| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva said softly [softly]" |
| | dialogueSentences | 31 | | tagDensity | 0.323 | | leniency | 0.645 | | rawRatio | 0.1 | | effectiveRatio | 0.065 | |
| 95.35% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1076 | | totalAiIsmAdverbs | 1 | | 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) | |
| 39.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1076 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "wavering" | | 1 | "silence" | | 2 | "tracing" | | 3 | "intricate" | | 4 | "etched" | | 5 | "standard" | | 6 | "pulse" | | 7 | "weight" | | 8 | "flicked" | | 9 | "stomach" | | 10 | "gloom" | | 11 | "flicker" |
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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 | 98 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 98 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 119 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 8 | | totalWords | 1070 | | ratio | 0.007 | | matches | | 0 | "Quinn, there’s something in the dark with me." |
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| 97.22% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 1 | | matches | | 0 | "Behind her, Eva gasped." |
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| 48.40% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 935 | | uniqueNames | 10 | | maxNameDensity | 2.03 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 19 | | Tube | 2 | | Camden | 1 | | Eva | 12 | | Kowalski | 1 | | Morris | 4 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Camden" | | 3 | "Eva" | | 4 | "Kowalski" | | 5 | "Morris" |
| | places | (empty) | | globalScore | 0.484 | | windowScore | 0.667 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | glossingSentenceCount | 4 | | matches | | 0 | "shadows that seemed to move when she wasn’t looking" | | 1 | "something like it before—three years ago, in" | | 2 | "looked like a cross between a rune and a" | | 3 | "looked like skin" |
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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 | 1070 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 119 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 22.77 | | std | 18.74 | | cv | 0.823 | | sampleLengths | | 0 | 57 | | 1 | 21 | | 2 | 49 | | 3 | 45 | | 4 | 60 | | 5 | 38 | | 6 | 13 | | 7 | 30 | | 8 | 20 | | 9 | 12 | | 10 | 46 | | 11 | 6 | | 12 | 57 | | 13 | 1 | | 14 | 33 | | 15 | 46 | | 16 | 5 | | 17 | 3 | | 18 | 24 | | 19 | 21 | | 20 | 5 | | 21 | 4 | | 22 | 10 | | 23 | 48 | | 24 | 10 | | 25 | 24 | | 26 | 38 | | 27 | 4 | | 28 | 34 | | 29 | 8 | | 30 | 14 | | 31 | 5 | | 32 | 72 | | 33 | 3 | | 34 | 30 | | 35 | 5 | | 36 | 32 | | 37 | 12 | | 38 | 3 | | 39 | 21 | | 40 | 5 | | 41 | 5 | | 42 | 13 | | 43 | 46 | | 44 | 12 | | 45 | 10 | | 46 | 10 |
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| 87.36% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 98 | | matches | | 0 | "been gutted" | | 1 | "been unzipped" | | 2 | "been sucked" | | 3 | "been buried" | | 4 | "been found" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 163 | | matches | | 0 | "wasn’t looking" | | 1 | "was speaking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 119 | | ratio | 0.059 | | matches | | 0 | "But his face—" | | 1 | "And the blood—there was barely any." | | 2 | "The lividity, the lack of rigor—this man hadn’t been dead long." | | 3 | "She’d seen something like it before—three years ago, in the pocket of DS Morris the night he vanished." | | 4 | "It looked like a cross between a rune and a child’s scribble—jagged lines intersecting at odd angles." | | 5 | "Not a modern door—this was iron, ancient, its surface pitted with age and more of those damn symbols." | | 6 | "But this—this was real." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 942 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.029723991507430998 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.0074309978768577496 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 119 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 119 | | mean | 8.99 | | std | 6.08 | | cv | 0.676 | | sampleLengths | | 0 | 17 | | 1 | 24 | | 2 | 16 | | 3 | 13 | | 4 | 8 | | 5 | 3 | | 6 | 9 | | 7 | 11 | | 8 | 21 | | 9 | 5 | | 10 | 18 | | 11 | 16 | | 12 | 8 | | 13 | 3 | | 14 | 8 | | 15 | 12 | | 16 | 16 | | 17 | 6 | | 18 | 18 | | 19 | 8 | | 20 | 20 | | 21 | 10 | | 22 | 4 | | 23 | 9 | | 24 | 5 | | 25 | 18 | | 26 | 7 | | 27 | 3 | | 28 | 3 | | 29 | 11 | | 30 | 3 | | 31 | 12 | | 32 | 5 | | 33 | 13 | | 34 | 5 | | 35 | 14 | | 36 | 9 | | 37 | 6 | | 38 | 6 | | 39 | 18 | | 40 | 14 | | 41 | 8 | | 42 | 11 | | 43 | 1 | | 44 | 13 | | 45 | 13 | | 46 | 7 | | 47 | 5 | | 48 | 15 | | 49 | 1 |
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| 58.54% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3865546218487395 | | totalSentences | 119 | | uniqueOpeners | 46 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 91 | | matches | | 0 | "Just a thin, dark line" | | 1 | "More symbols, these smaller, leading" | | 2 | "Then the symbols stopped." |
| | ratio | 0.033 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 91 | | matches | | 0 | "She didn’t answer." | | 1 | "His tie was still knotted," | | 2 | "His throat had been slit," | | 3 | "She peeled back the fabric." | | 4 | "She’d seen something like it" | | 5 | "She followed, Eva trailing behind." | | 6 | "It looked like a cross" | | 7 | "She didn’t believe in ghosts." | | 8 | "She forced the memory down." | | 9 | "It snaked between the old" | | 10 | "She’d heard the rumours, of" | | 11 | "It was Morris." | | 12 | "He smiled, and it was" | | 13 | "He held up the compass" | | 14 | "His gaze flicked past her," | | 15 | "It was the dead man" |
| | ratio | 0.176 | |
| 64.40% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 72 | | totalSentences | 91 | | matches | | 0 | "The bone token burned cold" | | 1 | "The abandoned Tube station beneath" | | 2 | "The flickering LED lanterns cast" | | 3 | "A uniformed officer nodded at" | | 4 | "She didn’t answer." | | 5 | "Words were for people who" | | 6 | "Quinn moved past him, her" | | 7 | "The station had been gutted" | | 8 | "The body lay sprawled near" | | 9 | "A man, mid-forties, dressed in" | | 10 | "His tie was still knotted," | | 11 | "Quinn crouched, gloved fingers hovering" | | 12 | "His throat had been slit," | | 13 | "The edges were too clean," | | 14 | "a voice said behind her" | | 15 | "Eva Kowalski adjusted her round" | | 16 | "Quinn didn’t look up." | | 17 | "Eva agreed, stepping closer" | | 18 | "The scent of old paper" | | 19 | "Quinn’s fingers twitched." |
| | ratio | 0.791 | |
| 54.95% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 91 | | matches | | 0 | "Now, it hosted something else." |
| | ratio | 0.011 | |
| 89.29% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 3 | | matches | | 0 | "The abandoned Tube station beneath Camden reeked of damp concrete and something older, something that made the hairs on her arms stand on end." | | 1 | "The flickering LED lanterns cast long, wavering shadows that seemed to move when she wasn’t looking." | | 2 | "Lanterns hung from chains, casting a sickly green light over tables laden with jars of things that squirmed, with weapons that hummed, with books bound in what …" |
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| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | 0 | "The case file had, the details labelled as" |
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| 53.23% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 3 | | fancyTags | | 0 | "Eva agreed (agree)" | | 1 | "Eva murmured (murmur)" | | 2 | "Quinn demanded (demand)" |
| | dialogueSentences | 31 | | tagDensity | 0.161 | | leniency | 0.323 | | rawRatio | 0.6 | | effectiveRatio | 0.194 | |