| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 44 | | tagDensity | 0.068 | | leniency | 0.136 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2100 | | 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) | |
| 76.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2100 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "porcelain" | | 1 | "footsteps" | | 2 | "traced" | | 3 | "stomach" | | 4 | "electric" | | 5 | "silence" | | 6 | "shattered" |
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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 | 245 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 245 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 285 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2100 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 49.36% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 63 | | wordCount | 1888 | | uniqueNames | 16 | | maxNameDensity | 2.01 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Wardour | 1 | | Street | 1 | | Quinn | 38 | | Tube | 1 | | Camden | 1 | | Veil | 1 | | Market | 2 | | Herrera | 3 | | Saint | 1 | | Christopher | 1 | | Metropolitan | 1 | | Police | 1 | | One | 4 | | Morris | 3 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Quinn" | | 3 | "Market" | | 4 | "Herrera" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "One" | | 8 | "Morris" |
| | places | | | globalScore | 0.494 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 151 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like an ordinary bar until the boo" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.476 | | wordCount | 2100 | | matches | | 0 | "not black ones, but the scar beside the left brow matched" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 285 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 169 | | mean | 12.43 | | std | 12.54 | | cv | 1.009 | | sampleLengths | | 0 | 18 | | 1 | 2 | | 2 | 31 | | 3 | 4 | | 4 | 48 | | 5 | 7 | | 6 | 48 | | 7 | 12 | | 8 | 44 | | 9 | 11 | | 10 | 16 | | 11 | 4 | | 12 | 5 | | 13 | 22 | | 14 | 29 | | 15 | 29 | | 16 | 8 | | 17 | 6 | | 18 | 20 | | 19 | 4 | | 20 | 10 | | 21 | 17 | | 22 | 8 | | 23 | 23 | | 24 | 1 | | 25 | 46 | | 26 | 3 | | 27 | 20 | | 28 | 7 | | 29 | 24 | | 30 | 6 | | 31 | 3 | | 32 | 7 | | 33 | 2 | | 34 | 3 | | 35 | 39 | | 36 | 8 | | 37 | 27 | | 38 | 5 | | 39 | 7 | | 40 | 5 | | 41 | 7 | | 42 | 54 | | 43 | 4 | | 44 | 3 | | 45 | 23 | | 46 | 25 | | 47 | 2 | | 48 | 6 | | 49 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 245 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 339 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 285 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1897 | | adjectiveStacks | 2 | | stackExamples | | 0 | "Right, left, long straight, stairs" | | 1 | "lay beneath surgical sheets." |
| | adverbCount | 43 | | adverbRatio | 0.022667369530838165 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0015814443858724301 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 285 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 285 | | mean | 7.37 | | std | 4.37 | | cv | 0.593 | | sampleLengths | | 0 | 18 | | 1 | 2 | | 2 | 4 | | 3 | 13 | | 4 | 14 | | 5 | 4 | | 6 | 5 | | 7 | 19 | | 8 | 5 | | 9 | 19 | | 10 | 7 | | 11 | 7 | | 12 | 12 | | 13 | 17 | | 14 | 12 | | 15 | 12 | | 16 | 5 | | 17 | 6 | | 18 | 16 | | 19 | 17 | | 20 | 11 | | 21 | 7 | | 22 | 4 | | 23 | 5 | | 24 | 4 | | 25 | 5 | | 26 | 14 | | 27 | 2 | | 28 | 6 | | 29 | 6 | | 30 | 5 | | 31 | 9 | | 32 | 5 | | 33 | 4 | | 34 | 10 | | 35 | 4 | | 36 | 15 | | 37 | 3 | | 38 | 5 | | 39 | 6 | | 40 | 8 | | 41 | 12 | | 42 | 4 | | 43 | 10 | | 44 | 3 | | 45 | 2 | | 46 | 12 | | 47 | 8 | | 48 | 5 | | 49 | 3 |
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| 61.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.38596491228070173 | | totalSentences | 285 | | uniqueOpeners | 110 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 231 | | matches | | 0 | "Somewhere behind, the Raven’s distinctive" | | 1 | "Then the grey-coated man had" | | 2 | "Only scaffolding, shuttered shops and" | | 3 | "Even the dripping pipes fell" | | 4 | "Then the taller guard unlocked" | | 5 | "Somewhere, metal struck metal in" | | 6 | "Then every light in the" |
| | ratio | 0.03 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 231 | | matches | | 0 | "He glanced back once." | | 1 | "She planted one hand on" | | 2 | "He clipped a waiter outside" | | 3 | "He had speed, but no" | | 4 | "His shoulders rose too high." | | 5 | "His stride length changed whenever" | | 6 | "She stopped beside a closed" | | 7 | "She drew her baton and" | | 8 | "He vanished inside." | | 9 | "She reached the door before" | | 10 | "She started down." | | 11 | "She searched the pockets and" | | 12 | "Its crown bore a tiny" | | 13 | "She counted turns without meaning" | | 14 | "She caught his jumper." | | 15 | "He cried out and twisted." | | 16 | "He drove an elbow towards" | | 17 | "He clawed at her face." | | 18 | "She pinned his wrist between" | | 19 | "His body went rigid beneath" |
| | ratio | 0.195 | |
| 66.06% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 182 | | totalSentences | 231 | | matches | | 0 | "Quinn shouldered through the Raven’s" | | 1 | "He glanced back once." | | 2 | "A white token flashed between" | | 3 | "Quinn ran after him." | | 4 | "A taxi blared its horn." | | 5 | "She planted one hand on" | | 6 | "Pain climbed her right knee." | | 7 | "The suspect cut between two" | | 8 | "Quinn followed, her coat snapping" | | 9 | "Rain glazed the paving stones" | | 10 | "Soho smeared around her in" | | 11 | "The Nest had looked like" | | 12 | "A concealed back room lay" | | 13 | "Quinn had found surgical blood" | | 14 | "He clipped a waiter outside" | | 15 | "Plates struck the pavement." | | 16 | "Porcelain burst beneath Quinn’s shoes." | | 17 | "The suspect snatched a chair" | | 18 | "He had speed, but no" | | 19 | "His shoulders rose too high." |
| | ratio | 0.788 | |
| 21.65% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 231 | | matches | | 0 | "By the time she returned," |
| | ratio | 0.004 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 70 | | technicalSentenceCount | 2 | | matches | | 0 | "Morris used to glance at it during pursuits, as if her wrist held the result." | | 1 | "Military precision had survived childhood, the academy and every superintendent who mistook it for obedience." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 44 | | tagDensity | 0.045 | | leniency | 0.091 | | rawRatio | 0 | | effectiveRatio | 0 | |