| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva said softly [softly]" |
| | dialogueSentences | 33 | | tagDensity | 0.576 | | leniency | 1 | | rawRatio | 0.053 | | effectiveRatio | 0.053 | |
| 79.54% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1466 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "carefully" | | 1 | "softly" | | 2 | "slightly" | | 3 | "completely" | | 4 | "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) | |
| 59.07% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1466 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoed" | | 2 | "dancing" | | 3 | "warmth" | | 4 | "gloom" | | 5 | "scanning" | | 6 | "pristine" | | 7 | "perfect" | | 8 | "etched" | | 9 | "intricate" | | 10 | "familiar" | | 11 | "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 | 110 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 110 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 125 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1459 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1072 | | uniqueNames | 15 | | maxNameDensity | 1.77 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Eva" | | discoveredNames | | Camden | 1 | | Harlow | 19 | | Quinn | 1 | | Late | 1 | | Morris | 2 | | Veil | 1 | | Market | 1 | | Kowalski | 1 | | Eva | 15 | | Chief | 1 | | Inspector | 1 | | British | 1 | | Museum | 1 | | Silas | 1 | | Davies | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Market" | | 4 | "Kowalski" | | 5 | "Eva" | | 6 | "Inspector" | | 7 | "Museum" | | 8 | "Silas" | | 9 | "Davies" |
| | places | | | globalScore | 0.614 | | windowScore | 0.5 | |
| 81.51% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 2 | | matches | | 0 | "something like burnt sugar and old paper" | | 1 | "It was as if every drop of fluid, every ounce of life, had been vacuumed out of him" |
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| 62.92% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.371 | | wordCount | 1459 | | matches | | 0 | "Not as a kook, not as an academic nuisance, but as someone who was holding a piece of the puzzle Harlow had" | | 1 | "not as an academic nuisance, but as someone who was holding a piece of the puzzle Harlow had" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 125 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 44.21 | | std | 24.71 | | cv | 0.559 | | sampleLengths | | 0 | 95 | | 1 | 63 | | 2 | 80 | | 3 | 20 | | 4 | 78 | | 5 | 11 | | 6 | 48 | | 7 | 24 | | 8 | 84 | | 9 | 22 | | 10 | 51 | | 11 | 68 | | 12 | 23 | | 13 | 19 | | 14 | 70 | | 15 | 24 | | 16 | 31 | | 17 | 23 | | 18 | 57 | | 19 | 69 | | 20 | 19 | | 21 | 44 | | 22 | 86 | | 23 | 73 | | 24 | 12 | | 25 | 39 | | 26 | 11 | | 27 | 18 | | 28 | 41 | | 29 | 42 | | 30 | 35 | | 31 | 50 | | 32 | 29 |
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| 86.12% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 110 | | matches | | 0 | "was slumped" | | 1 | "was drawn" | | 2 | "been vacuumed" | | 3 | "been found" | | 4 | "was fixed" | | 5 | "was gone" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 10 | | totalVerbs | 170 | | matches | | 0 | "was carefully dusting" | | 1 | "was spinning" | | 2 | "wasn’t pointing" | | 3 | "wasn’t pointing" | | 4 | "was stuttering" | | 5 | "wasn’t looking" | | 6 | "was looking" | | 7 | "was holding" | | 8 | "wasn’t pointing" | | 9 | "was looking" |
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| 51.43% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 125 | | ratio | 0.032 | | matches | | 0 | "She wore her usual academic chic—a threadbare cardigan over a simple dress, her round glasses perched on her freckled nose." | | 1 | "The man—Silas—was slumped against the base of a derelict ticket kiosk." | | 2 | "The market-goers had left their usual trail of litter—discarded wrappers, the husks of strange, glowing fruit—but there was a perfect, sterile circle around the body, as if an invisible barrier had kept the world at bay." | | 3 | "She’d built a wall around the memory of Morris—that sudden, impossible cold, the way the shadows had seemed to reach for him, the way his body had been found, aged and brittle, in a matter of hours." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 355 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.03380281690140845 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.005633802816901409 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 125 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 125 | | mean | 11.67 | | std | 8.88 | | cv | 0.761 | | sampleLengths | | 0 | 20 | | 1 | 29 | | 2 | 12 | | 3 | 22 | | 4 | 5 | | 5 | 7 | | 6 | 10 | | 7 | 14 | | 8 | 7 | | 9 | 19 | | 10 | 13 | | 11 | 5 | | 12 | 11 | | 13 | 22 | | 14 | 20 | | 15 | 22 | | 16 | 20 | | 17 | 7 | | 18 | 21 | | 19 | 20 | | 20 | 30 | | 21 | 7 | | 22 | 4 | | 23 | 10 | | 24 | 38 | | 25 | 13 | | 26 | 11 | | 27 | 6 | | 28 | 11 | | 29 | 9 | | 30 | 5 | | 31 | 2 | | 32 | 4 | | 33 | 2 | | 34 | 1 | | 35 | 26 | | 36 | 18 | | 37 | 22 | | 38 | 7 | | 39 | 44 | | 40 | 7 | | 41 | 10 | | 42 | 7 | | 43 | 8 | | 44 | 36 | | 45 | 13 | | 46 | 10 | | 47 | 10 | | 48 | 9 | | 49 | 5 |
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| 36.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.312 | | totalSentences | 125 | | uniqueOpeners | 39 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 102 | | matches | (empty) | | ratio | 0 | |
| 59.22% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 102 | | matches | | 0 | "She descended the steps to" | | 1 | "He didn’t say a word." | | 2 | "He just pointed down the" | | 3 | "She’d smelled it before, three" | | 4 | "It was the Veil Market," | | 5 | "She stood near the edge" | | 6 | "She wore her usual academic" | | 7 | "She clutched the strap of" | | 8 | "she said, her voice low" | | 9 | "She didn’t have time for" | | 10 | "He was fully dressed, in" | | 11 | "His skin was drawn taut" | | 12 | "It was as if every" | | 13 | "She circled the body, her" | | 14 | "She gestured with her chin" | | 15 | "She could understand that." | | 16 | "She lowered it again." | | 17 | "She snapped on a pair" | | 18 | "She picked up the evidence" | | 19 | "It was spinning, a frantic," |
| | ratio | 0.402 | |
| 28.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 88 | | totalSentences | 102 | | matches | | 0 | "The air in Camden tasted" | | 1 | "She descended the steps to" | | 2 | "A uniformed constable, young and" | | 3 | "He didn’t say a word." | | 4 | "He just pointed down the" | | 5 | "Harlow’s footsteps echoed with military" | | 6 | "The air grew colder, carrying" | | 7 | "something like burnt sugar and" | | 8 | "She’d smelled it before, three" | | 9 | "The memory was a knot" | | 10 | "The abandoned platform wasn't abandoned." | | 11 | "It was the Veil Market," | | 12 | "The full moon was last" | | 13 | "The graffiti on the walls" | | 14 | "Eva Kowalski was already there," | | 15 | "She stood near the edge" | | 16 | "She wore her usual academic" | | 17 | "She clutched the strap of" | | 18 | "she said, her voice low" | | 19 | "Harlow replied, her tone flat" |
| | ratio | 0.863 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 102 | | matches | (empty) | | ratio | 0 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 3 | | matches | | 0 | "His skin was drawn taut over his bones like old parchment, his eyes sunken hollows in a skull that seemed too large for his shrunken frame." | | 1 | "It was as if every drop of fluid, every ounce of life, had been vacuumed out of him." | | 2 | "The market-goers had left their usual trail of litter—discarded wrappers, the husks of strange, glowing fruit—but there was a perfect, sterile circle around the…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 8 | | matches | | 0 | "She descended, the ones marked with peeling laminate promising a ‘future refurbishment" | | 1 | "she said, her voice low" | | 2 | "Harlow replied, her tone flat" | | 3 | "Eva insisted, her voice gaining a desperate edge" | | 4 | "she said, her voice quiet but clear" | | 5 | "she said, almost to herself" | | 6 | "Eva said, her voice barely a whisper" | | 7 | "Harlow said, the pieces clicking into place with a horrifying, silent finality" |
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| 89.39% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 2 | | fancyTags | | 0 | "Eva insisted (insist)" | | 1 | "Eva explained (explain)" |
| | dialogueSentences | 33 | | tagDensity | 0.424 | | leniency | 0.848 | | rawRatio | 0.143 | | effectiveRatio | 0.121 | |