| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.414 | | leniency | 0.828 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 80.43% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1533 | | totalAiIsmAdverbs | 6 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | adverb | "barely above a whisper" | | count | 1 |
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| | highlights | | 0 | "completely" | | 1 | "very" | | 2 | "lazily" | | 3 | "carefully" | | 4 | "quickly" | | 5 | "barely above a whisper" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 64.12% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1533 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "footsteps" | | 1 | "silence" | | 2 | "perfect" | | 3 | "chaotic" | | 4 | "flickered" | | 5 | "etched" | | 6 | "pulse" | | 7 | "flicker" | | 8 | "whisper" |
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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) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 93 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 61 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1529 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1167 | | uniqueNames | 17 | | maxNameDensity | 1.29 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 15 | | Tube | 1 | | Camden | 1 | | Blitz | 1 | | Veil | 2 | | Market | 1 | | London | 1 | | Patel | 9 | | Tragic | 1 | | Straightforward | 1 | | Morris | 1 | | Ashworth | 3 | | Compass | 1 | | British | 1 | | Museum | 1 | | Kowalski | 1 | | Eva | 6 |
| | persons | | 0 | "Quinn" | | 1 | "Camden" | | 2 | "Market" | | 3 | "Patel" | | 4 | "Morris" | | 5 | "Ashworth" | | 6 | "Kowalski" | | 7 | "Eva" |
| | places | | 0 | "London" | | 1 | "Straightforward" | | 2 | "Compass" | | 3 | "British" |
| | globalScore | 0.857 | | windowScore | 0.667 | |
| 39.71% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 3 | | matches | | 0 | "tel continued, apparently taking her silence" | | 1 | "looked like he'd seen something eating th" | | 2 | "It was as if he had simply appeared in that spot and died" |
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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 | 1529 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 110 | | matches | | 0 | "learned that habit" | | 1 | "pointed that direction" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 39.21 | | std | 30.89 | | cv | 0.788 | | sampleLengths | | 0 | 88 | | 1 | 102 | | 2 | 28 | | 3 | 8 | | 4 | 83 | | 5 | 9 | | 6 | 39 | | 7 | 91 | | 8 | 77 | | 9 | 53 | | 10 | 45 | | 11 | 49 | | 12 | 71 | | 13 | 11 | | 14 | 40 | | 15 | 29 | | 16 | 51 | | 17 | 6 | | 18 | 13 | | 19 | 66 | | 20 | 93 | | 21 | 16 | | 22 | 60 | | 23 | 67 | | 24 | 21 | | 25 | 3 | | 26 | 24 | | 27 | 5 | | 28 | 26 | | 29 | 33 | | 30 | 7 | | 31 | 24 | | 32 | 2 | | 33 | 6 | | 34 | 105 | | 35 | 14 | | 36 | 7 | | 37 | 35 | | 38 | 22 |
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| 90.17% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 93 | | matches | | 0 | "was undisturbed" | | 1 | "was etched" | | 2 | "was supposed" | | 3 | "was locked" |
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| 61.83% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 193 | | matches | | 0 | "was waiting" | | 1 | "wasn't pointing" | | 2 | "was pointing" | | 3 | "were shaking" |
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| 90.91% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 110 | | ratio | 0.018 | | matches | | 0 | "His clothes were expensive—tailored wool coat, leather shoes that had probably cost more than Patel's monthly rent—and conspicuously clean for a man lying in decades of accumulated grime." | | 1 | "Outside that circle, there were the expected footprints—market-goers, probably from before the relocation, their tracks overlapping and chaotic." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1176 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.030612244897959183 | | lyAdverbCount | 18 | | lyAdverbRatio | 0.015306122448979591 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 13.9 | | std | 11.52 | | cv | 0.829 | | sampleLengths | | 0 | 14 | | 1 | 34 | | 2 | 2 | | 3 | 38 | | 4 | 14 | | 5 | 8 | | 6 | 21 | | 7 | 10 | | 8 | 17 | | 9 | 16 | | 10 | 16 | | 11 | 11 | | 12 | 17 | | 13 | 8 | | 14 | 7 | | 15 | 23 | | 16 | 25 | | 17 | 28 | | 18 | 5 | | 19 | 4 | | 20 | 9 | | 21 | 30 | | 22 | 11 | | 23 | 5 | | 24 | 20 | | 25 | 8 | | 26 | 4 | | 27 | 13 | | 28 | 4 | | 29 | 2 | | 30 | 1 | | 31 | 23 | | 32 | 16 | | 33 | 3 | | 34 | 8 | | 35 | 50 | | 36 | 24 | | 37 | 4 | | 38 | 7 | | 39 | 7 | | 40 | 4 | | 41 | 7 | | 42 | 45 | | 43 | 12 | | 44 | 7 | | 45 | 7 | | 46 | 23 | | 47 | 19 | | 48 | 18 | | 49 | 5 |
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| 79.09% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4909090909090909 | | totalSentences | 110 | | uniqueOpeners | 54 | |
| 80.32% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 83 | | matches | | 0 | "Sometimes junior detectives talked themselves" | | 1 | "Then a small nod." |
| | ratio | 0.024 | |
| 80.24% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 83 | | matches | | 0 | "She'd counted them on the" | | 1 | "It moved every full moon," | | 2 | "He stood when he heard" | | 3 | "He lay on his back" | | 4 | "His clothes were expensive—tailored wool" | | 5 | "It wasn't a question." | | 6 | "She'd learned that habit early." | | 7 | "You stayed clean at a" | | 8 | "She leaned close and studied" | | 9 | "She let him." | | 10 | "He said it with the" | | 11 | "She shifted her attention from" | | 12 | "He'd looked at the man" | | 13 | "It was as if he" | | 14 | "She kept her voice level" | | 15 | "He blinked and crouched beside" | | 16 | "She let a beat pass" | | 17 | "She stood and swept her" | | 18 | "Its casing had a patina" | | 19 | "It wasn't pointing north." |
| | ratio | 0.349 | |
| 68.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 83 | | matches | | 0 | "The stairs down from the" | | 1 | "Harlow Quinn clicked her torch" | | 2 | "She'd counted them on the" | | 3 | "The abandoned Tube station beneath" | | 4 | "Emergency lights strung along the" | | 5 | "It moved every full moon," | | 6 | "Someone had either gotten the" | | 7 | "DC Patel was waiting on" | | 8 | "He stood when he heard" | | 9 | "Quinn studied the scene without" | | 10 | "The body was male, mid-fifties" | | 11 | "He lay on his back" | | 12 | "His clothes were expensive—tailored wool" | | 13 | "It wasn't a question." | | 14 | "Patel gestured at the body" | | 15 | "Quinn crouched beside the body," | | 16 | "She'd learned that habit early." | | 17 | "You stayed clean at a" | | 18 | "She leaned close and studied" | | 19 | "The expression was wrong." |
| | ratio | 0.783 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 83 | | matches | | 0 | "While Patel moved down the" | | 1 | "If it was locked on" | | 2 | "Either the man had come" |
| | ratio | 0.036 | |
| 26.58% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 7 | | matches | | 0 | "Emergency lights strung along the platform cast everything in a sickly amber glow that made the shadows pool like spilled oil." | | 1 | "His clothes were expensive—tailored wool coat, leather shoes that had probably cost more than Patel's monthly rent—and conspicuously clean for a man lying in de…" | | 2 | "The kind of peaceful that required muscles to relax in a specific sequence that had nothing to do with the heart giving out." | | 3 | "He said it with the easy confidence of a man who had already filed this case in his mental cabinet under Tragic But Straightforward." | | 4 | "But Quinn had stopped believing in straightforward three years ago, when DS Morris had died in a room that was locked from the inside with no visible cause of d…" | | 5 | "Not a scuff from the rough platform edge, not a grain of the black sediment that had accumulated on the tracks over seventy years of abandonment." | | 6 | "Its casing had a patina of verdigris that her thumb knew by heart now, and the face was etched with protective sigils she'd photographed and sent to a contact a…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | 0 | "Patel continued (continue)" |
| | dialogueSentences | 29 | | tagDensity | 0.172 | | leniency | 0.345 | | rawRatio | 0.2 | | effectiveRatio | 0.069 | |