| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1048 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1048 | | totalAiIsms | 32 | | 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 | | | 25 | |
| | highlights | | 0 | "rhythmic" | | 1 | "calculated" | | 2 | "mechanical" | | 3 | "efficient" | | 4 | "oppressive" | | 5 | "maw" | | 6 | "gloom" | | 7 | "shimmered" | | 8 | "silence" | | 9 | "weight" | | 10 | "footsteps" | | 11 | "echoed" | | 12 | "standard" | | 13 | "familiar" | | 14 | "constructed" | | 15 | "velvet" | | 16 | "vibrated" | | 17 | "echoing" | | 18 | "scanning" | | 19 | "pulsed" | | 20 | "silk" | | 21 | "trembled" | | 22 | "synchronized" | | 23 | "electric" | | 24 | "flicked" | | 25 | "whisper" |
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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 | 77 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 77 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 89 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1048 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 957 | | uniqueNames | 12 | | maxNameDensity | 1.36 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Tube | 1 | | Morris | 1 | | Metropolitan | 1 | | Police | 1 | | London | 1 | | Underground | 1 | | Veil | 1 | | Market | 1 | | Quinn | 13 | | Italian | 1 | | Glock | 1 |
| | persons | | | places | | | globalScore | 0.821 | | windowScore | 0.667 | |
| 70.63% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 2 | | matches | | 0 | "stone that seemed to swallow the light from her torch" | | 1 | "sounded like grinding stones" |
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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 | 1048 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 89 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 23.82 | | std | 21.21 | | cv | 0.891 | | sampleLengths | | 0 | 47 | | 1 | 54 | | 2 | 61 | | 3 | 12 | | 4 | 59 | | 5 | 12 | | 6 | 86 | | 7 | 24 | | 8 | 12 | | 9 | 5 | | 10 | 54 | | 11 | 8 | | 12 | 48 | | 13 | 34 | | 14 | 40 | | 15 | 12 | | 16 | 48 | | 17 | 4 | | 18 | 6 | | 19 | 13 | | 20 | 2 | | 21 | 10 | | 22 | 11 | | 23 | 6 | | 24 | 16 | | 25 | 19 | | 26 | 22 | | 27 | 11 | | 28 | 64 | | 29 | 27 | | 30 | 49 | | 31 | 3 | | 32 | 3 | | 33 | 9 | | 34 | 21 | | 35 | 2 | | 36 | 52 | | 37 | 15 | | 38 | 6 | | 39 | 28 | | 40 | 10 | | 41 | 10 | | 42 | 9 | | 43 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 77 | | matches | | |
| 25.71% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 153 | | matches | | 0 | "wasn't running" | | 1 | "was running" | | 2 | "was sprinting" | | 3 | "was slowing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 89 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 961 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.015608740894901144 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.007284079084287201 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 89 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 89 | | mean | 11.78 | | std | 6.6 | | cv | 0.56 | | sampleLengths | | 0 | 17 | | 1 | 18 | | 2 | 12 | | 3 | 7 | | 4 | 5 | | 5 | 18 | | 6 | 24 | | 7 | 16 | | 8 | 12 | | 9 | 7 | | 10 | 26 | | 11 | 6 | | 12 | 6 | | 13 | 16 | | 14 | 18 | | 15 | 25 | | 16 | 3 | | 17 | 9 | | 18 | 8 | | 19 | 20 | | 20 | 26 | | 21 | 10 | | 22 | 3 | | 23 | 19 | | 24 | 6 | | 25 | 18 | | 26 | 12 | | 27 | 5 | | 28 | 9 | | 29 | 28 | | 30 | 17 | | 31 | 8 | | 32 | 14 | | 33 | 12 | | 34 | 22 | | 35 | 11 | | 36 | 11 | | 37 | 12 | | 38 | 4 | | 39 | 21 | | 40 | 12 | | 41 | 3 | | 42 | 12 | | 43 | 10 | | 44 | 17 | | 45 | 21 | | 46 | 4 | | 47 | 6 | | 48 | 3 | | 49 | 10 |
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| 28.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.24719101123595505 | | totalSentences | 89 | | uniqueOpeners | 22 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 62.11% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 76 | | matches | | 0 | "He didn't look back, but" | | 1 | "She didn't waste the oxygen." | | 2 | "She maintained a steady, rhythmic" | | 3 | "He vaulted over a pile" | | 4 | "She caught a glimpse of" | | 5 | "He wasn't running from the" | | 6 | "He was running for his" | | 7 | "He didn't hesitate." | | 8 | "He dove down the stairs," | | 9 | "It reminded her of the" | | 10 | "She remembered the way the" | | 11 | "She looked at the dark" | | 12 | "They didn't speak in the" | | 13 | "They whispered in a low," | | 14 | "She spotted the suspect." | | 15 | "He was sprinting toward a" | | 16 | "She reached the gate just" | | 17 | "She stepped into the guard's" | | 18 | "She hadn't identified herself." | | 19 | "She hadn't shown her badge." |
| | ratio | 0.395 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 72 | | totalSentences | 76 | | matches | | 0 | "Quinn's boot slammed into a" | | 1 | "He didn't look back, but" | | 2 | "Quinn didn't shout for him" | | 3 | "She didn't waste the oxygen." | | 4 | "She maintained a steady, rhythmic" | | 5 | "The worn leather watch on" | | 6 | "The man lunged around a" | | 7 | "He vaulted over a pile" | | 8 | "Quinn followed, her movements efficient" | | 9 | "She caught a glimpse of" | | 10 | "He wasn't running from the" | | 11 | "He was running for his" | | 12 | "The chase spilled out onto" | | 13 | "Neon lights from a distant" | | 14 | "The suspect bolted toward a" | | 15 | "He didn't hesitate." | | 16 | "He dove down the stairs," | | 17 | "Quinn stopped at the lip" | | 18 | "The air rising from the" | | 19 | "It reminded her of the" |
| | ratio | 0.947 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 76 | | matches | | 0 | "To her left, a vendor" | | 1 | "To her right, a woman" |
| | ratio | 0.026 | |
| 26.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 8 | | matches | | 0 | "The suspect bolted toward a derelict Tube station entrance, a gaping maw of concrete and rusted iron that smelled of damp earth and ancient electricity." | | 1 | "The air rising from the hole felt different, colder, with a metallic tang that stung the back of her throat." | | 2 | "The suspect's footsteps echoed from below, a frantic drumming that grew distant." | | 3 | "The tiled walls transitioned from the familiar white and blue of the London Underground to a rough, blackened stone that seemed to swallow the light from her to…" | | 4 | "Banners of heavy, purple velvet hung from the ceiling, dampened by a leak that dripped a slow, rhythmic tick-tock into obsidian basins." | | 5 | "He was sprinting toward a heavy, iron gate guarded by a creature that looked far too wide for its human clothes." | | 6 | "He smiled, but the expression didn't reach his eyes, which were a flat, void-like black." | | 7 | "They carried long, curved, silver blades that hummed with a low, electric frequency." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |