| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said mildly [mildly]" |
| | dialogueSentences | 2 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |
| 93.35% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2256 | | totalAiIsmAdverbs | 3 | | found | | 0 | | adverb | "deliberately" | | count | 1 |
| | 1 | | | 2 | |
| | highlights | | 0 | "deliberately" | | 1 | "suddenly" | | 2 | "slowly" |
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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) | |
| 73.40% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2256 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "pulsed" | | 1 | "tracing" | | 2 | "stomach" | | 3 | "flicked" | | 4 | "footsteps" | | 5 | "shimmered" | | 6 | "weight" | | 7 | "familiar" | | 8 | "scanned" | | 9 | "pulse" | | 10 | "throbbed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 210 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 5 | | narrationSentences | 210 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 210 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2255 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 2252 | | uniqueNames | 9 | | maxNameDensity | 0.93 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 4 | | Quinn | 21 | | One | 1 | | Camden | 2 | | London | 2 | | Morris | 3 | | Market | 3 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Quinn" | | 3 | "One" | | 4 | "Camden" | | 5 | "Morris" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Market" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 97.92% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 144 | | glossingSentenceCount | 3 | | matches | | 0 | "her face too obviously police even without" | | 1 | "as if expecting someone else to come down behind her" | | 2 | "as if warning her" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 0.887 | | wordCount | 2255 | | matches | | 0 | "Not a full run yet, but" | | 1 | "not from bulbs but from strings of lanterns" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 210 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 75 | | mean | 30.07 | | std | 26.27 | | cv | 0.874 | | sampleLengths | | 0 | 44 | | 1 | 73 | | 2 | 50 | | 3 | 107 | | 4 | 9 | | 5 | 72 | | 6 | 19 | | 7 | 8 | | 8 | 3 | | 9 | 4 | | 10 | 4 | | 11 | 50 | | 12 | 18 | | 13 | 62 | | 14 | 3 | | 15 | 2 | | 16 | 64 | | 17 | 64 | | 18 | 6 | | 19 | 10 | | 20 | 13 | | 21 | 75 | | 22 | 21 | | 23 | 14 | | 24 | 31 | | 25 | 9 | | 26 | 7 | | 27 | 70 | | 28 | 10 | | 29 | 71 | | 30 | 9 | | 31 | 49 | | 32 | 2 | | 33 | 29 | | 34 | 13 | | 35 | 9 | | 36 | 41 | | 37 | 12 | | 38 | 30 | | 39 | 39 | | 40 | 4 | | 41 | 33 | | 42 | 38 | | 43 | 14 | | 44 | 4 | | 45 | 56 | | 46 | 31 | | 47 | 59 | | 48 | 11 | | 49 | 62 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 210 | | matches | | 0 | "been shuttered" | | 1 | "was gone" | | 2 | "been rigged" |
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| 72.15% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 7 | | totalVerbs | 365 | | matches | | 0 | "was watching" | | 1 | "was going" | | 2 | "weren’t going" | | 3 | "was carrying" | | 4 | "was almost calming" | | 5 | "was speaking" | | 6 | "was already backing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 210 | | ratio | 0.01 | | matches | | 0 | "Quinn caught only the briefest view of his face before he turned—pale cheek, sharp nose, eyes too alert for a man who wanted to look anonymous." | | 1 | "Somewhere in the crush and the dim, he had to be—" |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2258 | | adjectiveStacks | 1 | | stackExamples | | 0 | "same hard, watchful stillness." |
| | adverbCount | 86 | | adverbRatio | 0.03808680248007086 | | lyAdverbCount | 18 | | lyAdverbRatio | 0.007971656333038087 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 210 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 210 | | mean | 10.74 | | std | 8.07 | | cv | 0.752 | | sampleLengths | | 0 | 10 | | 1 | 34 | | 2 | 32 | | 3 | 24 | | 4 | 17 | | 5 | 11 | | 6 | 9 | | 7 | 2 | | 8 | 28 | | 9 | 11 | | 10 | 2 | | 11 | 13 | | 12 | 17 | | 13 | 7 | | 14 | 24 | | 15 | 33 | | 16 | 9 | | 17 | 25 | | 18 | 21 | | 19 | 26 | | 20 | 6 | | 21 | 4 | | 22 | 9 | | 23 | 8 | | 24 | 3 | | 25 | 4 | | 26 | 4 | | 27 | 20 | | 28 | 15 | | 29 | 15 | | 30 | 9 | | 31 | 6 | | 32 | 3 | | 33 | 19 | | 34 | 15 | | 35 | 16 | | 36 | 12 | | 37 | 3 | | 38 | 2 | | 39 | 8 | | 40 | 24 | | 41 | 4 | | 42 | 2 | | 43 | 26 | | 44 | 14 | | 45 | 16 | | 46 | 4 | | 47 | 30 | | 48 | 6 | | 49 | 10 |
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| 53.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 24 | | diversityRatio | 0.3904761904761905 | | totalSentences | 210 | | uniqueOpeners | 82 | |
| 53.48% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 187 | | matches | | 0 | "Then he went fast." | | 1 | "Somewhere in the crush and" | | 2 | "Somewhere metal clanged hard enough" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 187 | | matches | | 0 | "Her left wrist felt heavier" | | 1 | "She glanced down at the" | | 2 | "She’d been there nearly two" | | 3 | "She knew because she’d spent" | | 4 | "He was maybe thirty, medium" | | 5 | "He looked right at the" | | 6 | "His gaze snagged there for" | | 7 | "She came out of the" | | 8 | "She ignored it." | | 9 | "His stride broke." | | 10 | "He was faster than he’d" | | 11 | "He nearly went under the" | | 12 | "She saw the man turn" | | 13 | "He knew where he was" | | 14 | "He had a destination." | | 15 | "They would not accept a" | | 16 | "She had spent months trying" | | 17 | "She could hear something distant" | | 18 | "She took the first step" | | 19 | "It lay on the landing" |
| | ratio | 0.257 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 133 | | totalSentences | 187 | | matches | | 0 | "The green neon sign above" | | 1 | "Quinn stood across the street" | | 2 | "Tonight she was a dark" | | 3 | "Her left wrist felt heavier" | | 4 | "She glanced down at the" | | 5 | "She’d been there nearly two" | | 6 | "The Nest looked ordinary if" | | 7 | "A narrow door that let" | | 8 | "She knew because she’d spent" | | 9 | "The man came out through" | | 10 | "He was maybe thirty, medium" | | 11 | "Quinn caught only the briefest" | | 12 | "He looked right at the" | | 13 | "His gaze snagged there for" | | 14 | "Quinn didn’t move." | | 15 | "The man kept walking." | | 16 | "Quinn was off the curb" | | 17 | "She came out of the" | | 18 | "a voice barked from the" | | 19 | "She ignored it." |
| | ratio | 0.711 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 187 | | matches | | 0 | "Now she wished she’d asked" | | 1 | "If she turned around now," | | 2 | "If she chased him farther" | | 3 | "If she stayed where she" |
| | ratio | 0.021 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 98 | | technicalSentenceCount | 4 | | matches | | 0 | "Quinn caught only the briefest view of his face before he turned—pale cheek, sharp nose, eyes too alert for a man who wanted to look anonymous." | | 1 | "Not a full run yet, but that quickening stride of someone who’d seen enough to know he was already late." | | 2 | "The old ticket hall opened below her in pieces, first the edge of a broken sign, then a slab of platform, then a wash of light that came not from bulbs but from…" | | 3 | "He looked past her shoulder, toward the stairwell, as if expecting someone else to come down behind her." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 2 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |