| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn glanced back [back]" |
| | dialogueSentences | 21 | | tagDensity | 0.524 | | leniency | 1 | | rawRatio | 0.091 | | effectiveRatio | 0.091 | |
| 90.40% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1563 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "nervously" | | 1 | "softly" | | 2 | "sharply" |
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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) | |
| 52.02% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1563 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "wavering" | | 1 | "weight" | | 2 | "pulsed" | | 3 | "etched" | | 4 | "searing" | | 5 | "chill" | | 6 | "stomach" | | 7 | "could feel" | | 8 | "traced" | | 9 | "familiar" | | 10 | "tension" |
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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 | 105 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 105 | | filterMatches | (empty) | | hedgeMatches | | |
| 97.40% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 1 | | adjustedGibberishSentences | 1 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 59 | | ratio | 0.009 | | matches | | 0 | "Getkel set his pen down to rub at his own reddened своём nose." |
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| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1556 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 65.19% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 81 | | wordCount | 1297 | | uniqueNames | 40 | | maxNameDensity | 1.7 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Quinn | 22 | | Tony | 2 | | Davies | 1 | | Navy | 1 | | Drains | 1 | | You | 2 | | Key | 1 | | Flotational | 1 | | Victim | 1 | | Kool-Aid | 1 | | Flotant | 3 | | Men | 1 | | Don | 1 | | Crave | 1 | | Glory | 1 | | Brown | 1 | | Eternal | 1 | | Army | 1 | | Loyal | 1 | | Killed | 1 | | Man | 1 | | Mrs | 1 | | Pears | 1 | | Lavender | 1 | | Westside | 1 | | Medical | 1 | | Examiner | 1 | | Carved | 2 | | Getkel | 11 | | Fresh | 1 | | Fruit | 1 | | Strips | 1 | | Blood | 2 | | Docs | 1 | | Onscreen | 1 | | Noe | 1 | | Brunan | 1 | | John | 3 | | Beal | 3 |
| | persons | | 0 | "Detective" | | 1 | "Quinn" | | 2 | "Tony" | | 3 | "Davies" | | 4 | "You" | | 5 | "Victim" | | 6 | "Flotant" | | 7 | "Men" | | 8 | "Glory" | | 9 | "Brown" | | 10 | "Man" | | 11 | "Mrs" | | 12 | "Examiner" | | 13 | "Carved" | | 14 | "Getkel" | | 15 | "Blood" | | 16 | "Noe" | | 17 | "Brunan" | | 18 | "John" |
| | places | | | globalScore | 0.652 | | windowScore | 0.667 | |
| 92.53% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | glossingSentenceCount | 2 | | matches | | 0 | "ftly remarked, obviously unaware of her ment" | | 1 | "as if answering a question she hadn't posed, Getkel re-entered the coroner's domain bearing the corpse" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.643 | | wordCount | 1556 | | matches | | 0 | "Not one of Brunan's standoffish notes either but an explosion of ink" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 114 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 38.9 | | std | 20.78 | | cv | 0.534 | | sampleLengths | | 0 | 31 | | 1 | 55 | | 2 | 45 | | 3 | 43 | | 4 | 56 | | 5 | 44 | | 6 | 34 | | 7 | 39 | | 8 | 54 | | 9 | 27 | | 10 | 33 | | 11 | 5 | | 12 | 38 | | 13 | 33 | | 14 | 56 | | 15 | 5 | | 16 | 21 | | 17 | 13 | | 18 | 67 | | 19 | 104 | | 20 | 60 | | 21 | 28 | | 22 | 29 | | 23 | 57 | | 24 | 14 | | 25 | 57 | | 26 | 42 | | 27 | 4 | | 28 | 31 | | 29 | 40 | | 30 | 50 | | 31 | 41 | | 32 | 6 | | 33 | 84 | | 34 | 56 | | 35 | 17 | | 36 | 40 | | 37 | 41 | | 38 | 25 | | 39 | 31 |
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| 95.24% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 105 | | matches | | 0 | "been etched" | | 1 | "was said" | | 2 | "were rendered" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 218 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 114 | | ratio | 0.009 | | matches | | 0 | "Under his left arm was painted BEAL - Brown's Eternal Army Loyal." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1253 | | adjectiveStacks | 1 | | stackExamples | | 0 | "under blood-stained Getkel" |
| | adverbCount | 29 | | adverbRatio | 0.02314445331205108 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.011971268954509178 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 13.65 | | std | 8.97 | | cv | 0.657 | | sampleLengths | | 0 | 13 | | 1 | 9 | | 2 | 9 | | 3 | 11 | | 4 | 16 | | 5 | 10 | | 6 | 18 | | 7 | 14 | | 8 | 22 | | 9 | 6 | | 10 | 3 | | 11 | 43 | | 12 | 16 | | 13 | 12 | | 14 | 16 | | 15 | 12 | | 16 | 7 | | 17 | 4 | | 18 | 13 | | 19 | 20 | | 20 | 6 | | 21 | 12 | | 22 | 16 | | 23 | 8 | | 24 | 7 | | 25 | 11 | | 26 | 13 | | 27 | 21 | | 28 | 21 | | 29 | 12 | | 30 | 8 | | 31 | 19 | | 32 | 20 | | 33 | 13 | | 34 | 13 | | 35 | 15 | | 36 | 14 | | 37 | 1 | | 38 | 17 | | 39 | 3 | | 40 | 13 | | 41 | 56 | | 42 | 5 | | 43 | 21 | | 44 | 4 | | 45 | 5 | | 46 | 4 | | 47 | 17 | | 48 | 16 | | 49 | 18 |
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| 85.09% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5263157894736842 | | totalSentences | 114 | | uniqueOpeners | 60 | |
| 33.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 99 | | matches | | 0 | "Then, as if answering a" |
| | ratio | 0.01 | |
| 98.79% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 99 | | matches | | 0 | "Her torch cut a wavering" | | 1 | "Her lover's Navy t-shirt, given" | | 2 | "She hated Drains, with their" | | 3 | "You never knew what you'd" | | 4 | "She rubbed her belly, feeling" | | 5 | "She lowered her face, coming" | | 6 | "She knew this man." | | 7 | "His clean shave and groom" | | 8 | "She could easily lift him" | | 9 | "I Killed a Man Here" | | 10 | "You get a wash all" | | 11 | "She shook her head." | | 12 | "They moved him to the" | | 13 | "His right eye held close" | | 14 | "She could feel the momentum" | | 15 | "She stared down at the" | | 16 | "She swore they pulsed against" | | 17 | "It was a smell that" | | 18 | "She did it swiftly, to" | | 19 | "She held up a silver" |
| | ratio | 0.303 | |
| 45.86% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 99 | | matches | | 0 | "The storm drain gurgled as" | | 1 | "Her torch cut a wavering" | | 2 | "DC Tony Davies obligingly panned" | | 3 | "Teflon boots snickered as Quinn" | | 4 | "Her lover's Navy t-shirt, given" | | 5 | "Quinn dipped a gloved finger" | | 6 | "She hated Drains, with their" | | 7 | "You never knew what you'd" | | 8 | "Sanitation was Key." | | 9 | "She rubbed her belly, feeling" | | 10 | "The dead weight lifted and" | | 11 | "She lowered her face, coming" | | 12 | "Blood from his lacerated mouth" | | 13 | "Quinn rolled metaphorical sleeves of" | | 14 | "She knew this man." | | 15 | "The lavender scent of his" | | 16 | "His clean shave and groom" | | 17 | "This man had been history," | | 18 | "The noose eccentrically dangled above" | | 19 | "The wool constricting his neck" |
| | ratio | 0.828 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 99 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 65 | | technicalSentenceCount | 3 | | matches | | 0 | "His clean shave and groom fingered him as a cultivated urban pro who'd given an abundant life buying society's Kool-Aid." | | 1 | "It was a smell that made her question why she still had a job." | | 2 | "Then, as if answering a question she hadn't posed, Getkel re-entered the coroner's domain bearing the corpse." |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn circled, torchlight dusting across his blistered skin" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 21 | | tagDensity | 0.095 | | leniency | 0.19 | | rawRatio | 0.5 | | effectiveRatio | 0.095 | |