| 18.18% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 3 | | adverbTags | | 0 | "Quinn said finally [finally]" | | 1 | "She crouched again [again]" | | 2 | "she said quietly [quietly]" |
| | dialogueSentences | 33 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0.25 | | effectiveRatio | 0.182 | |
| 83.73% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 922 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "sharply" | | 1 | "slightly" | | 2 | "gently" |
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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) | |
| 34.92% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 922 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "flicker" | | 1 | "wavering" | | 2 | "footsteps" | | 3 | "silence" | | 4 | "weight" | | 5 | "tracing" | | 6 | "pristine" | | 7 | "etched" | | 8 | "trembled" | | 9 | "furrowing" | | 10 | "pulse" | | 11 | "shimmered" |
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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 | 83 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 83 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 103 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 918 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 44.32% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 757 | | uniqueNames | 9 | | maxNameDensity | 2.11 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 16 | | Tube | 1 | | Davies | 9 | | Veil | 2 | | Market | 1 | | Camden | 1 | | Morris | 2 | | Compass | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Davies" | | 3 | "Camden" | | 4 | "Morris" |
| | places | (empty) | | globalScore | 0.443 | | windowScore | 0.5 | |
| 97.92% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like dried blood" |
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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 | 918 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 103 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 24.81 | | std | 24.56 | | cv | 0.99 | | sampleLengths | | 0 | 73 | | 1 | 10 | | 2 | 38 | | 3 | 36 | | 4 | 59 | | 5 | 9 | | 6 | 59 | | 7 | 4 | | 8 | 66 | | 9 | 7 | | 10 | 6 | | 11 | 51 | | 12 | 16 | | 13 | 10 | | 14 | 1 | | 15 | 24 | | 16 | 9 | | 17 | 53 | | 18 | 10 | | 19 | 9 | | 20 | 12 | | 21 | 95 | | 22 | 6 | | 23 | 67 | | 24 | 3 | | 25 | 3 | | 26 | 29 | | 27 | 2 | | 28 | 11 | | 29 | 38 | | 30 | 3 | | 31 | 17 | | 32 | 6 | | 33 | 21 | | 34 | 6 | | 35 | 43 | | 36 | 6 |
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| 75.67% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 83 | | matches | | 0 | "was crouched" | | 1 | "being dragged" | | 2 | "been wiped" | | 3 | "been left" | | 4 | "been closed" | | 5 | "was curled" | | 6 | "were fixed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 128 | | matches | (empty) | |
| 31.90% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 103 | | ratio | 0.039 | | matches | | 0 | "The symbols were jagged, uneven, as if whoever had written them had been in a hurry—or lacked the skill." | | 1 | "Nothing to suggest a struggle—or even a body being dragged." | | 2 | "The Veil Market—a hidden black market beneath Camden, selling everything from enchanted trinkets to banned alchemical substances." | | 3 | "The needle trembled, then swung wildly before settling on a direction that made no sense—pointing deeper into the tunnel, toward a wall of solid brick." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 761 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.03416557161629435 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.010512483574244415 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 103 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 103 | | mean | 8.91 | | std | 6.68 | | cv | 0.75 | | sampleLengths | | 0 | 20 | | 1 | 15 | | 2 | 21 | | 3 | 17 | | 4 | 5 | | 5 | 5 | | 6 | 6 | | 7 | 16 | | 8 | 16 | | 9 | 20 | | 10 | 9 | | 11 | 3 | | 12 | 4 | | 13 | 14 | | 14 | 19 | | 15 | 11 | | 16 | 15 | | 17 | 3 | | 18 | 6 | | 19 | 11 | | 20 | 19 | | 21 | 16 | | 22 | 3 | | 23 | 2 | | 24 | 1 | | 25 | 1 | | 26 | 6 | | 27 | 4 | | 28 | 3 | | 29 | 13 | | 30 | 10 | | 31 | 6 | | 32 | 3 | | 33 | 5 | | 34 | 26 | | 35 | 7 | | 36 | 2 | | 37 | 4 | | 38 | 13 | | 39 | 3 | | 40 | 3 | | 41 | 10 | | 42 | 20 | | 43 | 2 | | 44 | 3 | | 45 | 5 | | 46 | 2 | | 47 | 6 | | 48 | 6 | | 49 | 4 |
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| 63.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.39805825242718446 | | totalSentences | 103 | | uniqueOpeners | 41 | |
| 93.90% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 71 | | matches | | 0 | "Instead, she walked a slow" | | 1 | "Just a single, small detail" |
| | ratio | 0.028 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 71 | | matches | | 0 | "he said, straightening" | | 1 | "She adjusted the worn leather" | | 2 | "He glanced up as she" | | 3 | "she corrected, tracing a finger" | | 4 | "Her hands were pristine, nails" | | 5 | "She pointed to the packed" | | 6 | "She crouched again, this time" | | 7 | "She’d heard whispers of it" | | 8 | "She’d seen this before." | | 9 | "She’d seen the way Morris" | | 10 | "She turned back to the" | | 11 | "She’d heard of them, of" | | 12 | "She was too busy staring" | | 13 | "She stood abruptly, the compass" | | 14 | "She didn’t look at him." | | 15 | "Her eyes were fixed on" | | 16 | "she said quietly" |
| | ratio | 0.239 | |
| 65.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 71 | | matches | | 0 | "The air smelled of damp" | | 1 | "Detective Harlow Quinn stepped over" | | 2 | "The abandoned Tube tunnel stretched" | | 3 | "A uniformed officer stood near" | | 4 | "he said, straightening" | | 5 | "Quinn nodded, her sharp jaw" | | 6 | "She adjusted the worn leather" | | 7 | "The tunnel swallowed the sound" | | 8 | "Davies was crouched near the" | | 9 | "He glanced up as she" | | 10 | "Quinn knelt beside him, her" | | 11 | "The symbols were jagged, uneven," | | 12 | "she corrected, tracing a finger" | | 13 | "Davies exhaled sharply." | | 14 | "Quinn stood, her gaze sweeping" | | 15 | "The body lay near the" | | 16 | "A young woman, early twenties," | | 17 | "Quinn didn’t answer." | | 18 | "The victim’s clothes were clean," | | 19 | "Her hands were pristine, nails" |
| | ratio | 0.789 | |
| 70.42% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 71 | | matches | | 0 | "As if they’d been wiped" |
| | ratio | 0.014 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 6 | | matches | | 0 | "The air smelled of damp stone and something older, something that clung to the back of the throat like copper." | | 1 | "Just a single, small detail that didn’t fit: a thin line of dirt along the hem of her jeans, as if she’d knelt in something damp." | | 2 | "Three years ago, when her partner, DS Morris, had vanished during a case that had reeked of the supernatural." | | 3 | "The way the air had smelled of ozone and something darker, something that had no place in the world she knew." | | 4 | "The needle trembled, then swung wildly before settling on a direction that made no sense—pointing deeper into the tunnel, toward a wall of solid brick." | | 5 | "Her eyes were fixed on the compass, on the way the needle had begun to spin again, faster this time, as if caught in an invisible current." |
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| 83.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn stood, her gaze sweeping over the scene" |
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| 89.39% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 2 | | fancyTags | | 0 | "he muttered (mutter)" | | 1 | "she corrected (correct)" |
| | dialogueSentences | 33 | | tagDensity | 0.212 | | leniency | 0.424 | | rawRatio | 0.286 | | effectiveRatio | 0.121 | |