| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 25 | | adverbTagCount | 2 | | adverbTags | | 0 | "The words came too [too]" | | 1 | "He stepped back [back]" |
| | dialogueSentences | 86 | | tagDensity | 0.291 | | leniency | 0.581 | | rawRatio | 0.08 | | effectiveRatio | 0.047 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1718 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 73.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1718 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "flicker" | | 1 | "eyebrow" | | 2 | "scanning" | | 3 | "silence" | | 4 | "pulse" | | 5 | "flickered" | | 6 | "traced" | | 7 | "calculated" |
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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 | 85 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 85 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 146 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1718 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 1045 | | uniqueNames | 13 | | maxNameDensity | 1.15 | | worstName | "Lucien" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Ptolemy | 2 | | Eva | 5 | | Moreau | 3 | | Soho | 2 | | Rory | 8 | | French | 1 | | East | 1 | | London | 1 | | Lucien | 12 | | Evan | 3 | | Heat | 1 | | Brick | 1 | | Lane | 1 |
| | persons | | 0 | "Ptolemy" | | 1 | "Eva" | | 2 | "Moreau" | | 3 | "Rory" | | 4 | "Lucien" | | 5 | "Evan" | | 6 | "Heat" |
| | places | | 0 | "Soho" | | 1 | "East" | | 2 | "London" | | 3 | "Brick" | | 4 | "Lane" |
| | globalScore | 0.926 | | windowScore | 0.833 | |
| 68.03% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a held breath" | | 1 | "smelled like old paper and the ghosts of c" |
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| 83.59% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.164 | | wordCount | 1718 | | matches | | 0 | "no sense to anyone but" | | 1 | "Not threatening, but intimate, the way someone might speak a secret aloud in a da" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 146 | | matches | | 0 | "seen that face" | | 1 | "accepted that she'd" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 85 | | mean | 20.21 | | std | 18.22 | | cv | 0.901 | | sampleLengths | | 0 | 48 | | 1 | 7 | | 2 | 45 | | 3 | 2 | | 4 | 4 | | 5 | 18 | | 6 | 50 | | 7 | 5 | | 8 | 36 | | 9 | 2 | | 10 | 10 | | 11 | 39 | | 12 | 17 | | 13 | 6 | | 14 | 28 | | 15 | 1 | | 16 | 5 | | 17 | 20 | | 18 | 11 | | 19 | 49 | | 20 | 4 | | 21 | 49 | | 22 | 35 | | 23 | 1 | | 24 | 20 | | 25 | 4 | | 26 | 27 | | 27 | 16 | | 28 | 16 | | 29 | 3 | | 30 | 3 | | 31 | 43 | | 32 | 54 | | 33 | 31 | | 34 | 3 | | 35 | 59 | | 36 | 9 | | 37 | 8 | | 38 | 33 | | 39 | 6 | | 40 | 3 | | 41 | 7 | | 42 | 56 | | 43 | 3 | | 44 | 3 | | 45 | 52 | | 46 | 25 | | 47 | 7 | | 48 | 28 | | 49 | 1 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 85 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 175 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 146 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1048 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.03244274809160305 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.003816793893129771 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 146 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 146 | | mean | 11.77 | | std | 10.13 | | cv | 0.861 | | sampleLengths | | 0 | 4 | | 1 | 3 | | 2 | 25 | | 3 | 16 | | 4 | 7 | | 5 | 17 | | 6 | 9 | | 7 | 19 | | 8 | 2 | | 9 | 4 | | 10 | 16 | | 11 | 2 | | 12 | 3 | | 13 | 17 | | 14 | 30 | | 15 | 5 | | 16 | 30 | | 17 | 6 | | 18 | 2 | | 19 | 7 | | 20 | 3 | | 21 | 10 | | 22 | 1 | | 23 | 28 | | 24 | 10 | | 25 | 7 | | 26 | 6 | | 27 | 24 | | 28 | 4 | | 29 | 1 | | 30 | 5 | | 31 | 3 | | 32 | 17 | | 33 | 11 | | 34 | 15 | | 35 | 34 | | 36 | 4 | | 37 | 17 | | 38 | 32 | | 39 | 3 | | 40 | 32 | | 41 | 1 | | 42 | 8 | | 43 | 12 | | 44 | 4 | | 45 | 7 | | 46 | 3 | | 47 | 17 | | 48 | 11 | | 49 | 5 |
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| 65.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.4383561643835616 | | totalSentences | 146 | | uniqueOpeners | 64 | |
| 41.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 80 | | matches | | | ratio | 0.013 | |
| 65.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 80 | | matches | | 0 | "His charcoal suit looked fresh-pressed" | | 1 | "He glanced down at himself" | | 2 | "She didn't move." | | 3 | "His mouth curved at one" | | 4 | "She reached for the door," | | 5 | "He tapped the cane once" | | 6 | "He leaned forward, close enough" | | 7 | "Her hand stopped." | | 8 | "He said it simply, without" | | 9 | "She laughed, the sound scraping" | | 10 | "He adjusted his grip on" | | 11 | "He dealt in secrets and" | | 12 | "She stepped back." | | 13 | "He took in the chaos" | | 14 | "He set the cane against" | | 15 | "He folded his hands in" | | 16 | "He tilted his head again," | | 17 | "She should have looked away." | | 18 | "Her voice came out steadier" | | 19 | "She crushed it down." |
| | ratio | 0.388 | |
| 10.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 72 | | totalSentences | 80 | | matches | | 0 | "The first deadbolt clicked." | | 1 | "The third stuck, as it" | | 2 | "Rory's hand froze on the" | | 3 | "Lucien Moreau leaned against the" | | 4 | "His charcoal suit looked fresh-pressed" | | 5 | "The ivory-handled cane rested against" | | 6 | "He glanced down at himself" | | 7 | "She didn't move." | | 8 | "The crescent scar on her" | | 9 | "Lucien tilted his head, one" | | 10 | "His mouth curved at one" | | 11 | "Ptolemy slipped between Rory's ankles" | | 12 | "She reached for the door," | | 13 | "He tapped the cane once" | | 14 | "He leaned forward, close enough" | | 15 | "Her hand stopped." | | 16 | "The door hung open, two" | | 17 | "Lucien withdrew the cane, tucking" | | 18 | "He said it simply, without" | | 19 | "Rory's jaw tightened." |
| | ratio | 0.9 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 80 | | matches | (empty) | | ratio | 0 | |
| 96.77% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 2 | | matches | | 0 | "Evan, who had never accepted that she'd left without taking anything because in his world, people always took something." | | 1 | "Eva's desk had overflowed onto every available surface, maps pinned to the walls with red thread connecting locations that made no sense to anyone but her." |
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| 65.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 25 | | uselessAdditionCount | 3 | | matches | | 0 | "She laughed, the sound scraping out of her throat" | | 1 | "He tilted, that analytical gaze stripping away layers" | | 2 | "She dug, the crescent scar throbbing in time with her pulse" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 86 | | tagDensity | 0.023 | | leniency | 0.047 | | rawRatio | 0.5 | | effectiveRatio | 0.023 | |