| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn gestured vaguely [vaguely]" |
| | dialogueSentences | 26 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.077 | | effectiveRatio | 0.077 | |
| 73.12% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1302 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "sharply" | | 1 | "suddenly" | | 2 | "quickly" | | 3 | "slightly" | | 4 | "cautiously" |
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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) | |
| 38.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1302 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "navigated" | | 1 | "flicked" | | 2 | "quickened" | | 3 | "perfect" | | 4 | "echoed" | | 5 | "scanning" | | 6 | "footsteps" | | 7 | "flickered" | | 8 | "intricate" | | 9 | "mechanical" | | 10 | "unreadable" | | 11 | "pulsed" | | 12 | "stomach" | | 13 | "comfortable" |
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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 | 137 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 137 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 150 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1306 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 47.61% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 72 | | wordCount | 1172 | | uniqueNames | 22 | | maxNameDensity | 2.05 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 24 | | Dean | 1 | | Street | 1 | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Tomás | 2 | | Herrera | 20 | | Spanish | 1 | | Morris | 4 | | Shaftesbury | 1 | | Avenue | 1 | | Saint | 2 | | Christopher | 2 | | Camden | 2 | | Metropolitan | 1 | | Police | 1 | | South | 1 | | Veil | 1 | | Market | 2 | | Collector | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Morris" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Collector" |
| | places | | 0 | "Dean" | | 1 | "Street" | | 2 | "Raven" | | 3 | "Soho" | | 4 | "Shaftesbury" | | 5 | "Avenue" | | 6 | "Camden" | | 7 | "Market" |
| | globalScore | 0.476 | | windowScore | 0.5 | |
| 99.49% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 99 | | glossingSentenceCount | 2 | | matches | | 0 | "patterns that seemed to shift in the poor light" | | 1 | "looked like preserved organs" |
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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 | 1306 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 150 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 24.19 | | std | 14.88 | | cv | 0.615 | | sampleLengths | | 0 | 20 | | 1 | 60 | | 2 | 43 | | 3 | 59 | | 4 | 54 | | 5 | 21 | | 6 | 15 | | 7 | 41 | | 8 | 32 | | 9 | 45 | | 10 | 45 | | 11 | 10 | | 12 | 33 | | 13 | 27 | | 14 | 9 | | 15 | 51 | | 16 | 39 | | 17 | 43 | | 18 | 30 | | 19 | 11 | | 20 | 38 | | 21 | 23 | | 22 | 35 | | 23 | 33 | | 24 | 13 | | 25 | 35 | | 26 | 41 | | 27 | 17 | | 28 | 8 | | 29 | 13 | | 30 | 20 | | 31 | 3 | | 32 | 33 | | 33 | 8 | | 34 | 14 | | 35 | 6 | | 36 | 23 | | 37 | 10 | | 38 | 24 | | 39 | 15 | | 40 | 11 | | 41 | 9 | | 42 | 15 | | 43 | 2 | | 44 | 9 | | 45 | 25 | | 46 | 15 | | 47 | 27 | | 48 | 21 | | 49 | 23 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 137 | | matches | | 0 | "was connected" | | 1 | "was engaged" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 222 | | matches | | 0 | "was heading" | | 1 | "was purchasing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 150 | | ratio | 0.06 | | matches | | 0 | "She'd followed her suspect from The Raven's Nest after witnessing a curious exchange – bone-white tokens passed between hands under a table." | | 1 | "Her suspect – Tomás Herrera – moved with the confidence of someone who knew these streets intimately." | | 2 | "His olive-skinned hand reached up occasionally to touch something at his neck – that Saint Christopher medallion mentioned in his file." | | 3 | "The stench of damp concrete and something else – something earthy and organic – rose to meet her." | | 4 | "But Morris's face flashed in her mind – the confusion in his dead eyes, the bone token clutched in his hand." | | 5 | "Footprints marked the dusty floor – fresh ones, heading inward." | | 6 | "The emergency lighting ended fifty meters in, giving way to something else – a warm, flickering glow that spilled around a curve ahead." | | 7 | "People – at least fifty of them – browsed goods displayed on tables and racks." | | 8 | "These \"Collectors\" moved wrong – joints bending in impossible directions, faces too symmetrical to be real." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1167 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.028277634961439587 | | lyAdverbCount | 21 | | lyAdverbRatio | 0.017994858611825194 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 150 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 150 | | mean | 8.71 | | std | 4.82 | | cv | 0.553 | | sampleLengths | | 0 | 11 | | 1 | 3 | | 2 | 6 | | 3 | 17 | | 4 | 8 | | 5 | 22 | | 6 | 13 | | 7 | 5 | | 8 | 20 | | 9 | 10 | | 10 | 5 | | 11 | 3 | | 12 | 17 | | 13 | 6 | | 14 | 13 | | 15 | 15 | | 16 | 8 | | 17 | 8 | | 18 | 4 | | 19 | 11 | | 20 | 10 | | 21 | 21 | | 22 | 7 | | 23 | 7 | | 24 | 7 | | 25 | 6 | | 26 | 5 | | 27 | 4 | | 28 | 13 | | 29 | 4 | | 30 | 13 | | 31 | 11 | | 32 | 6 | | 33 | 6 | | 34 | 11 | | 35 | 9 | | 36 | 3 | | 37 | 9 | | 38 | 6 | | 39 | 11 | | 40 | 16 | | 41 | 14 | | 42 | 17 | | 43 | 14 | | 44 | 7 | | 45 | 3 | | 46 | 7 | | 47 | 9 | | 48 | 9 | | 49 | 8 |
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| 72.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.4533333333333333 | | totalSentences | 150 | | uniqueOpeners | 68 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 125 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 125 | | matches | | 0 | "She ignored it." | | 1 | "Her target was on the" | | 2 | "She'd followed her suspect from" | | 3 | "Her leather shoes splashed through" | | 4 | "Her suspect – Tomás Herrera" | | 5 | "She wove through them, keeping" | | 6 | "His olive-skinned hand reached up" | | 7 | "Her leather watch weighed on" | | 8 | "she muttered, shouldering past a" | | 9 | "She pumped her legs harder," | | 10 | "She glimpsed Herrera's back as" | | 11 | "He was heading north, toward" | | 12 | "Her breathing created small clouds" | | 13 | "She listened past it for" | | 14 | "It swung open with a" | | 15 | "Her training shouted warnings." | | 16 | "She tried photographing them with" | | 17 | "She slowed her approach, pressing" | | 18 | "He was engaged in intense" | | 19 | "She needed to blend in" |
| | ratio | 0.224 | |
| 68.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 98 | | totalSentences | 125 | | matches | | 0 | "The phone in Harlow Quinn's" | | 1 | "She ignored it." | | 2 | "Her target was on the" | | 3 | "She'd followed her suspect from" | | 4 | "Quinn kept pace, maintaining distance." | | 5 | "The rain plastered her closely" | | 6 | "Her leather shoes splashed through" | | 7 | "Water seeped into her socks." | | 8 | "Discomfort was irrelevant." | | 9 | "Her suspect – Tomás Herrera" | | 10 | "Quinn flicked raindrops from her" | | 11 | "The Spanish ex-paramedic was connected" | | 12 | "Each victim found with the" | | 13 | "Wounds that matched those on" | | 14 | "Quinn quickened her pace." | | 15 | "The street teemed with theatregoers" | | 16 | "She wove through them, keeping" | | 17 | "His olive-skinned hand reached up" | | 18 | "Her leather watch weighed on" | | 19 | "Herrera suddenly broke into a" |
| | ratio | 0.784 | |
| 40.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 125 | | matches | | 0 | "Wherever he headed, he moved" |
| | ratio | 0.008 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 2 | | matches | | 0 | "The emergency lighting ended fifty meters in, giving way to something else – a warm, flickering glow that spilled around a curve ahead." | | 1 | "The nearest Collector began moving toward them, its coat rippling like liquid shadow." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 34.62% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 3 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "Herrera snapped (snap)" | | 2 | "Herrera's voice snapped (snap)" |
| | dialogueSentences | 26 | | tagDensity | 0.192 | | leniency | 0.385 | | rawRatio | 0.6 | | effectiveRatio | 0.231 | |