| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "Aurora said softly [softly]" |
| | dialogueSentences | 30 | | tagDensity | 0.533 | | leniency | 1 | | rawRatio | 0.063 | | effectiveRatio | 0.063 | |
| 80.54% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1542 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "suddenly" | | 1 | "softly" | | 2 | "really" | | 3 | "very" | | 4 | "slowly" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 35.15% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1542 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "familiar" | | 1 | "rhythmic" | | 2 | "warmth" | | 3 | "efficient" | | 4 | "navigating" | | 5 | "ensure" | | 6 | "silence" | | 7 | "profound" | | 8 | "effortless" | | 9 | "encounter" | | 10 | "perfect" | | 11 | "weight" | | 12 | "unspoken" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 86 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 86 | | 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 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1537 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 52 | | wordCount | 1271 | | uniqueNames | 10 | | maxNameDensity | 1.57 | | worstName | "Aurora" | | maxWindowNameDensity | 3 | | worstWindowName | "Aurora" | | discoveredNames | | Soho | 2 | | Carter | 1 | | Raven | 1 | | Nest | 4 | | London | 3 | | Yu-Fei | 1 | | Aurora | 20 | | Cardiff | 2 | | Eva | 15 | | Silas | 3 |
| | persons | | 0 | "Carter" | | 1 | "Raven" | | 2 | "Yu-Fei" | | 3 | "Aurora" | | 4 | "Eva" | | 5 | "Silas" |
| | places | | 0 | "Soho" | | 1 | "Nest" | | 2 | "London" | | 3 | "Cardiff" |
| | globalScore | 0.713 | | windowScore | 0.667 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 5 | | matches | | 0 | "light that seemed to swallow the edges of the room" | | 1 | "looked like armor, and her hair was pulle" | | 2 | "felt like they might give way if she st" | | 3 | "looked like she had never had to worry ab" | | 4 | "looked like a person who existed in the s" |
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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 | 1537 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 100 | | matches | | 0 | "knew that profile" | | 1 | "realized that the" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 41.54 | | std | 24.11 | | cv | 0.58 | | sampleLengths | | 0 | 98 | | 1 | 50 | | 2 | 83 | | 3 | 13 | | 4 | 28 | | 5 | 58 | | 6 | 59 | | 7 | 47 | | 8 | 15 | | 9 | 60 | | 10 | 3 | | 11 | 67 | | 12 | 37 | | 13 | 35 | | 14 | 52 | | 15 | 25 | | 16 | 34 | | 17 | 42 | | 18 | 45 | | 19 | 27 | | 20 | 50 | | 21 | 12 | | 22 | 81 | | 23 | 58 | | 24 | 18 | | 25 | 61 | | 26 | 34 | | 27 | 52 | | 28 | 22 | | 29 | 55 | | 30 | 25 | | 31 | 10 | | 32 | 43 | | 33 | 4 | | 34 | 2 | | 35 | 42 | | 36 | 90 |
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| 72.62% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 8 | | totalSentences | 86 | | matches | | 0 | "was tired" | | 1 | "was pulled" | | 2 | "was styled" | | 3 | "been left" | | 4 | "been consumed" | | 5 | "been broken" | | 6 | "was gone" | | 7 | "been forged" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 198 | | matches | | 0 | "were still steaming" | | 1 | "was polishing" | | 2 | "was breathing" | | 3 | "were looking" | | 4 | "was navigating" | | 5 | "wasn't finding" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 2 | | flaggedSentences | 6 | | totalSentences | 100 | | ratio | 0.06 | | matches | | 0 | "She was tired in a way that sleep wouldn't fix—a bone-deep weariness that came from twelve hours of navigating London’s labyrinthine streets on a bicycle, dodging black cabs and delivery vans to ensure Yu-Fei’s orders arrived while they were still steaming." | | 1 | "He didn't say anything—he never felt the need to fill the silence with trivialities—but he gave a singular, slow nod of recognition." | | 2 | "It was a booth tucked away near the back, shadowed by one of the many old maps that lined the walls—a topographical relic of a London that no longer existed." | | 3 | "Eva didn’t gasp; she didn't even smile." | | 4 | "Aurora looked at their joined hands—the polished professional and the girl who had learned to fight for every inch of ground." | | 5 | "For a moment, they weren't two successful women in a London bar; they were just two girls from Cardiff, lost in the fog, looking for a way home." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1283 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, crescent-shaped scar" |
| | adverbCount | 43 | | adverbRatio | 0.03351519875292284 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.006235385814497272 | |
| 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 | 15.37 | | std | 9.49 | | cv | 0.618 | | sampleLengths | | 0 | 35 | | 1 | 26 | | 2 | 37 | | 3 | 9 | | 4 | 41 | | 5 | 14 | | 6 | 14 | | 7 | 12 | | 8 | 22 | | 9 | 21 | | 10 | 13 | | 11 | 12 | | 12 | 16 | | 13 | 28 | | 14 | 30 | | 15 | 4 | | 16 | 11 | | 17 | 15 | | 18 | 29 | | 19 | 2 | | 20 | 13 | | 21 | 4 | | 22 | 28 | | 23 | 15 | | 24 | 6 | | 25 | 5 | | 26 | 9 | | 27 | 7 | | 28 | 33 | | 29 | 3 | | 30 | 20 | | 31 | 20 | | 32 | 12 | | 33 | 15 | | 34 | 10 | | 35 | 13 | | 36 | 14 | | 37 | 10 | | 38 | 25 | | 39 | 27 | | 40 | 25 | | 41 | 15 | | 42 | 10 | | 43 | 11 | | 44 | 23 | | 45 | 9 | | 46 | 33 | | 47 | 9 | | 48 | 18 | | 49 | 10 |
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| 36.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.28 | | totalSentences | 100 | | uniqueOpeners | 28 | |
| 86.58% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 77 | | matches | | 0 | "Instead, a look of profound," | | 1 | "Slowly, she reached for the" |
| | ratio | 0.026 | |
| 32.99% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 77 | | matches | | 0 | "She shook her umbrella, her" | | 1 | "She was tired in a" | | 2 | "He was polishing a highball" | | 3 | "He looked up, his hazel" | | 4 | "He didn't say anything—he never" | | 5 | "He moved with that characteristic," | | 6 | "he asked, his voice a" | | 7 | "She moved toward the small" | | 8 | "It was a booth tucked" | | 9 | "She was alone, a glass" | | 10 | "She wore a trench coat" | | 11 | "She knew that profile." | | 12 | "She knew the way that" | | 13 | "It was a phantom sensation," | | 14 | "She walked toward the booth," | | 15 | "She felt heavy, her movements" | | 16 | "It was a polished voice," | | 17 | "She sat down across from" | | 18 | "It was a heavy silence," | | 19 | "She meant it to be" |
| | ratio | 0.468 | |
| 11.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 77 | | matches | | 0 | "The rain in Soho didn't" | | 1 | "Aurora Carter pushed through the" | | 2 | "The transition was always a" | | 3 | "She shook her umbrella, her" | | 4 | "She was tired in a" | | 5 | "Silas was behind the bar," | | 6 | "He was polishing a highball" | | 7 | "He looked up, his hazel" | | 8 | "He didn't say anything—he never" | | 9 | "He moved with that characteristic," | | 10 | "he asked, his voice a" | | 11 | "Aurora replied, pulling her damp" | | 12 | "She moved toward the small" | | 13 | "It was a booth tucked" | | 14 | "A woman sat there." | | 15 | "She was alone, a glass" | | 16 | "She wore a trench coat" | | 17 | "The air in her lungs" | | 18 | "She knew that profile." | | 19 | "She knew the way that" |
| | ratio | 0.896 | |
| 64.94% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 77 | | matches | | 0 | "Even in the dim, moody" |
| | ratio | 0.013 | |
| 48.52% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 7 | | matches | | 0 | "The rain in Soho didn't fall so much as it drifted, a fine, pervasive mist that turned the pavement into a dark mirror and clung to the eyelashes of everyone un…" | | 1 | "The transition was always a sensory shock: the sudden warmth, the smell of old paper, cedarwood, and the faint, sharp tang of gin, and the low, amber light that…" | | 2 | "She was tired in a way that sleep wouldn't fix—a bone-deep weariness that came from twelve hours of navigating London’s labyrinthine streets on a bicycle, dodgi…" | | 3 | "It was a booth tucked away near the back, shadowed by one of the many old maps that lined the walls—a topographical relic of a London that no longer existed." | | 4 | "Instead, a look of profound, unsettling confusion washed over her face, as if she were looking at a photograph that had been left in the sun too long, the featu…" | | 5 | "The delivery bike, the cramped flat above the bar, the quiet, observant man behind the counter who knew her name but nothing of her soul." | | 6 | "She found nothing but a calm, impenetrable intelligence, a coolness that had been forged in a very specific kind of fire." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 4 | | matches | | 0 | "he asked, his voice a low rumble that anchored the room" | | 1 | "The name escaped, a ghost of a sound" | | 2 | "Eva said, her voice regaining its footing" | | 3 | "Aurora said, her voice steady" |
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| 83.33% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 2 | | fancyTags | | 0 | "Eva whispered (whisper)" | | 1 | "Aurora interrupted (interrupt)" |
| | dialogueSentences | 30 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.133 | | effectiveRatio | 0.133 | |