| 94.74% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 2 | | adverbTags | | 0 | "Aurora returned curtly [curtly]" | | 1 | "she asked finally [finally]" |
| | dialogueSentences | 28 | | tagDensity | 0.679 | | leniency | 1 | | rawRatio | 0.105 | | effectiveRatio | 0.105 | |
| 73.17% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1118 | | totalAiIsmAdverbs | 6 | | found | | 0 | | | 1 | | | 2 | | adverb | "reluctantly" | | count | 1 |
| | 3 | |
| | highlights | | 0 | "slightly" | | 1 | "softly" | | 2 | "reluctantly" | | 3 | "gently" |
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| 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1118 | | totalAiIsms | 28 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | |
| | highlights | | 0 | "pounding" | | 1 | "racing" | | 2 | "reminder" | | 3 | "warmth" | | 4 | "aligned" | | 5 | "familiar" | | 6 | "silk" | | 7 | "comforting" | | 8 | "amidst" | | 9 | "charged" | | 10 | "tension" | | 11 | "flickered" | | 12 | "intensity" | | 13 | "delve" | | 14 | "eyebrow" | | 15 | "comfortable" | | 16 | "charm" | | 17 | "echoed" | | 18 | "silence" | | 19 | "encounter" | | 20 | "depths" | | 21 | "unspoken" | | 22 | "dance" |
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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 | 59 | | matches | (empty) | |
| 21.79% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 5 | | narrationSentences | 59 | | filterMatches | (empty) | | hedgeMatches | | 0 | "tried to" | | 1 | "seemed to" | | 2 | "managed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 67 | | 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 | 1107 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 961 | | uniqueNames | 15 | | maxNameDensity | 0.73 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Carter | 1 | | Ptolemy | 2 | | Brick | 2 | | Lane | 2 | | Moreau | 1 | | East | 1 | | London | 3 | | French | 1 | | Westminster | 1 | | Bridge | 1 | | Lucien | 7 | | Eva | 3 | | Aurora | 7 | | Sighing | 1 | | Silence | 1 |
| | persons | | 0 | "Carter" | | 1 | "Ptolemy" | | 2 | "Moreau" | | 3 | "Lucien" | | 4 | "Eva" | | 5 | "Aurora" | | 6 | "Silence" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "East" | | 3 | "London" | | 4 | "Westminster" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 1 | | matches | | 0 | "as if choosing each word with care" |
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| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.71 | | wordCount | 1107 | | matches | | 0 | "not due to any sartorial inadequacy on Lucien’s part but his perpetually devil-may-care manner" | | 1 | "not quite sure where this path leads,” she said, matching his frankness, “but tonight I’m willing to find out" | | 2 | "neither backing away nor" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 67 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 27.68 | | std | 16.99 | | cv | 0.614 | | sampleLengths | | 0 | 43 | | 1 | 60 | | 2 | 29 | | 3 | 58 | | 4 | 11 | | 5 | 17 | | 6 | 45 | | 7 | 15 | | 8 | 52 | | 9 | 24 | | 10 | 23 | | 11 | 24 | | 12 | 17 | | 13 | 8 | | 14 | 12 | | 15 | 37 | | 16 | 5 | | 17 | 14 | | 18 | 61 | | 19 | 4 | | 20 | 14 | | 21 | 22 | | 22 | 25 | | 23 | 19 | | 24 | 51 | | 25 | 12 | | 26 | 23 | | 27 | 15 | | 28 | 20 | | 29 | 68 | | 30 | 17 | | 31 | 14 | | 32 | 42 | | 33 | 25 | | 34 | 22 | | 35 | 53 | | 36 | 42 | | 37 | 17 | | 38 | 15 | | 39 | 32 |
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| 99.32% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 59 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 163 | | matches | | 0 | "wasn’t expecting" | | 1 | "were comforting" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 67 | | ratio | 0.119 | | matches | | 0 | "His gaze was intense—as it always had been—but more so now with the twilight casting strange light across his heterochromatic eyes: one amber, one black." | | 1 | "Lucien was always good at that—revealing just enough without giving anything away." | | 2 | "She hadn’t expected this—certainly not now, and she wasn’t prepared for the punch of nostalgia and something sharper." | | 3 | "The research notes—Eva’s life’s work on the supernatural world—were comforting in their chaos, grounding her amidst the sudden whirlwind of his presence." | | 4 | "Acquaintances was a mild description for what had flickered between them—moments of fiery intensity ever hovering on the precipice of something more." | | 5 | "Her gaze lingered on the crooked line of his collar—not due to any sartorial inadequacy on Lucien’s part but his perpetually devil-may-care manner." | | 6 | "Outside, the city didn’t pause—life carried on along Brick Lane with its usual clamor—but in the cocoon of Aurora’s flat, time seemed to hold its breath." | | 7 | "They stood there, neither backing away nor stepping forward, caught in the shifting dance of shadows and light—a reminder of how things had once been, and perhaps, how they might be again." |
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| 90.91% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 978 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 46 | | adverbRatio | 0.04703476482617587 | | lyAdverbCount | 23 | | lyAdverbRatio | 0.023517382413087935 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 67 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 67 | | mean | 16.52 | | std | 7.16 | | cv | 0.433 | | sampleLengths | | 0 | 9 | | 1 | 14 | | 2 | 20 | | 3 | 15 | | 4 | 25 | | 5 | 20 | | 6 | 5 | | 7 | 24 | | 8 | 17 | | 9 | 25 | | 10 | 16 | | 11 | 11 | | 12 | 13 | | 13 | 4 | | 14 | 8 | | 15 | 12 | | 16 | 25 | | 17 | 15 | | 18 | 18 | | 19 | 34 | | 20 | 18 | | 21 | 6 | | 22 | 23 | | 23 | 24 | | 24 | 9 | | 25 | 8 | | 26 | 8 | | 27 | 11 | | 28 | 1 | | 29 | 15 | | 30 | 22 | | 31 | 5 | | 32 | 14 | | 33 | 19 | | 34 | 22 | | 35 | 20 | | 36 | 4 | | 37 | 14 | | 38 | 10 | | 39 | 12 | | 40 | 11 | | 41 | 14 | | 42 | 19 | | 43 | 26 | | 44 | 25 | | 45 | 12 | | 46 | 10 | | 47 | 13 | | 48 | 15 | | 49 | 20 |
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| 95.02% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5970149253731343 | | totalSentences | 67 | | uniqueOpeners | 40 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 57 | | matches | | 0 | "Ever since they’d parted ways" | | 1 | "Perhaps it was the brandy," |
| | ratio | 0.035 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 57 | | matches | | 0 | "She wasn’t expecting anyone, and" | | 1 | "she called out, her voice" | | 2 | "Her flat on Brick Lane" | | 3 | "She twisted her wrist out" | | 4 | "She fumbled with the deadbolts." | | 5 | "His gaze was intense—as it" | | 6 | "He leaned casually on his" | | 7 | "he drawled, his French accent" | | 8 | "Her reply was clipped, an" | | 9 | "He tilted his head slightly," | | 10 | "It was part of what" | | 11 | "She hadn’t expected this—certainly not" | | 12 | "He crossed the threshold, uninvited" | | 13 | "she retorted, trying to muster" | | 14 | "He chuckled softly, the sound" | | 15 | "He feigned innocence dramatically, his" | | 16 | "She crossed her arms over" | | 17 | "He arched an eyebrow, mirth" | | 18 | "He inclined his head, accepting" | | 19 | "she asked, shifting her tone" |
| | ratio | 0.596 | |
| 30.18% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 57 | | matches | | 0 | "Aurora Carter heard the insistent" | | 1 | "She wasn’t expecting anyone, and" | | 2 | "The cat protested with a" | | 3 | "she called out, her voice" | | 4 | "Her flat on Brick Lane" | | 5 | "She twisted her wrist out" | | 6 | "She fumbled with the deadbolts." | | 7 | "The room’s warmth spilled out" | | 8 | "Lucien Moreau stood there, his" | | 9 | "His gaze was intense—as it" | | 10 | "He leaned casually on his" | | 11 | "he drawled, his French accent" | | 12 | "Her reply was clipped, an" | | 13 | "He tilted his head slightly," | | 14 | "Lucien was always good at" | | 15 | "It was part of what" | | 16 | "She hadn’t expected this—certainly not" | | 17 | "He crossed the threshold, uninvited" | | 18 | "Aurora stepped back instinctively, eyes" | | 19 | "Lucien commented, glancing at the" |
| | ratio | 0.86 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 57 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 1 | | matches | | 0 | "The research notes—Eva’s life’s work on the supernatural world—were comforting in their chaos, grounding her amidst the sudden whirlwind of his presence." |
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| 19.74% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 4 | | matches | | 0 | "He feigned, his voice pure silk" | | 1 | "He arched, mirth glimmering softly through his amber eye" | | 2 | "she asked finally, her voice low, with an honest edge to it" | | 3 | "He hesitated, as if choosing each word with care" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 7 | | fancyTags | | 0 | "she called out (call out)" | | 1 | "he drawled (drawl)" | | 2 | "Lucien commented (comment)" | | 3 | "she retorted (retort)" | | 4 | "he interrupted (interrupt)" | | 5 | "he whispered (whisper)" | | 6 | "she agreed (agree)" |
| | dialogueSentences | 28 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0.583 | | effectiveRatio | 0.5 | |