| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "She crouched again [again]" |
| | dialogueSentences | 35 | | tagDensity | 0.486 | | leniency | 0.971 | | rawRatio | 0.059 | | effectiveRatio | 0.057 | |
| 96.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1421 | | totalAiIsmAdverbs | 1 | | found | | 0 | | adverb | "deliberately" | | count | 1 |
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| | highlights | | |
| 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) | |
| 78.89% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1421 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "weight" | | 1 | "velvet" | | 2 | "unreadable" | | 3 | "perfect" | | 4 | "etched" |
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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 | 143 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 143 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 160 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1406 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 1196 | | uniqueNames | 7 | | maxNameDensity | 0.59 | | worstName | "Quinn" | | maxWindowNameDensity | 1 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 7 | | Tube | 1 | | Veil | 1 | | Market | 2 | | Reece | 6 | | Finnegan | 1 | | Morris | 2 |
| | persons | | 0 | "Quinn" | | 1 | "Market" | | 2 | "Reece" | | 3 | "Finnegan" | | 4 | "Morris" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1406 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 160 | | matches | | 0 | "realized, that the" | | 1 | "seen that walk" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 29.29 | | std | 23.03 | | cv | 0.786 | | sampleLengths | | 0 | 57 | | 1 | 86 | | 2 | 72 | | 3 | 44 | | 4 | 74 | | 5 | 37 | | 6 | 7 | | 7 | 7 | | 8 | 44 | | 9 | 62 | | 10 | 5 | | 11 | 9 | | 12 | 50 | | 13 | 6 | | 14 | 5 | | 15 | 57 | | 16 | 5 | | 17 | 4 | | 18 | 37 | | 19 | 14 | | 20 | 51 | | 21 | 12 | | 22 | 33 | | 23 | 46 | | 24 | 23 | | 25 | 14 | | 26 | 7 | | 27 | 11 | | 28 | 3 | | 29 | 52 | | 30 | 25 | | 31 | 45 | | 32 | 7 | | 33 | 22 | | 34 | 29 | | 35 | 14 | | 36 | 11 | | 37 | 48 | | 38 | 74 | | 39 | 14 | | 40 | 21 | | 41 | 1 | | 42 | 54 | | 43 | 50 | | 44 | 8 | | 45 | 17 | | 46 | 20 | | 47 | 12 |
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| 92.99% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 143 | | matches | | 0 | "were drawn" | | 1 | "was arranged" | | 2 | "was etched" | | 3 | "was oriented" | | 4 | "been robbed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 202 | | matches | | 0 | "was pointing" | | 1 | "was already walking" | | 2 | "was still standing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 15 | | semicolonCount | 0 | | flaggedSentences | 13 | | totalSentences | 160 | | ratio | 0.081 | | matches | | 0 | "Camden rumbled overhead—a Tube train, or maybe just the city shifting its weight." | | 1 | "The entry requirement was a bone token, according to one informant—a little carved thing you couldn't buy anywhere legal." | | 2 | "A man, maybe fifty, with a face like a closed door—weather-beaten, unreadable." | | 3 | "He looked up as she approached, and his mouth did the thing it always did—the slight downturn of a man who'd rather be anywhere else." | | 4 | "She touched the fabric—still damp—then pressed two fingers to the back of his hand." | | 5 | "Not the slack, half-open gaze of most homicide victims—closed, deliberately." | | 6 | "Small, brass, the casing webbed with green patina—the kind of corrosion that took decades, not years." | | 7 | "It spun—a quarter turn one way, a half turn back, jittering like a trapped insect." | | 8 | "Not cool—cold, the way a tombstone is cold." | | 9 | "\"Room temperature. But here—\" she pressed her palm back to the cold spot, \"—it's like a freezer.\"" | | 10 | "She'd seen that walk before—the shrug of a man who had a theory and didn't want it complicated." | | 11 | "No sign of anything, except that his face had been that same expression—eyes closed, arms at his sides, arranged." | | 12 | "And whatever he'd been guarding had come through the wall and killed him—or was still standing on the other side, waiting." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 931 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.031149301825993556 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0021482277121374865 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 160 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 160 | | mean | 8.79 | | std | 5.94 | | cv | 0.676 | | sampleLengths | | 0 | 16 | | 1 | 23 | | 2 | 13 | | 3 | 5 | | 4 | 3 | | 5 | 15 | | 6 | 21 | | 7 | 19 | | 8 | 4 | | 9 | 24 | | 10 | 13 | | 11 | 20 | | 12 | 8 | | 13 | 7 | | 14 | 13 | | 15 | 11 | | 16 | 15 | | 17 | 19 | | 18 | 10 | | 19 | 12 | | 20 | 4 | | 21 | 2 | | 22 | 1 | | 23 | 1 | | 24 | 12 | | 25 | 18 | | 26 | 9 | | 27 | 5 | | 28 | 7 | | 29 | 3 | | 30 | 12 | | 31 | 25 | | 32 | 3 | | 33 | 4 | | 34 | 3 | | 35 | 4 | | 36 | 14 | | 37 | 30 | | 38 | 2 | | 39 | 12 | | 40 | 9 | | 41 | 2 | | 42 | 2 | | 43 | 2 | | 44 | 14 | | 45 | 4 | | 46 | 15 | | 47 | 5 | | 48 | 9 | | 49 | 6 |
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| 59.79% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.41875 | | totalSentences | 160 | | uniqueOpeners | 67 | |
| 29.24% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 114 | | matches | | 0 | "Then at the cold tile," |
| | ratio | 0.009 | |
| 79.65% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 114 | | matches | | 0 | "They groaned under Quinn's boots," | | 1 | "She'd never had one." | | 2 | "She'd never needed one, until" | | 3 | "His stall was three paces" | | 4 | "He looked up as she" | | 5 | "He gestured with his chin" | | 6 | "He let the sentence trail," | | 7 | "She touched the fabric—still damp—then" | | 8 | "She looked at the wound" | | 9 | "It soaks the clothes, puddles" | | 10 | "She stood, turned a slow" | | 11 | "He'd died where he stood," | | 12 | "She nodded at the stall" | | 13 | "She crouched again, studying the" | | 14 | "His eyes were closed." | | 15 | "His hands lay at his" | | 16 | "He hadn't fought." | | 17 | "He was pointing at a" | | 18 | "She fished a glove from" | | 19 | "It spun—a quarter turn one" |
| | ratio | 0.351 | |
| 78.42% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 87 | | totalSentences | 114 | | matches | | 0 | "The escalators had been dead" | | 1 | "They groaned under Quinn's boots," | | 2 | "Camden rumbled overhead—a Tube train," | | 3 | "The Veil Market." | | 4 | "Quinn had a file on" | | 5 | "Reports surfaced every few months," | | 6 | "The entry requirement was a" | | 7 | "She'd never had one." | | 8 | "She'd never needed one, until" | | 9 | "The platform opened out before" | | 10 | "Stalls lined the curved walls," | | 11 | "Jars of things that caught" | | 12 | "A case of glass vials," | | 13 | "The air smelled of ozone," | | 14 | "Crime-scene tape stretched across the" | | 15 | "Quinn ducked under the tape" | | 16 | "The body lay on its" | | 17 | "Arms at its sides." | | 18 | "A man, maybe fifty, with" | | 19 | "His stall was three paces" |
| | ratio | 0.763 | |
| 43.86% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 114 | | matches | | 0 | "Now she looked again: the" |
| | ratio | 0.009 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 1 | | matches | | 0 | "Small, brass, the casing webbed with green patina—the kind of corrosion that took decades, not years." |
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| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 1 | | matches | | 0 | "He let, as if the market explained everything" |
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| 92.86% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 2 | | fancyTags | | 0 | "she repeated (repeat)" | | 1 | "she pressed (press)" |
| | dialogueSentences | 35 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0.2 | | effectiveRatio | 0.114 | |