| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 55 | | tagDensity | 0.218 | | leniency | 0.436 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1530 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 37.91% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1530 | | totalAiIsms | 19 | | found | | | highlights | | 0 | "gloom" | | 1 | "rhythmic" | | 2 | "silence" | | 3 | "perfect" | | 4 | "intensity" | | 5 | "familiar" | | 6 | "apprehension" | | 7 | "weight" | | 8 | "flicker" | | 9 | "echoed" | | 10 | "footsteps" | | 11 | "etch" | | 12 | "shattered" |
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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 | 109 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 109 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 152 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 6 | | totalWords | 1530 | | ratio | 0.004 | | matches | | 0 | "Eva Kowalski." | | 1 | "Click. Drag. Click. Drag." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1036 | | uniqueNames | 11 | | maxNameDensity | 1.16 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Harlow" | | discoveredNames | | Quinn | 1 | | Camden | 1 | | Tube | 1 | | Miller | 11 | | London | 1 | | Underground | 1 | | Harlow | 12 | | Morris | 1 | | Metropolitan | 1 | | Police | 1 | | North | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Miller" | | 2 | "Harlow" | | 3 | "Morris" |
| | places | | | globalScore | 0.921 | | windowScore | 0.833 | |
| 80.56% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like a countdown" | | 1 | "sockets that seemed to drink the light rather than reflect it" |
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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 | 1530 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 152 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 81 | | mean | 18.89 | | std | 16.76 | | cv | 0.887 | | sampleLengths | | 0 | 4 | | 1 | 47 | | 2 | 15 | | 3 | 41 | | 4 | 12 | | 5 | 43 | | 6 | 44 | | 7 | 64 | | 8 | 1 | | 9 | 14 | | 10 | 13 | | 11 | 2 | | 12 | 34 | | 13 | 4 | | 14 | 29 | | 15 | 10 | | 16 | 43 | | 17 | 7 | | 18 | 13 | | 19 | 63 | | 20 | 4 | | 21 | 26 | | 22 | 9 | | 23 | 5 | | 24 | 4 | | 25 | 57 | | 26 | 8 | | 27 | 55 | | 28 | 18 | | 29 | 8 | | 30 | 25 | | 31 | 6 | | 32 | 5 | | 33 | 19 | | 34 | 30 | | 35 | 10 | | 36 | 56 | | 37 | 16 | | 38 | 2 | | 39 | 11 | | 40 | 9 | | 41 | 15 | | 42 | 33 | | 43 | 30 | | 44 | 28 | | 45 | 10 | | 46 | 12 | | 47 | 1 | | 48 | 12 | | 49 | 4 |
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| 95.61% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 109 | | matches | | 0 | "been closed" | | 1 | "was replaced" | | 2 | "being pulled" |
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| 81.66% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 169 | | matches | | 0 | "was watching" | | 1 | "were speaking" | | 2 | "was using" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 152 | | ratio | 0.007 | | matches | | 0 | "It didn't walk; it unfolded." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1038 | | adjectiveStacks | 1 | | stackExamples | | 0 | "heavy, pressing against her" |
| | adverbCount | 17 | | adverbRatio | 0.016377649325626204 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.007707129094412331 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 152 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 152 | | mean | 10.07 | | std | 6.69 | | cv | 0.665 | | sampleLengths | | 0 | 4 | | 1 | 22 | | 2 | 8 | | 3 | 17 | | 4 | 15 | | 5 | 10 | | 6 | 19 | | 7 | 12 | | 8 | 12 | | 9 | 7 | | 10 | 22 | | 11 | 14 | | 12 | 6 | | 13 | 8 | | 14 | 30 | | 15 | 9 | | 16 | 28 | | 17 | 27 | | 18 | 1 | | 19 | 3 | | 20 | 11 | | 21 | 13 | | 22 | 2 | | 23 | 11 | | 24 | 14 | | 25 | 9 | | 26 | 4 | | 27 | 29 | | 28 | 10 | | 29 | 22 | | 30 | 3 | | 31 | 18 | | 32 | 7 | | 33 | 13 | | 34 | 9 | | 35 | 16 | | 36 | 7 | | 37 | 5 | | 38 | 15 | | 39 | 11 | | 40 | 4 | | 41 | 7 | | 42 | 11 | | 43 | 8 | | 44 | 9 | | 45 | 5 | | 46 | 4 | | 47 | 10 | | 48 | 10 | | 49 | 2 |
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| 45.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.34210526315789475 | | totalSentences | 152 | | uniqueOpeners | 52 | |
| 67.34% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 99 | | matches | | 0 | "Instead, she reached into her" | | 1 | "Only two deep, hollow sockets" |
| | ratio | 0.02 | |
| 34.14% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 46 | | totalSentences | 99 | | matches | | 0 | "He looked pale under the" | | 1 | "He gestured vaguely at the" | | 2 | "She adjusted the worn leather" | | 3 | "He pointed a gloved finger" | | 4 | "His eyes were wide, fixed" | | 5 | "She didn't touch, but she" | | 6 | "She clicked it on, the" | | 7 | "She shifted the light to" | | 8 | "They were clean." | | 9 | "She began to pace the" | | 10 | "She didn't look at the" | | 11 | "She looked at the environment." | | 12 | "She stopped near a rusted" | | 13 | "She knelt, the fabric of" | | 14 | "She pulled her light close" | | 15 | "They were narrow, rhythmic indentations," | | 16 | "They led toward the dark" | | 17 | "She felt a familiar, cold" | | 18 | "It was the same sensation" | | 19 | "It wasn't fear." |
| | ratio | 0.465 | |
| 10.51% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 89 | | totalSentences | 99 | | matches | | 0 | "Harlow Quinn stepped over a" | | 1 | "The air tasted of copper" | | 2 | "A single, flickering halogen work" | | 3 | "DS Miller stood hunched over" | | 4 | "He looked pale under the" | | 5 | "He gestured vaguely at the" | | 6 | "Harlow tightened her grip on" | | 7 | "She adjusted the worn leather" | | 8 | "The silence of the station" | | 9 | "He pointed a gloved finger" | | 10 | "Harlow knelt, keeping a respectful" | | 11 | "The victim was a young" | | 12 | "His eyes were wide, fixed" | | 13 | "Harlow leaned closer." | | 14 | "She didn't touch, but she" | | 15 | "Harlow pulled a small penlight" | | 16 | "She clicked it on, the" | | 17 | "Miller leaned in, squinting." | | 18 | "She shifted the light to" | | 19 | "They were clean." |
| | ratio | 0.899 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 99 | | matches | (empty) | | ratio | 0 | |
| 45.45% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 6 | | matches | | 0 | "She adjusted the worn leather watch on her left wrist, a rhythmic habit that helped her anchor herself to the physical world." | | 1 | "The victim was a young man, perhaps in his early twenties, dressed in expensive linen that looked absurdly out of place in this tomb of concrete and rust." | | 2 | "They were narrow, rhythmic indentations, as if someone had been dragging a heavy, thin rod through the dirt." | | 3 | "She looked at Miller, who was watching her with a mixture of annoyance and growing apprehension." | | 4 | "It was an unregistered item, something that didn't belong in a Metropolitan Police evidence locker." | | 5 | "It lunged from the wall with a speed that defied its size, the metallic rod clattering against the tracks like a rhythmic hammer." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 4 | | matches | | 0 | "Harlow stood, her eyes narrowing" | | 1 | "Miller whispered, his voice tight" | | 2 | "Miller's voice sounded, as if he were speaking from underwater" | | 3 | "Miller breathed, the flashlight trembling in his grip" |
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| 77.27% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 4 | | fancyTags | | 0 | "Miller suggested (suggest)" | | 1 | "Miller whispered (whisper)" | | 2 | "Miller breathed (breathe)" | | 3 | "Miller screamed (scream)" |
| | dialogueSentences | 55 | | tagDensity | 0.127 | | leniency | 0.255 | | rawRatio | 0.571 | | effectiveRatio | 0.145 | |