| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 25 | | adverbTagCount | 6 | | adverbTags | | 0 | "She gestured vaguely [vaguely]" | | 1 | "Her voice steadied slightly [slightly]" | | 2 | "she said quietly [quietly]" | | 3 | "she said slowly [slowly]" | | 4 | "Harlow turned back [back]" | | 5 | "she said quietly [quietly]" |
| | dialogueSentences | 57 | | tagDensity | 0.439 | | leniency | 0.877 | | rawRatio | 0.24 | | effectiveRatio | 0.211 | |
| 84.28% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1909 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "really" | | 3 | "suddenly" | | 4 | "very" |
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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) | |
| 84.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1909 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "familiar" | | 1 | "weight" | | 2 | "tracing" | | 3 | "structure" | | 4 | "etched" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 106 | | matches | (empty) | |
| 88.95% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 1 | | narrationSentences | 106 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 138 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 26 | | totalWords | 1891 | | ratio | 0.014 | | matches | | 0 | "M.W. - 11/14 - Unstable." | | 1 | "You think everything has to make sense, Quinn. You think if you just look hard enough, you'll find the rational explanation." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 1190 | | uniqueNames | 10 | | maxNameDensity | 1.43 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Harlow" | | discoveredNames | | Quinn | 2 | | Tube | 1 | | Met | 1 | | Harlow | 17 | | English | 1 | | Eleven-fourteen | 1 | | November | 1 | | Whitechapel | 2 | | Morris | 4 | | Eva | 8 |
| | persons | | 0 | "Quinn" | | 1 | "Harlow" | | 2 | "Morris" | | 3 | "Eva" |
| | places | | | globalScore | 0.786 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like ordinary teeth but were too l" |
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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 | 1891 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 138 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 33.77 | | std | 25.08 | | cv | 0.743 | | sampleLengths | | 0 | 51 | | 1 | 77 | | 2 | 26 | | 3 | 2 | | 4 | 90 | | 5 | 54 | | 6 | 34 | | 7 | 31 | | 8 | 36 | | 9 | 37 | | 10 | 4 | | 11 | 16 | | 12 | 10 | | 13 | 76 | | 14 | 6 | | 15 | 46 | | 16 | 8 | | 17 | 71 | | 18 | 34 | | 19 | 15 | | 20 | 15 | | 21 | 2 | | 22 | 63 | | 23 | 71 | | 24 | 19 | | 25 | 38 | | 26 | 3 | | 27 | 27 | | 28 | 3 | | 29 | 65 | | 30 | 3 | | 31 | 72 | | 32 | 3 | | 33 | 54 | | 34 | 55 | | 35 | 5 | | 36 | 30 | | 37 | 59 | | 38 | 17 | | 39 | 27 | | 40 | 103 | | 41 | 38 | | 42 | 21 | | 43 | 23 | | 44 | 37 | | 45 | 42 | | 46 | 2 | | 47 | 18 | | 48 | 29 | | 49 | 35 |
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| 82.09% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 106 | | matches | | 0 | "being prepared" | | 1 | "been decommissioned" | | 2 | "been converted" | | 3 | "been labeled" | | 4 | "been closed" | | 5 | "been destroyed" | | 6 | "been extracted" | | 7 | "been found" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 211 | | matches | | 0 | "was looking" | | 1 | "was spinning" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 15 | | semicolonCount | 0 | | flaggedSentences | 12 | | totalSentences | 138 | | ratio | 0.087 | | matches | | 0 | "The uniforms had done their work—perimeter secured, witnesses questioned, area clear—but they'd called her in anyway." | | 1 | "The station had been decommissioned in 1986 and officially demolished on paper, but the lower levels remained—a labyrinth of abandoned passages and closed platforms that urban explorers loved to photograph and occasionally died in." | | 2 | "Harlow crouched beside the thermal blanket and studied what remained of his face—handsome before whatever had happened to him, the kind of face that belonged in a city that fed on ambition." | | 3 | "Something else—geometric patterns, almost like..." | | 4 | "The shelves held jars—hundreds of them—filled with liquids of varying colors and viscosities." | | 5 | "She couldn't read most of them—the script wasn't English, or any language she recognized—but one near the end had been labeled in careful handwriting: *M.W." | | 6 | "- 11/14 - Unstable.*" | | 7 | "Another officer had bagged the fragment and set it on an evidence table beside the other items—notebooks with strange diagrams, a compass with a greenish patina, a handful of what looked like ordinary teeth but were too large, too sharp." | | 8 | "\"Detective Quinn.\" The voice came from behind her—female, educated accent, faintly nervous." | | 9 | "It wasn't that tissue had been destroyed—it was that something had been extracted." | | 10 | "Harlow looked at her—really looked, past the nervous habit of tucking hair behind her ear, past the scholarly demeanor, past the glasses that suddenly seemed less like a weakness and more like a deliberate choice." | | 11 | "\"And I know who you're looking for. But finding him and finding the truth about this—\" she gestured at the body, the shelves, the door \"—may not be the same thing.\"" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1225 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 47 | | adverbRatio | 0.03836734693877551 | | lyAdverbCount | 22 | | lyAdverbRatio | 0.017959183673469388 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 138 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 138 | | mean | 13.7 | | std | 10.87 | | cv | 0.793 | | sampleLengths | | 0 | 20 | | 1 | 31 | | 2 | 4 | | 3 | 19 | | 4 | 22 | | 5 | 16 | | 6 | 16 | | 7 | 16 | | 8 | 10 | | 9 | 2 | | 10 | 21 | | 11 | 34 | | 12 | 7 | | 13 | 28 | | 14 | 7 | | 15 | 9 | | 16 | 2 | | 17 | 2 | | 18 | 2 | | 19 | 32 | | 20 | 10 | | 21 | 20 | | 22 | 4 | | 23 | 31 | | 24 | 3 | | 25 | 17 | | 26 | 8 | | 27 | 3 | | 28 | 5 | | 29 | 7 | | 30 | 20 | | 31 | 10 | | 32 | 4 | | 33 | 16 | | 34 | 8 | | 35 | 2 | | 36 | 10 | | 37 | 21 | | 38 | 13 | | 39 | 3 | | 40 | 13 | | 41 | 16 | | 42 | 6 | | 43 | 17 | | 44 | 25 | | 45 | 4 | | 46 | 1 | | 47 | 3 | | 48 | 4 | | 49 | 21 |
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| 59.90% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.39855072463768115 | | totalSentences | 138 | | uniqueOpeners | 55 | |
| 34.72% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 96 | | matches | | 0 | "Then it stopped, pointing directly" |
| | ratio | 0.01 | |
| 82.50% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 96 | | matches | | 0 | "She hadn't worked a Tube" | | 1 | "They'd brought it up to" | | 2 | "He led her down the" | | 3 | "she said, more to herself" | | 4 | "She leaned closer, narrowing her" | | 5 | "She was looking at his" | | 6 | "He pointed toward the maintenance" | | 7 | "She couldn't read most of" | | 8 | "Her hand went to the" | | 9 | "They'd found his badge in" | | 10 | "She'd asked what he'd found." | | 11 | "He'd said he'd found something" | | 12 | "She turned to the sergeant" | | 13 | "They walked back up the" | | 14 | "It was a token, she" | | 15 | "*You think everything has to" | | 16 | "You think if you just" | | 17 | "She clutched a worn leather" | | 18 | "She gestured vaguely at the" | | 19 | "Her voice steadied slightly, the" |
| | ratio | 0.344 | |
| 22.50% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 96 | | matches | | 0 | "The tunnel stretched before her" | | 1 | "Harlow Quinn stood at the" | | 2 | "This wasn't her jurisdiction." | | 3 | "She hadn't worked a Tube" | | 4 | "They'd brought it up to" | | 5 | "The uniforms had done their" | | 6 | "The DI at the Met" | | 7 | "A uniformed sergeant approached, his" | | 8 | "He led her down the" | | 9 | "The station had been decommissioned" | | 10 | "Someone had been using this" | | 11 | "The track bed showed clear" | | 12 | "The body lay where they'd" | | 13 | "Harlow crouched beside the thermal" | | 14 | "she said, more to herself" | | 15 | "She leaned closer, narrowing her" | | 16 | "Harlow said nothing." | | 17 | "She was looking at his" | | 18 | "Something else—geometric patterns, almost like..." | | 19 | "The sergeant shifted his weight" |
| | ratio | 0.875 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 96 | | matches | (empty) | | ratio | 0 | |
| 57.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 5 | | matches | | 0 | "Someone had cleared the old equipment, swept the floors, and installed a series of heavy wooden shelves that lined both walls." | | 1 | "Her hand went to the worn leather watch on her wrist, pressing against the cold metal as if to anchor herself." | | 2 | "The woman standing at the edge of the scene was small, red-haired, freckled, wearing round glasses that magnified her green eyes into something owlish." | | 3 | "Something that might have looked, to the right kind of observer, like a small and luminous flame." | | 4 | "Her eyes searched Harlow's face, reading something there that made her expression shift from fear to something more complicated." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 25 | | uselessAdditionCount | 5 | | matches | | 0 | "sergeant approached, his face young and faintly green beneath the harsh lights" | | 1 | "she said, more to herself than the sergeant" | | 2 | "Her voice steadied slightly, the nervousness channeling into academic certainty" | | 3 | "the sergeant said, his voice thin" | | 4 | "she gestured, the shelves, the door" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | 0 | "the sergeant breathed (breathe)" |
| | dialogueSentences | 57 | | tagDensity | 0.123 | | leniency | 0.246 | | rawRatio | 0.143 | | effectiveRatio | 0.035 | |