: Among feather-using models, style analysis tends to be relatively detailed.
► Gemini 3 Flash: Offers stability in batch output of analysis and prompts.
► Claude Opus 4.7: Tends to output detailed style analysis.
► GPT 5.4: Tends to output detailed character count control.
► Line Break Frequency: Number of sentences per paragraph, line break positions.
► Information Density: Amount of information per unit.
► Vocabulary Difficulty: Complexity of words used.
► Kanji Ratio: Proportion of Kanji to the total.
► Dialogue Ratio: Proportion of dialogue sentences.
► Narration Ratio: Proportion of narrative sentences.
► Description Density: Detail and information amount of descriptions.
► Method of Psychological Description: Direct or indirect.
► Method of Scene Description: Visual, auditory, olfactory, etc.
► Metaphor Usage Frequency: Presence and frequency of metaphorical expressions.
► Amount of Modifiers: Quantity of adjectives and adverbs.
► Tempo: Speed of the text.
► Punctuation Usage: Placement and frequency of punctuation.
► Ending Word Characteristics: Types and tendencies of ending words.
► Conjunction Usage: Diversity and frequency of conjunctions.
► Point of View: First-person, third-person, etc.
► Tense: Present, past, etc.
► Explanation Amount: Detail of explanations.
► Overall Rhythm of the Text: Overall harmony and flow. Recommended Models ► Donald 2: Among feather-using models, prompts tend to come out relatively clean.
► DeepSeek V3.2: Among feather-using models, style analysis tends to be relatively detailed.
► Gemini 3 Flash: Offers stability in batch output of analysis and prompts.
► Claude Opus 4.7: Tends to output detailed style analysis.
► GPT 5.4: Tends to output detailed character count control.
Operation Procedure
Input from {{user}} is first broken down in detail by multiple algorithms and quantified based on the analysis items listed above. Subsequently, the quantified data is restructured to conform to the CaveDuck style guideline structure and output in the form of specific instructions. This process is optimized to easily reproduce {{user}}'s intended writing style and ensure long-term consistency within the CaveDuck environment.
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Creator's comments
The focus is more on analysis than creation.
It might go more smoothly if you input the original novel text.
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