| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 41 | | tagDensity | 0.244 | | leniency | 0.488 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.61% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 878 | | totalAiIsmAdverbs | 2 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
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| | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 54.44% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 878 | | totalAiIsms | 8 | | found | | 0 | | | 1 | | | 2 | | | 3 | | word | "down her spine" | | count | 1 |
| | 4 | | | 5 | | | 6 | |
| | highlights | | 0 | "flicked" | | 1 | "unreadable" | | 2 | "silence" | | 3 | "down her spine" | | 4 | "effortless" | | 5 | "tension" | | 6 | "pulse" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 69 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 69 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 100 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 872 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 674 | | uniqueNames | 8 | | maxNameDensity | 1.48 | | worstName | "Aurora" | | maxWindowNameDensity | 3 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 10 | | Ptolemy | 5 | | Eva | 4 | | French-accented | 1 | | Three | 3 | | Damn | 1 | | French | 2 | | Lucien | 9 |
| | persons | | 0 | "Aurora" | | 1 | "Ptolemy" | | 2 | "Eva" | | 3 | "Lucien" |
| | places | (empty) | | globalScore | 0.758 | | windowScore | 0.667 | |
| 91.86% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 1 | | matches | | 0 | "tasted like bergamot and unresolved histo" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 872 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 100 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 17.1 | | std | 14.02 | | cv | 0.82 | | sampleLengths | | 0 | 44 | | 1 | 43 | | 2 | 49 | | 3 | 10 | | 4 | 12 | | 5 | 6 | | 6 | 51 | | 7 | 11 | | 8 | 15 | | 9 | 33 | | 10 | 3 | | 11 | 51 | | 12 | 6 | | 13 | 14 | | 14 | 16 | | 15 | 20 | | 16 | 18 | | 17 | 13 | | 18 | 3 | | 19 | 23 | | 20 | 6 | | 21 | 3 | | 22 | 22 | | 23 | 2 | | 24 | 33 | | 25 | 6 | | 26 | 10 | | 27 | 3 | | 28 | 20 | | 29 | 32 | | 30 | 10 | | 31 | 7 | | 32 | 4 | | 33 | 18 | | 34 | 13 | | 35 | 26 | | 36 | 46 | | 37 | 14 | | 38 | 6 | | 39 | 8 | | 40 | 7 | | 41 | 19 | | 42 | 11 | | 43 | 1 | | 44 | 6 | | 45 | 8 | | 46 | 22 | | 47 | 38 | | 48 | 16 | | 49 | 12 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 69 | | matches | (empty) | |
| 83.04% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 114 | | matches | | 0 | "was settling" | | 1 | "was, standing" |
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| 28.57% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 100 | | ratio | 0.04 | | matches | | 0 | "Three sharp raps—too precise to be Eva, too impatient to be a delivery." | | 1 | "She could still taste the bitterness of their last conversation—his clipped words, the way he'd turned his back on her in that alley behind Silas’ bar." | | 2 | "He surveyed the cluttered flat with a slow sweep of his gaze—the stacks of Eva’s research, the half-empty mugs littering every surface, the single bed barely visible through the open bedroom door." | | 3 | "The scent of him wrapped around her—bergamot, leather, the faintest trace of demonic ozone." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 682 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.030791788856304986 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005865102639296188 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 100 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 100 | | mean | 8.72 | | std | 6.62 | | cv | 0.759 | | sampleLengths | | 0 | 20 | | 1 | 13 | | 2 | 11 | | 3 | 16 | | 4 | 10 | | 5 | 17 | | 6 | 16 | | 7 | 15 | | 8 | 18 | | 9 | 10 | | 10 | 6 | | 11 | 6 | | 12 | 4 | | 13 | 2 | | 14 | 4 | | 15 | 26 | | 16 | 21 | | 17 | 11 | | 18 | 11 | | 19 | 4 | | 20 | 4 | | 21 | 10 | | 22 | 16 | | 23 | 3 | | 24 | 3 | | 25 | 19 | | 26 | 32 | | 27 | 6 | | 28 | 5 | | 29 | 9 | | 30 | 11 | | 31 | 5 | | 32 | 4 | | 33 | 4 | | 34 | 7 | | 35 | 5 | | 36 | 6 | | 37 | 8 | | 38 | 4 | | 39 | 11 | | 40 | 2 | | 41 | 3 | | 42 | 21 | | 43 | 2 | | 44 | 4 | | 45 | 2 | | 46 | 3 | | 47 | 5 | | 48 | 14 | | 49 | 3 |
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| 67.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.41 | | totalSentences | 100 | | uniqueOpeners | 41 | |
| 52.08% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 64 | | matches | | | ratio | 0.016 | |
| 88.75% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 64 | | matches | | 0 | "She set her mug down," | | 1 | "His charcoal suit was impeccable," | | 2 | "he said, her name smooth" | | 3 | "He inclined his head." | | 4 | "She could still taste the" | | 5 | "She should say no." | | 6 | "He surveyed the cluttered flat" | | 7 | "She crossed her arms" | | 8 | "He leaned his cane against" | | 9 | "He turned to face her" | | 10 | "Her voice cracked on the" | | 11 | "He took a step closer." | | 12 | "His gloved hand lifted, hovered" | | 13 | "Her breath caught." | | 14 | "she asked, deliberately not looking" | | 15 | "She glanced up." | | 16 | "His mouth twisted" | | 17 | "His gaze dropped to her" | | 18 | "She exhaled shakily." | | 19 | "His gloved hand came up" |
| | ratio | 0.328 | |
| 30.31% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 64 | | matches | | 0 | "The knock came just as" | | 1 | "The tabby flicked his ears" | | 2 | "She set her mug down," | | 3 | "The deadbolts clicked open one" | | 4 | "Lucien stood on the threshold," | | 5 | "The amber and black of" | | 6 | "His charcoal suit was impeccable," | | 7 | "he said, her name smooth" | | 8 | "Aurora’s fingers tightened on the" | | 9 | "He inclined his head." | | 10 | "The silence stretched, brittle." | | 11 | "She could still taste the" | | 12 | "Ptolemy wound between her ankles," | | 13 | "Lucien’s gaze dropped to the" | | 14 | "She should say no." | | 15 | "Something was wrong." | | 16 | "Aurora stepped back." | | 17 | "Lucien moved past her, the" | | 18 | "He surveyed the cluttered flat" | | 19 | "She crossed her arms" |
| | ratio | 0.859 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 64 | | matches | (empty) | | ratio | 0 | |
| 37.04% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 4 | | matches | | 0 | "Ptolemy chose that moment to leap onto the coffee table, sending a stack of Eva’s notes fluttering to the floor." | | 1 | "Three months of telling herself she was better off without him, three months of burying the memory of his hands in her hair, his voice murmuring French endearme…" | | 2 | "Aurora closed the last inch between them, her lips meeting his in a kiss that tasted like bergamot and unresolved history." | | 3 | "Lucien’s arms came around her, pulling her flush against him, his cane clattering forgotten to the floor." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 41 | | tagDensity | 0.098 | | leniency | 0.195 | | rawRatio | 0.25 | | effectiveRatio | 0.049 | |