| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 2 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1086 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 12.52% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1086 | | totalAiIsms | 19 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "echoing" | | 2 | "familiar" | | 3 | "cacophony" | | 4 | "echo" | | 5 | "weight" | | 6 | "treacherous" | | 7 | "scanned" | | 8 | "glint" | | 9 | "stomach" | | 10 | "glinting" | | 11 | "gloom" | | 12 | "depths" | | 13 | "pulsed" | | 14 | "tinged" | | 15 | "chilled" |
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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 | 94 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 94 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 94 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 1078 | | ratio | 0.002 | | matches | | |
| 83.33% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 1 | | matches | | 0 | "An abandoned Tube station beneath Camden, they said." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 1060 | | uniqueNames | 23 | | maxNameDensity | 0.85 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 9 | | London | 2 | | Raven | 1 | | Nest | 1 | | Shaftesbury | 1 | | Avenue | 1 | | Double | 1 | | Decker | 1 | | Charing | 1 | | Cross | 1 | | Road | 1 | | Victorian | 1 | | Veil | 1 | | Market | 1 | | Tube | 1 | | Camden | 1 | | Davies | 2 | | Morris | 1 | | Taking | 1 | | Saint | 1 | | Christopher | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Davies" | | 4 | "Morris" | | 5 | "Saint" | | 6 | "Christopher" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Shaftesbury" | | 3 | "Avenue" | | 4 | "Charing" | | 5 | "Cross" | | 6 | "Road" |
| | globalScore | 1 | | windowScore | 1 | |
| 42.86% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | glossingSentenceCount | 3 | | matches | | 0 | "quite place but recognized from that *other* case" | | 1 | "looked like old, tarnished brass" | | 2 | "as if speaking through water" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.928 | | wordCount | 1078 | | matches | | 0 | "not a sewer tunnel as she’d expected, but a steep, narrow staircase descending into absolute blackness" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 94 | | matches | (empty) | |
| 22.71% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 15 | | mean | 71.87 | | std | 16.49 | | cv | 0.229 | | sampleLengths | | 0 | 84 | | 1 | 74 | | 2 | 89 | | 3 | 64 | | 4 | 74 | | 5 | 76 | | 6 | 56 | | 7 | 85 | | 8 | 64 | | 9 | 62 | | 10 | 55 | | 11 | 56 | | 12 | 78 | | 13 | 47 | | 14 | 114 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 94 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 160 | | matches | | |
| 82.07% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 94 | | ratio | 0.021 | | matches | | 0 | "This wasn't just any collar; this felt different." | | 1 | "The way the suspect moved, the sheer desperation in his flight – it hinted at something beyond petty theft." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1068 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.03089887640449438 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.008426966292134831 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 94 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 94 | | mean | 11.47 | | std | 6.83 | | cv | 0.595 | | sampleLengths | | 0 | 20 | | 1 | 30 | | 2 | 14 | | 3 | 20 | | 4 | 15 | | 5 | 18 | | 6 | 18 | | 7 | 23 | | 8 | 18 | | 9 | 14 | | 10 | 9 | | 11 | 21 | | 12 | 8 | | 13 | 19 | | 14 | 15 | | 15 | 16 | | 16 | 6 | | 17 | 24 | | 18 | 3 | | 19 | 18 | | 20 | 3 | | 21 | 17 | | 22 | 14 | | 23 | 22 | | 24 | 13 | | 25 | 13 | | 26 | 10 | | 27 | 15 | | 28 | 13 | | 29 | 12 | | 30 | 20 | | 31 | 11 | | 32 | 18 | | 33 | 7 | | 34 | 8 | | 35 | 1 | | 36 | 9 | | 37 | 7 | | 38 | 5 | | 39 | 4 | | 40 | 12 | | 41 | 15 | | 42 | 2 | | 43 | 2 | | 44 | 7 | | 45 | 2 | | 46 | 5 | | 47 | 6 | | 48 | 7 | | 49 | 18 |
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| 56.38% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3829787234042553 | | totalSentences | 94 | | uniqueOpeners | 36 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 84 | | matches | | 0 | "Just the endless drumming of" | | 1 | "Then, her eyes landed on" | | 2 | "Carefully, she gripped the cold," | | 3 | "Then, she stepped onto the" |
| | ratio | 0.048 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 84 | | matches | | 0 | "Her closely cropped salt-and-pepper hair" | | 1 | "He moved with an unnatural" | | 2 | "Her military precision, honed by" | | 3 | "He darted down Charing Cross" | | 4 | "It tickled at the back" | | 5 | "Her breath hitched." | | 6 | "She plunged in after him," | | 7 | "He was faster than she" | | 8 | "He scrambled up a rusted" | | 9 | "She reached the next rooftop," | | 10 | "He reached a section of" | | 11 | "She scanned the rooftops, the" | | 12 | "It looked like old, tarnished" | | 13 | "She remembered whispers, hushed conversations" | | 14 | "She’d dismissed them as bar" | | 15 | "She knelt, probing the edge" | | 16 | "It gave way with a" | | 17 | "she muttered, the word snatched" | | 18 | "She could hear the faintest" | | 19 | "Her police radio crackled, static-laden" |
| | ratio | 0.333 | |
| 61.19% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 84 | | matches | | 0 | "Rain lashed down, turning the" | | 1 | "Detective Harlow Quinn’s worn leather" | | 2 | "Her closely cropped salt-and-pepper hair" | | 3 | "The sharp scent of ozone" | | 4 | "He moved with an unnatural" | | 5 | "Quinn had caught him in" | | 6 | "The chase spilled onto Shaftesbury" | | 7 | "The suspect dodged a Double" | | 8 | "Quinn skidded, catching herself before" | | 9 | "Her military precision, honed by" | | 10 | "This wasn't just any collar;" | | 11 | "The way the suspect moved," | | 12 | "He darted down Charing Cross" | | 13 | "The scent of exhaust fumes" | | 14 | "something metallic, sharp, and undeniably" | | 15 | "It tickled at the back" | | 16 | "Her breath hitched." | | 17 | "The man ducked into an" | | 18 | "Quinn didn't hesitate." | | 19 | "She plunged in after him," |
| | ratio | 0.798 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 84 | | matches | | 0 | "Now he ran, and Quinn," | | 1 | "Now, standing on a rain-slicked" |
| | ratio | 0.024 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 3 | | matches | | 0 | "She remembered whispers, hushed conversations in the precinct break room about places that existed just outside the everyday." | | 1 | "She could hear the faintest echo of voices, too, distant and distorted, as if speaking through water." | | 2 | "She pictured the scene: Davies and his men fanning out, their flashlights cutting futile swathes through the rain, searching rooftops and alleys that were alrea…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "she muttered, the word snatched away by the wind" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 2 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |