| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 38 | | tagDensity | 0.184 | | leniency | 0.368 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.76% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1908 | | totalAiIsmAdverbs | 2 | | found | | | 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) | |
| 86.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1908 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "pulsed" | | 1 | "scanned" | | 2 | "measured" | | 3 | "pulse" | | 4 | "quickened" |
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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 | 1 | | narrationSentences | 194 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 194 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 225 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1906 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 62.08% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 52 | | wordCount | 1706 | | uniqueNames | 14 | | maxNameDensity | 1.76 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | High | 1 | | Street | 1 | | Quinn | 30 | | Tube | 1 | | Morris | 2 | | Saint | 1 | | Christopher | 1 | | London | 2 | | Tomás | 1 | | Herrera | 5 | | Don | 1 | | Harlow | 1 | | People | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Tomás" | | 5 | "Herrera" | | 6 | "People" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "London" |
| | globalScore | 0.621 | | windowScore | 0.667 | |
| 91.41% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 128 | | glossingSentenceCount | 3 | | matches | | 0 | "seemed suddenly loud in her hand" | | 1 | "something like a human hand rested in a nest" | | 2 | "looked like he might be watching her, but" |
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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 | 1906 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 225 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 95 | | mean | 20.06 | | std | 17.59 | | cv | 0.877 | | sampleLengths | | 0 | 34 | | 1 | 3 | | 2 | 28 | | 3 | 39 | | 4 | 38 | | 5 | 2 | | 6 | 14 | | 7 | 37 | | 8 | 6 | | 9 | 5 | | 10 | 18 | | 11 | 38 | | 12 | 28 | | 13 | 4 | | 14 | 26 | | 15 | 2 | | 16 | 30 | | 17 | 26 | | 18 | 3 | | 19 | 81 | | 20 | 7 | | 21 | 1 | | 22 | 3 | | 23 | 55 | | 24 | 45 | | 25 | 27 | | 26 | 19 | | 27 | 18 | | 28 | 54 | | 29 | 5 | | 30 | 28 | | 31 | 18 | | 32 | 53 | | 33 | 19 | | 34 | 33 | | 35 | 28 | | 36 | 75 | | 37 | 9 | | 38 | 41 | | 39 | 48 | | 40 | 11 | | 41 | 17 | | 42 | 4 | | 43 | 3 | | 44 | 11 | | 45 | 4 | | 46 | 42 | | 47 | 14 | | 48 | 2 | | 49 | 26 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 194 | | matches | | 0 | "was framed" | | 1 | "was hidden" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 302 | | matches | | 0 | "were speaking" | | 1 | "was already crossing" | | 2 | "was choosing" |
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| 79.37% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 3 | | flaggedSentences | 5 | | totalSentences | 225 | | ratio | 0.022 | | matches | | 0 | "Her breath came even; her legs knew this work." | | 1 | "Rusted rails disappeared into a tunnel at one end; at the other, a row of old station lamps burned with a faint blue glow." | | 2 | "The air changed at once—warmer, thick with incense, damp wool, and something sharp and chemical that stung the back of her throat." | | 3 | "At another stall, a woman sold tiny brass cages; something inside one scratched at the metal." | | 4 | "The market noise faded behind her, replaced by a low, steady thudding that might have been a train moving through the earth—or a heartbeat." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1712 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 46 | | adverbRatio | 0.026869158878504672 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.004672897196261682 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 225 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 225 | | mean | 8.47 | | std | 5.63 | | cv | 0.664 | | sampleLengths | | 0 | 11 | | 1 | 23 | | 2 | 3 | | 3 | 4 | | 4 | 8 | | 5 | 12 | | 6 | 4 | | 7 | 4 | | 8 | 9 | | 9 | 14 | | 10 | 12 | | 11 | 6 | | 12 | 13 | | 13 | 6 | | 14 | 7 | | 15 | 6 | | 16 | 2 | | 17 | 14 | | 18 | 9 | | 19 | 9 | | 20 | 19 | | 21 | 6 | | 22 | 5 | | 23 | 4 | | 24 | 1 | | 25 | 10 | | 26 | 3 | | 27 | 9 | | 28 | 18 | | 29 | 11 | | 30 | 6 | | 31 | 2 | | 32 | 12 | | 33 | 8 | | 34 | 4 | | 35 | 7 | | 36 | 12 | | 37 | 7 | | 38 | 2 | | 39 | 6 | | 40 | 14 | | 41 | 10 | | 42 | 1 | | 43 | 3 | | 44 | 22 | | 45 | 3 | | 46 | 10 | | 47 | 9 | | 48 | 24 | | 49 | 24 |
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| 43.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.28444444444444444 | | totalSentences | 225 | | uniqueOpeners | 64 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 176 | | matches | | 0 | "Then he ran faster." | | 1 | "Somewhere a car alarm wailed," | | 2 | "Then a metallic clatter came" | | 3 | "Too many strangers." | | 4 | "Too few clear angles." | | 5 | "Only the blue light, dimming" |
| | ratio | 0.034 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 52 | | totalSentences | 176 | | matches | | 0 | "He looked back once." | | 1 | "Her breath came even; her" | | 2 | "He darted down a side" | | 3 | "Her radio crackled at her" | | 4 | "They burst across the pavement," | | 5 | "She hurdled the last one" | | 6 | "Her transmission dissolved into static." | | 7 | "She tapped the radio." | | 8 | "She kept moving." | | 9 | "She drew her pistol." | | 10 | "Her left hand brushed the" | | 11 | "She pushed through." | | 12 | "He did not." | | 13 | "Her pistol seemed suddenly loud" | | 14 | "She had a row of" | | 15 | "She had seen too much" | | 16 | "He turned through it and" | | 17 | "She could wait." | | 18 | "She could secure the entrance," | | 19 | "She could also lose him." |
| | ratio | 0.295 | |
| 62.27% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 140 | | totalSentences | 176 | | matches | | 0 | "Quinn’s boots struck it hard," | | 1 | "He looked back once." | | 2 | "A pale line showed at" | | 3 | "Quinn lengthened her stride." | | 4 | "Her breath came even; her" | | 5 | "The city narrowed to the" | | 6 | "He darted down a side" | | 7 | "Quinn followed, one hand skimming" | | 8 | "A shutter banged in the" | | 9 | "Her radio crackled at her" | | 10 | "The man knocked over a" | | 11 | "They burst across the pavement," | | 12 | "She hurdled the last one" | | 13 | "Her transmission dissolved into static." | | 14 | "She tapped the radio." | | 15 | "The signal was bad here," | | 16 | "She kept moving." | | 17 | "The passage smelled of wet" | | 18 | "Quinn reached the gate, found" | | 19 | "A brick stairwell plunged into" |
| | ratio | 0.795 | |
| 28.41% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 176 | | matches | | 0 | "Now the door was choosing" |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 68 | | technicalSentenceCount | 2 | | matches | | 0 | "Muffled, close, with a strange layered quality, as if they were speaking through the walls and from somewhere farther away at once." | | 1 | "The market noise faded behind her, replaced by a low, steady thudding that might have been a train moving through the earth—or a heartbeat." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 38 | | tagDensity | 0.158 | | leniency | 0.316 | | rawRatio | 0.167 | | effectiveRatio | 0.053 | |