| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva protested weakly [weakly]" |
| | dialogueSentences | 42 | | tagDensity | 0.405 | | leniency | 0.81 | | rawRatio | 0.059 | | effectiveRatio | 0.048 | |
| 76.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1503 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "slightly" | | 1 | "loosely" | | 2 | "slowly" | | 3 | "nervously" | | 4 | "really" | | 5 | "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) | |
| 70.06% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1503 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "cacophony" | | 1 | "silence" | | 2 | "echoed" | | 3 | "etched" | | 4 | "vibrated" | | 5 | "perfect" | | 6 | "mechanical" | | 7 | "weight" |
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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 | 102 | | matches | (empty) | |
| 58.82% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 5 | | narrationSentences | 102 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 127 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1496 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 65 | | wordCount | 1168 | | uniqueNames | 12 | | maxNameDensity | 2.31 | | worstName | "Harlow" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Harlow" | | discoveredNames | | Camden | 1 | | Harlow | 27 | | Quinn | 2 | | Maglite | 1 | | London | 1 | | Silas | 4 | | Vane | 10 | | Northern | 1 | | Line | 1 | | Eva | 14 | | Morris | 1 | | Shoreditch | 2 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Silas" | | 4 | "Vane" | | 5 | "Eva" | | 6 | "Morris" |
| | places | | | globalScore | 0.344 | | windowScore | 0.167 | |
| 53.85% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like an overdose" | | 1 | "looked like a deflated balloon, his skin" | | 2 | "It was as if the man had simply sat down and evaporated from the inside out" |
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| 66.31% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.337 | | wordCount | 1496 | | matches | | 0 | "not with cardinal directions, but with angular, shifting sigils" | | 1 | "not the mechanical rumble of a distant train, but a groan of metal twisting under immense pressure" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 127 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 31.17 | | std | 22.71 | | cv | 0.729 | | sampleLengths | | 0 | 94 | | 1 | 50 | | 2 | 56 | | 3 | 14 | | 4 | 6 | | 5 | 45 | | 6 | 31 | | 7 | 48 | | 8 | 13 | | 9 | 14 | | 10 | 57 | | 11 | 25 | | 12 | 41 | | 13 | 18 | | 14 | 43 | | 15 | 52 | | 16 | 36 | | 17 | 39 | | 18 | 3 | | 19 | 68 | | 20 | 33 | | 21 | 20 | | 22 | 82 | | 23 | 34 | | 24 | 13 | | 25 | 37 | | 26 | 1 | | 27 | 43 | | 28 | 18 | | 29 | 6 | | 30 | 57 | | 31 | 6 | | 32 | 61 | | 33 | 17 | | 34 | 5 | | 35 | 15 | | 36 | 17 | | 37 | 6 | | 38 | 3 | | 39 | 16 | | 40 | 5 | | 41 | 34 | | 42 | 25 | | 43 | 51 | | 44 | 19 | | 45 | 14 | | 46 | 26 | | 47 | 79 |
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| 98.38% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 102 | | matches | | 0 | "been dissolved" | | 1 | "was dusted" |
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| 30.80% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 197 | | matches | | 0 | "was sitting" | | 1 | "was acting" | | 2 | "were dissolving" | | 3 | "was pointing" | | 4 | "were already moving" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 5 | | flaggedSentences | 10 | | totalSentences | 127 | | ratio | 0.079 | | matches | | 0 | "She had followed the breadcrumbs of a missing persons report—a low-level fence named Silas Vane—straight to a boarded-up access point of the Northern Line." | | 1 | "This wasn’t just an abandoned maintenance shaft; the space opened up into a platform that shouldn’t have existed on any city map." | | 2 | "He hadn't been dead for days; the coffee cup next to his boot was still warm." | | 3 | "She nervously tucked a stray curl of hair behind her left ear—a tick Harlow had seen a dozen times during previous interrogations." | | 4 | "The needle inside didn't float; it vibrated, snapping erratically." | | 5 | "He had looked similar—drained, empty, the physics of his death defying the coroner’s report." | | 6 | "The young woman wasn't acting like a criminal caught in the act; she was acting like a bomb disposal technician watching someone play with a wire." | | 7 | "Beneath the hem, the skin wasn't just grey; it was dusted with a fine white powder." | | 8 | "The concrete details she relied on—fingerprints, motive, ballistics—were dissolving." | | 9 | "A low sound began to hum through the tracks—not the mechanical rumble of a distant train, but a groan of metal twisting under immense pressure." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1178 | | adjectiveStacks | 1 | | stackExamples | | 0 | "twisting under immense pressure." |
| | adverbCount | 34 | | adverbRatio | 0.028862478777589132 | | lyAdverbCount | 17 | | lyAdverbRatio | 0.014431239388794566 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 127 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 127 | | mean | 11.78 | | std | 7.39 | | cv | 0.627 | | sampleLengths | | 0 | 26 | | 1 | 30 | | 2 | 27 | | 3 | 11 | | 4 | 10 | | 5 | 2 | | 6 | 24 | | 7 | 9 | | 8 | 5 | | 9 | 17 | | 10 | 22 | | 11 | 17 | | 12 | 8 | | 13 | 6 | | 14 | 6 | | 15 | 15 | | 16 | 9 | | 17 | 21 | | 18 | 8 | | 19 | 9 | | 20 | 14 | | 21 | 4 | | 22 | 4 | | 23 | 24 | | 24 | 16 | | 25 | 13 | | 26 | 12 | | 27 | 2 | | 28 | 9 | | 29 | 15 | | 30 | 15 | | 31 | 18 | | 32 | 7 | | 33 | 5 | | 34 | 13 | | 35 | 5 | | 36 | 22 | | 37 | 14 | | 38 | 18 | | 39 | 11 | | 40 | 27 | | 41 | 5 | | 42 | 11 | | 43 | 7 | | 44 | 5 | | 45 | 13 | | 46 | 16 | | 47 | 17 | | 48 | 19 | | 49 | 19 |
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| 49.87% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3464566929133858 | | totalSentences | 127 | | uniqueOpeners | 44 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 99 | | matches | (empty) | | ratio | 0 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 99 | | matches | | 0 | "She adjusted the beam of" | | 1 | "It was a heavy, suffocating" | | 2 | "She had followed the breadcrumbs" | | 3 | "She stepped over a pile" | | 4 | "She advanced with the military" | | 5 | "Her boots made no sound" | | 6 | "She found Silas Vane twenty" | | 7 | "He hadn't been dead for" | | 8 | "She wore a heavy coat" | | 9 | "She didn't lower the weapon." | | 10 | "She nervously tucked a stray" | | 11 | "She trailed off, seeing the" | | 12 | "She turned her attention back" | | 13 | "It was as if the" | | 14 | "She gestured vaguely at the" | | 15 | "It was a brass compass," | | 16 | "It was cold, heavier than" | | 17 | "She frowned, the headache that" | | 18 | "She thought of Morris." | | 19 | "He had looked similar—drained, empty," |
| | ratio | 0.333 | |
| 25.66% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 86 | | totalSentences | 99 | | matches | | 0 | "The damp air beneath Camden" | | 1 | "She adjusted the beam of" | | 2 | "It was a heavy, suffocating" | | 3 | "Harlow checked the worn leather" | | 4 | "She had followed the breadcrumbs" | | 5 | "The padlock had been dissolved" | | 6 | "That was the first irregularity." | | 7 | "She stepped over a pile" | | 8 | "This wasn’t just an abandoned" | | 9 | "The air grew colder, biting" | | 10 | "Harlow shouted, her voice cracking" | | 11 | "Nothing but the drip of" | | 12 | "She advanced with the military" | | 13 | "Her boots made no sound" | | 14 | "She found Silas Vane twenty" | | 15 | "Vane was sitting up, head" | | 16 | "Vane looked like a deflated" | | 17 | "He hadn't been dead for" | | 18 | "a voice echoed from the" | | 19 | "Harlow spun, her sidearm clearing" |
| | ratio | 0.869 | |
| 50.51% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 99 | | matches | | 0 | "Even in the harsh glare" |
| | ratio | 0.01 | |
| 76.41% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 4 | | matches | | 0 | "This wasn’t just an abandoned maintenance shaft; the space opened up into a platform that shouldn’t have existed on any city map." | | 1 | "The air grew colder, biting through her coat, smelling of ozone and something sweet, like rotting lilies." | | 2 | "She found Silas Vane twenty yards down the platform, slumped against a ticket booth that advertised prices from four decades ago." | | 3 | "Vane looked like a deflated balloon, his skin grey and papery, draped loosely over a skeletal frame that seemed too small for the clothes." |
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| 7.35% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 4 | | matches | | 0 | "Harlow shouted, her voice cracking the silence" | | 1 | "Harlow said, her tone flat" | | 2 | "Harlow said, her voice dropping an octave" | | 3 | "Eva protested weakly, though her feet were already moving" |
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| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 6 | | fancyTags | | 0 | "Harlow shouted (shout)" | | 1 | "Harlow corrected (correct)" | | 2 | "Eva insisted (insist)" | | 3 | "Eva whispered (whisper)" | | 4 | "Eva protested weakly (protest)" | | 5 | "Harlow snapped (snap)" |
| | dialogueSentences | 42 | | tagDensity | 0.262 | | leniency | 0.524 | | rawRatio | 0.545 | | effectiveRatio | 0.286 | |