| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 72 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 79.28% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1448 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "suddenly" | | 1 | "slowly" | | 2 | "really" | | 3 | "quickly" | | 4 | "completely" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 65.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1448 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "stomach" | | 1 | "flicked" | | 2 | "measured" | | 3 | "furrowing" | | 4 | "silence" | | 5 | "unreadable" | | 6 | "flicker" | | 7 | "tension" | | 8 | "shattered" | | 9 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 76 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 76 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 131 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 83 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1441 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 884 | | uniqueNames | 11 | | maxNameDensity | 0.68 | | worstName | "Lucien" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Carter | 1 | | Moreau | 1 | | Rory | 1 | | Eva | 3 | | Evan | 2 | | Lucien | 6 | | Ptolemy | 2 | | Paris | 2 | | Camden | 1 | | Three | 3 | | Aurora | 5 |
| | persons | | 0 | "Carter" | | 1 | "Moreau" | | 2 | "Rory" | | 3 | "Eva" | | 4 | "Evan" | | 5 | "Lucien" | | 6 | "Ptolemy" | | 7 | "Aurora" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 63.79% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like he'd stepped out of a magazin" | | 1 | "felt like another wall she hadn't known" |
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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 | 1441 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 131 | | matches | | 0 | "rationalise that decision" | | 1 | "explaining that justice" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 71 | | mean | 20.3 | | std | 20.17 | | cv | 0.994 | | sampleLengths | | 0 | 33 | | 1 | 50 | | 2 | 2 | | 3 | 9 | | 4 | 39 | | 5 | 5 | | 6 | 4 | | 7 | 26 | | 8 | 7 | | 9 | 45 | | 10 | 27 | | 11 | 44 | | 12 | 2 | | 13 | 49 | | 14 | 3 | | 15 | 22 | | 16 | 5 | | 17 | 11 | | 18 | 59 | | 19 | 5 | | 20 | 41 | | 21 | 3 | | 22 | 27 | | 23 | 19 | | 24 | 6 | | 25 | 23 | | 26 | 5 | | 27 | 11 | | 28 | 81 | | 29 | 5 | | 30 | 20 | | 31 | 8 | | 32 | 30 | | 33 | 2 | | 34 | 2 | | 35 | 47 | | 36 | 1 | | 37 | 30 | | 38 | 8 | | 39 | 6 | | 40 | 25 | | 41 | 4 | | 42 | 49 | | 43 | 36 | | 44 | 2 | | 45 | 27 | | 46 | 40 | | 47 | 34 | | 48 | 34 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 76 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 153 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 131 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 886 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.03611738148984198 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.007900677200902935 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 131 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 131 | | mean | 11 | | std | 10.79 | | cv | 0.981 | | sampleLengths | | 0 | 2 | | 1 | 19 | | 2 | 12 | | 3 | 19 | | 4 | 31 | | 5 | 2 | | 6 | 9 | | 7 | 7 | | 8 | 6 | | 9 | 26 | | 10 | 5 | | 11 | 4 | | 12 | 20 | | 13 | 6 | | 14 | 7 | | 15 | 8 | | 16 | 22 | | 17 | 15 | | 18 | 10 | | 19 | 13 | | 20 | 4 | | 21 | 6 | | 22 | 15 | | 23 | 23 | | 24 | 2 | | 25 | 28 | | 26 | 21 | | 27 | 3 | | 28 | 12 | | 29 | 6 | | 30 | 4 | | 31 | 5 | | 32 | 7 | | 33 | 4 | | 34 | 5 | | 35 | 6 | | 36 | 3 | | 37 | 24 | | 38 | 9 | | 39 | 12 | | 40 | 5 | | 41 | 15 | | 42 | 22 | | 43 | 4 | | 44 | 3 | | 45 | 27 | | 46 | 14 | | 47 | 5 | | 48 | 6 | | 49 | 14 |
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| 59.80% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.40458015267175573 | | totalSentences | 131 | | uniqueOpeners | 53 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 17.10% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 69 | | matches | | 0 | "She'd counted them every night" | | 1 | "He looked like he'd stepped" | | 2 | "Her hand froze on the" | | 3 | "She leaned her forehead against" | | 4 | "She'd had plenty of time" | | 5 | "she repeated, more to herself" | | 6 | "Her fingers worked the chain" | | 7 | "He was taller than she" | | 8 | "His heterochromatic eyes, one amber" | | 9 | "She stepped aside, acutely aware" | | 10 | "He crouched, offering his hand" | | 11 | "His gaze flicked up to" | | 12 | "She hadn't said it before" | | 13 | "He'd told her on their" | | 14 | "She'd taken it in stride," | | 15 | "She shut the door behind" | | 16 | "His expression revealed nothing." | | 17 | "He picked up a sheaf" | | 18 | "His mouth curved, but the" | | 19 | "She'd spent weeks memorising the" |
| | ratio | 0.507 | |
| 32.46% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 69 | | matches | | 0 | "She'd counted them every night" | | 1 | "Aurora Carter pressed her eye" | | 2 | "Lucien Moreau stood in the" | | 3 | "He looked like he'd stepped" | | 4 | "Her hand froze on the" | | 5 | "She leaned her forehead against" | | 6 | "The accusation stung more than" | | 7 | "She'd had plenty of time" | | 8 | "Lucien didn't do well with" | | 9 | "she repeated, more to herself" | | 10 | "Her fingers worked the chain" | | 11 | "The door swung open." | | 12 | "He was taller than she" | | 13 | "His heterochromatic eyes, one amber" | | 14 | "She stepped aside, acutely aware" | | 15 | "Ptolemy had never met Lucien," | | 16 | "He crouched, offering his hand" | | 17 | "The cat butted his palm" | | 18 | "His gaze flicked up to" | | 19 | "The word hung between them." |
| | ratio | 0.855 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 69 | | matches | | 0 | "Now it felt like another" | | 1 | "Now she couldn't decide whether" |
| | ratio | 0.029 | |
| 93.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 2 | | matches | | 0 | "She'd counted them every night for six months, the metallic clicks a ritual that kept the panic at bay." | | 1 | "His heterochromatic eyes, one amber and one black, swept over her in a single assessing glance that made her feel far too exposed." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 6 | | matches | | 0 | "she repeated, more to herself than to him" | | 1 | "He picked up, his brow furrowing" | | 2 | "Aurora grabbed, her fingers shaking as she scrolled to Eva's contact" | | 3 | "The words tumbled, defensive" | | 4 | "Something shifted, a flicker of pain quickly suppressed" | | 5 | "His voice remained, but his knuckles had gone white around the head of his cane" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 3 | | fancyTags | | 0 | "Eva had (have)" | | 1 | "she repeated (repeat)" | | 2 | "She pressed (press)" |
| | dialogueSentences | 72 | | tagDensity | 0.042 | | leniency | 0.083 | | rawRatio | 1 | | effectiveRatio | 0.083 | |