| 33.33% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn replied curtly [curtly]" | | 1 | "she shouted again [again]" |
| | dialogueSentences | 22 | | tagDensity | 0.545 | | leniency | 1 | | rawRatio | 0.167 | | effectiveRatio | 0.167 | |
| 88.49% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1303 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slowly" | | 1 | "very" | | 2 | "really" |
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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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1303 | | totalAiIsms | 34 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | | | 23 | | | 24 | | word | "down her spine" | | count | 1 |
| | 25 | | | 26 | |
| | highlights | | 0 | "flickered" | | 1 | "quickened" | | 2 | "raced" | | 3 | "glint" | | 4 | "scanning" | | 5 | "tension" | | 6 | "familiar" | | 7 | "eyebrow" | | 8 | "whisper" | | 9 | "jaw clenched" | | 10 | "glistening" | | 11 | "anticipation" | | 12 | "could feel" | | 13 | "pulse" | | 14 | "pounding" | | 15 | "reminder" | | 16 | "depths" | | 17 | "cacophony" | | 18 | "navigated" | | 19 | "glinting" | | 20 | "weight" | | 21 | "unwavering" | | 22 | "intrigue" | | 23 | "chill" | | 24 | "down her spine" | | 25 | "echoed" | | 26 | "determined" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "jaw clenched" | | 1 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 82 | | matches | | 0 | "k with anticipation" | | 1 | "felt a chill" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 82 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 92 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1298 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1139 | | uniqueNames | 9 | | maxNameDensity | 1.58 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Silas" | | discoveredNames | | Harlow | 1 | | Quinn | 18 | | Soho | 1 | | Morris | 1 | | Raven | 1 | | Nest | 2 | | Silas | 6 | | Tube | 1 | | Camden | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Raven" | | 4 | "Silas" |
| | places | | | globalScore | 0.71 | | windowScore | 0.667 | |
| 84.21% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 76 | | glossingSentenceCount | 2 | | matches | | 0 | "puzzle that seemed to shift with every lead" | | 1 | "as if weighing the consequences of his next words" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.77 | | wordCount | 1298 | | matches | | 0 | "not just from the exertion but from the thrill of the chase" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 92 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 38.18 | | std | 21.35 | | cv | 0.559 | | sampleLengths | | 0 | 70 | | 1 | 68 | | 2 | 94 | | 3 | 60 | | 4 | 61 | | 5 | 74 | | 6 | 49 | | 7 | 18 | | 8 | 24 | | 9 | 22 | | 10 | 29 | | 11 | 13 | | 12 | 36 | | 13 | 10 | | 14 | 42 | | 15 | 18 | | 16 | 18 | | 17 | 14 | | 18 | 65 | | 19 | 46 | | 20 | 58 | | 21 | 26 | | 22 | 14 | | 23 | 43 | | 24 | 44 | | 25 | 33 | | 26 | 59 | | 27 | 29 | | 28 | 15 | | 29 | 37 | | 30 | 15 | | 31 | 40 | | 32 | 12 | | 33 | 42 |
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| 88.15% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 82 | | matches | | 0 | "was known" | | 1 | "were traded" | | 2 | "were adorned" | | 3 | "was unmarked" | | 4 | "was determined" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 193 | | matches | | 0 | "was being" | | 1 | "was already disappearing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 92 | | ratio | 0.054 | | matches | | 0 | "Tonight, she was close—too close to let this one slip away." | | 1 | "The rain continued to pour, and the distant sound of laughter and clinking glasses drifted from a nearby bar—the Raven’s Nest." | | 2 | "Then, she spotted him—a figure slipping between the stalls, the same silhouette she had chased through the rain-soaked streets." | | 3 | "But she couldn’t turn back—not now." | | 4 | "The figure turned slowly, revealing a face she recognized from the files—someone connected to the very criminal activity she had been investigating." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1147 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.024411508282476024 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004359197907585004 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 92 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 92 | | mean | 14.11 | | std | 5.95 | | cv | 0.422 | | sampleLengths | | 0 | 25 | | 1 | 26 | | 2 | 19 | | 3 | 20 | | 4 | 15 | | 5 | 22 | | 6 | 11 | | 7 | 21 | | 8 | 24 | | 9 | 16 | | 10 | 25 | | 11 | 8 | | 12 | 17 | | 13 | 8 | | 14 | 14 | | 15 | 21 | | 16 | 10 | | 17 | 23 | | 18 | 10 | | 19 | 18 | | 20 | 21 | | 21 | 21 | | 22 | 19 | | 23 | 13 | | 24 | 12 | | 25 | 13 | | 26 | 15 | | 27 | 9 | | 28 | 12 | | 29 | 6 | | 30 | 11 | | 31 | 13 | | 32 | 6 | | 33 | 16 | | 34 | 12 | | 35 | 17 | | 36 | 13 | | 37 | 15 | | 38 | 21 | | 39 | 3 | | 40 | 7 | | 41 | 16 | | 42 | 15 | | 43 | 11 | | 44 | 9 | | 45 | 9 | | 46 | 18 | | 47 | 11 | | 48 | 3 | | 49 | 21 |
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| 55.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.358695652173913 | | totalSentences | 92 | | uniqueOpeners | 33 | |
| 42.19% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 79 | | matches | | 0 | "Then, she spotted him—a figure" |
| | ratio | 0.013 | |
| 73.16% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 79 | | matches | | 0 | "she shouted, her voice cutting" | | 1 | "She had been on the" | | 2 | "She could see the glint" | | 3 | "She pushed it aside, focusing" | | 4 | "She cursed under her breath," | | 5 | "She had been there before," | | 6 | "She took a step toward" | | 7 | "It was Silas, the owner," | | 8 | "His dark hair fell in" | | 9 | "she asked, her tone clipped" | | 10 | "She didn’t have time for" | | 11 | "she pressed, her impatience bubbling" | | 12 | "It glimmered in the dim" | | 13 | "she said, tucking the token" | | 14 | "She turned to leave, but" | | 15 | "She shot him a look" | | 16 | "She approached the entrance, her" | | 17 | "He leaned against a stall" | | 18 | "She couldn’t afford distractions." | | 19 | "She pressed on, her determination" |
| | ratio | 0.367 | |
| 10.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 79 | | matches | | 0 | "The rain fell in relentless" | | 1 | "Detective Harlow Quinn’s breath came" | | 2 | "The neon glow of the" | | 3 | "she shouted, her voice cutting" | | 4 | "Quinn’s heart raced, not just" | | 5 | "She had been on the" | | 6 | "Tonight, she was close—too close" | | 7 | "The figure slipped into an" | | 8 | "She could see the glint" | | 9 | "The memory of his laughter," | | 10 | "She pushed it aside, focusing" | | 11 | "The alley opened up into" | | 12 | "The figure had vanished, swallowed" | | 13 | "She cursed under her breath," | | 14 | "The rain continued to pour," | | 15 | "Quinn hesitated, her instincts battling" | | 16 | "The Nest was known for" | | 17 | "She had been there before," | | 18 | "The air was thick with" | | 19 | "She took a step toward" |
| | ratio | 0.899 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 90.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 4 | | matches | | 0 | "The figure slipped into an alley, and Quinn followed, her boots splashing through puddles, the cold water soaking through her socks." | | 1 | "Silas hesitated, glancing around the bar as if weighing the consequences of his next words." | | 2 | "It glimmered in the dim light, a bone-like substance that felt cool against her palm." | | 3 | "He leaned against a stall filled with shimmering trinkets, his eyes glinting with mischief." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 8 | | matches | | 0 | "she asked, her tone clipped" | | 1 | "Silas said, his voice dropping to a whisper" | | 2 | "she pressed, her impatience bubbling to the surface" | | 3 | "a vendor called, his voice smooth and inviting" | | 4 | "she shouted again, but the figure was already disappearing into the shadows" | | 5 | "she demanded, her voice steady despite the uncertainty gnawing at her gut" | | 6 | "they said, their voice dripping with mockery" | | 7 | "she demanded, her voice low and fierce" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 5 | | fancyTags | | 0 | "she shouted (shout)" | | 1 | "she pressed (press)" | | 2 | "she shouted again (shout)" | | 3 | "she demanded (demand)" | | 4 | "she demanded (demand)" |
| | dialogueSentences | 22 | | tagDensity | 0.545 | | leniency | 1 | | rawRatio | 0.417 | | effectiveRatio | 0.417 | |