| 49.06% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 4 | | adverbTags | | 0 | "Aurora said finally [finally]" | | 1 | "Eva's expression softened slightly [slightly]" | | 2 | "Aurora asked softly [softly]" | | 3 | "their fingers brushing briefly [briefly]" |
| | dialogueSentences | 53 | | tagDensity | 0.321 | | leniency | 0.642 | | rawRatio | 0.235 | | effectiveRatio | 0.151 | |
| 85.03% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1336 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "quickly" | | 1 | "slightly" | | 2 | "softly" | | 3 | "really" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 28.89% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1336 | | totalAiIsms | 19 | | found | | | highlights | | 0 | "familiar" | | 1 | "calculating" | | 2 | "crystal" | | 3 | "flickered" | | 4 | "weight" | | 5 | "mechanical" | | 6 | "warmth" | | 7 | "silence" | | 8 | "unspoken" | | 9 | "flicker" | | 10 | "navigate" | | 11 | "whisper" | | 12 | "glistening" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "weight of words/silence" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
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| | highlights | | 0 | "the weight of unspoken words" | | 1 | "hung in the air" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 57 | | matches | (empty) | |
| 92.73% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 57 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1330 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 37.58% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 934 | | uniqueNames | 8 | | maxNameDensity | 2.25 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 21 | | Camus | 1 | | Raven | 2 | | Nest | 2 | | Silas | 2 | | Eva | 19 | | Marcus | 1 | | London | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Silas" | | 2 | "Eva" | | 3 | "Marcus" |
| | places | | | globalScore | 0.376 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 51 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared beside them, wiping a glass with mechanical precision" |
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| 49.62% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.504 | | wordCount | 1330 | | matches | | 0 | "not just her university life but also the memories of an abusive relationship" | | 1 | "not wanting the moment to end but knowing it couldn't last forever" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 91 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 25.58 | | std | 20.81 | | cv | 0.814 | | sampleLengths | | 0 | 60 | | 1 | 1 | | 2 | 28 | | 3 | 68 | | 4 | 3 | | 5 | 59 | | 6 | 7 | | 7 | 51 | | 8 | 33 | | 9 | 15 | | 10 | 78 | | 11 | 26 | | 12 | 33 | | 13 | 17 | | 14 | 21 | | 15 | 2 | | 16 | 26 | | 17 | 34 | | 18 | 10 | | 19 | 4 | | 20 | 59 | | 21 | 4 | | 22 | 34 | | 23 | 9 | | 24 | 17 | | 25 | 3 | | 26 | 7 | | 27 | 68 | | 28 | 4 | | 29 | 16 | | 30 | 59 | | 31 | 13 | | 32 | 43 | | 33 | 2 | | 34 | 7 | | 35 | 56 | | 36 | 4 | | 37 | 1 | | 38 | 33 | | 39 | 25 | | 40 | 20 | | 41 | 43 | | 42 | 35 | | 43 | 2 | | 44 | 22 | | 45 | 4 | | 46 | 40 | | 47 | 22 | | 48 | 21 | | 49 | 22 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 57 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 162 | | matches | (empty) | |
| 17.27% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 91 | | ratio | 0.044 | | matches | | 0 | "Her eyes, once bright with mischief, held something harder now—calculating, watchful." | | 1 | "Aurora nodded, memories flooding back—late-night debates in cramped student flats, Marcus's condescending lectures about the futility of idealism, the way Eva had always been the one to cut through his rhetoric with brutal honesty." | | 2 | "\"I did.\" A flicker of something—pride, perhaps, or shame—crossed her face." | | 3 | "Eva flinched, and for a moment Aurora saw the girl she'd once known—the one who'd stayed up all night talking about justice and fairness, who'd believed in the inherent goodness of people despite everything." |
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| 95.02% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 941 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 43 | | adverbRatio | 0.04569606801275239 | | lyAdverbCount | 17 | | lyAdverbRatio | 0.018065887353878853 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 14.62 | | std | 10.63 | | cv | 0.727 | | sampleLengths | | 0 | 28 | | 1 | 32 | | 2 | 1 | | 3 | 20 | | 4 | 8 | | 5 | 11 | | 6 | 20 | | 7 | 11 | | 8 | 26 | | 9 | 3 | | 10 | 8 | | 11 | 36 | | 12 | 15 | | 13 | 7 | | 14 | 33 | | 15 | 18 | | 16 | 14 | | 17 | 19 | | 18 | 7 | | 19 | 8 | | 20 | 10 | | 21 | 20 | | 22 | 24 | | 23 | 24 | | 24 | 22 | | 25 | 4 | | 26 | 13 | | 27 | 20 | | 28 | 14 | | 29 | 3 | | 30 | 18 | | 31 | 3 | | 32 | 2 | | 33 | 10 | | 34 | 16 | | 35 | 34 | | 36 | 10 | | 37 | 4 | | 38 | 42 | | 39 | 17 | | 40 | 4 | | 41 | 11 | | 42 | 23 | | 43 | 8 | | 44 | 1 | | 45 | 13 | | 46 | 4 | | 47 | 3 | | 48 | 5 | | 49 | 2 |
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| 62.64% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.42857142857142855 | | totalSentences | 91 | | uniqueOpeners | 39 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 56 | | matches | | 0 | "It was the man sitting" | | 1 | "Her eyes, once bright with" | | 2 | "She wore a tailored blazer" | | 3 | "She'd been walking home from" | | 4 | "She hadn't expected to find" | | 5 | "His hazel eyes, shadowed by" | | 6 | "He'd watched Aurora grow from" | | 7 | "He'd also watched Eva transform" | | 8 | "His voice carried that particular" | | 9 | "She paused, searching for the" | | 10 | "She'd changed her name on" | | 11 | "They sat in silence for" | | 12 | "She thought about the flat" | | 13 | "she asked, not wanting the" |
| | ratio | 0.25 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 56 | | matches | | 0 | "The first thing Aurora noticed" | | 1 | "It was the man sitting" | | 2 | "The name slipped out before" | | 3 | "The woman looked up, and" | | 4 | "Time had been kinder to" | | 5 | "Eva's dark hair now threaded" | | 6 | "Her eyes, once bright with" | | 7 | "She wore a tailored blazer" | | 8 | "Aurora's voice sounded foreign to" | | 9 | "She'd been walking home from" | | 10 | "She hadn't expected to find" | | 11 | "Eva studied her for a" | | 12 | "Recognition flickered across her face," | | 13 | "Aurora asked, sliding onto the" | | 14 | "The wood creaked under her" | | 15 | "Eva gestured to her drink" | | 16 | "Silas appeared beside them, wiping" | | 17 | "His hazel eyes, shadowed by" | | 18 | "He'd watched Aurora grow from" | | 19 | "He'd also watched Eva transform" |
| | ratio | 0.964 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 7 | | matches | | 0 | "Eva's dark hair now threaded with premature silver, cut in that sharp bob that framed her face like a blade." | | 1 | "Eva studied her for a long moment, those sharp eyes taking in the worn jacket, the delivery uniform, the small crescent scar on her left wrist that peeked out f…" | | 2 | "Recognition flickered across her face, quickly replaced by something that might have been concern, or perhaps just curiosity." | | 3 | "He'd also watched Eva transform from a bright-eyed law student into someone who moved through the world like a shark, always hunting, always calculating." | | 4 | "Aurora looked down at her hands, remembering the night she'd packed a single bag and fled to London, leaving behind not just her university life but also the me…" | | 5 | "Aurora noticed the expensive watch on Eva's wrist, the subtle signs of wealth that screamed success, and wondered when her friend had become so polished, so rem…" | | 6 | "Eva flinched, and for a moment Aurora saw the girl she'd once known—the one who'd stayed up all night talking about justice and fairness, who'd believed in the …" |
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| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 1 | | matches | | 0 | "Aurora said finally, the words tumbling out before she could cage them" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 53 | | tagDensity | 0.113 | | leniency | 0.226 | | rawRatio | 0.167 | | effectiveRatio | 0.038 | |