| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.176 | | leniency | 0.353 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.26% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1177 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slowly" | | 1 | "very" | | 2 | "slightly" |
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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) | |
| 40.53% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1177 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "measured" | | 1 | "treacherous" | | 2 | "scanned" | | 3 | "weight" | | 4 | "rhythmic" | | 5 | "echoed" | | 6 | "velvet" | | 7 | "pulsed" | | 8 | "silk" | | 9 | "macabre" | | 10 | "silence" | | 11 | "lilt" |
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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 | 93 | | matches | (empty) | |
| 81.41% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 93 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 106 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1177 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1054 | | uniqueNames | 13 | | maxNameDensity | 1.42 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | Quinn | 1 | | London | 1 | | Veil | 1 | | Market | 1 | | Metropolitan | 1 | | Police | 1 | | Morris | 2 | | Harlow | 15 | | Saint | 1 | | Christopher | 1 | | Seville | 1 | | Tomás | 5 | | Herrera | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Police" | | 2 | "Morris" | | 3 | "Harlow" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Tomás" | | 7 | "Herrera" |
| | places | | | globalScore | 0.788 | | windowScore | 0.667 | |
| 80.56% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 2 | | matches | | 0 | "staircase that seemed to drop far deeper than any London utility vault should go" | | 1 | "felt like a heartbeat beneath the floor" |
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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 | 1177 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 106 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 26.16 | | std | 18.76 | | cv | 0.717 | | sampleLengths | | 0 | 2 | | 1 | 51 | | 2 | 55 | | 3 | 42 | | 4 | 3 | | 5 | 18 | | 6 | 48 | | 7 | 63 | | 8 | 42 | | 9 | 31 | | 10 | 10 | | 11 | 42 | | 12 | 63 | | 13 | 5 | | 14 | 46 | | 15 | 47 | | 16 | 22 | | 17 | 23 | | 18 | 49 | | 19 | 43 | | 20 | 3 | | 21 | 51 | | 22 | 3 | | 23 | 19 | | 24 | 49 | | 25 | 24 | | 26 | 18 | | 27 | 9 | | 28 | 34 | | 29 | 10 | | 30 | 9 | | 31 | 22 | | 32 | 4 | | 33 | 8 | | 34 | 33 | | 35 | 20 | | 36 | 4 | | 37 | 39 | | 38 | 6 | | 39 | 2 | | 40 | 47 | | 41 | 10 | | 42 | 21 | | 43 | 12 | | 44 | 15 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 93 | | matches | (empty) | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 166 | | matches | | 0 | "wasn't just running" | | 1 | "was descending" | | 2 | "was weaving" | | 3 | "was heading" | | 4 | "was wearing" | | 5 | "was coming" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 106 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 512 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 7 | | adverbRatio | 0.013671875 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.005859375 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 106 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 106 | | mean | 11.1 | | std | 6.27 | | cv | 0.565 | | sampleLengths | | 0 | 2 | | 1 | 11 | | 2 | 15 | | 3 | 25 | | 4 | 12 | | 5 | 4 | | 6 | 19 | | 7 | 20 | | 8 | 15 | | 9 | 16 | | 10 | 11 | | 11 | 3 | | 12 | 2 | | 13 | 16 | | 14 | 9 | | 15 | 12 | | 16 | 6 | | 17 | 8 | | 18 | 13 | | 19 | 2 | | 20 | 15 | | 21 | 13 | | 22 | 9 | | 23 | 5 | | 24 | 19 | | 25 | 3 | | 26 | 10 | | 27 | 14 | | 28 | 15 | | 29 | 3 | | 30 | 13 | | 31 | 15 | | 32 | 10 | | 33 | 14 | | 34 | 5 | | 35 | 23 | | 36 | 16 | | 37 | 13 | | 38 | 6 | | 39 | 16 | | 40 | 12 | | 41 | 5 | | 42 | 11 | | 43 | 23 | | 44 | 12 | | 45 | 21 | | 46 | 26 | | 47 | 9 | | 48 | 10 | | 49 | 3 |
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| 42.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.33962264150943394 | | totalSentences | 106 | | uniqueOpeners | 36 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 89 | | matches | (empty) | | ratio | 0 | |
| 58.20% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 89 | | matches | | 0 | "He vaulted over a low" | | 1 | "She didn't slow down." | | 2 | "Her military precision usually kept" | | 3 | "She vaulted the wall in" | | 4 | "He scrambled over a pile" | | 5 | "He hit a heavy iron" | | 6 | "She threw her shoulder against" | | 7 | "It was locked from the" | | 8 | "She scanned the alley, her" | | 9 | "He wasn't in a basement." | | 10 | "He was descending a spiral" | | 11 | "She found a ventilation shaft," | | 12 | "She slid inside, the smell" | | 13 | "She descended through the darkness," | | 14 | "It smelled of dried herbs," | | 15 | "She dropped the last few" | | 16 | "She stood up and stepped" | | 17 | "They didn't sell fruit or" | | 18 | "She had heard the whispers" | | 19 | "She had dismissed them as" |
| | ratio | 0.404 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 83 | | totalSentences | 89 | | matches | | 0 | "Harlow Quinn lunged forward, her" | | 1 | "The suspect, a wiry man" | | 2 | "He vaulted over a low" | | 3 | "Harlow's breath hitched in her" | | 4 | "She didn't slow down." | | 5 | "Her military precision usually kept" | | 6 | "She vaulted the wall in" | | 7 | "The man dove into a" | | 8 | "Water cascaded from rusted gutters," | | 9 | "He scrambled over a pile" | | 10 | "He hit a heavy iron" | | 11 | "Harlow reached the door just" | | 12 | "She threw her shoulder against" | | 13 | "It was locked from the" | | 14 | "She scanned the alley, her" | | 15 | "A fire escape clung to" | | 16 | "The metal groaned under her" | | 17 | "He wasn't in a basement." | | 18 | "He was descending a spiral" | | 19 | "Harlow didn't hesitate." |
| | ratio | 0.933 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 89 | | matches | (empty) | | ratio | 0 | |
| 92.73% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 4 | | matches | | 0 | "He was descending a spiral staircase that seemed to drop far deeper than any London utility vault should go." | | 1 | "She had heard the whispers in the precinct, the fringe reports of an underground trade that defied every law of physics and forensics." | | 2 | "He was heading toward a vendor who looked less like a man and more like a collection of sharp angles draped in a heavy wool cloak." | | 3 | "It was a sound, a rhythmic thrumming that felt like a heartbeat beneath the floor." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "the man said, his voice carrying a soft, melodic lilt from Seville" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.059 | | leniency | 0.118 | | rawRatio | 0 | | effectiveRatio | 0 | |