| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 2 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1026 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 17.15% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1026 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "chilling" | | 1 | "weight" | | 2 | "navigating" | | 3 | "maw" | | 4 | "vibrated" | | 5 | "pulse" | | 6 | "rhythmic" | | 7 | "footsteps" | | 8 | "silence" | | 9 | "flicker" | | 10 | "pulsed" | | 11 | "shattered" | | 12 | "sentinel" | | 13 | "glinting" |
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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 | 104 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 104 | | filterMatches | | | hedgeMatches | (empty) | |
| 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 | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1019 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 982 | | uniqueNames | 14 | | maxNameDensity | 0.71 | | worstName | "Herrera" | | maxWindowNameDensity | 2 | | worstWindowName | "Herrera" | | discoveredNames | | Soho | 1 | | Quinn | 1 | | Herrera | 7 | | Morris | 3 | | Saint | 1 | | Christopher | 1 | | Victorian | 1 | | Tube | 1 | | Veil | 2 | | Market | 2 | | Tomás | 2 | | Metropolitan | 1 | | Police | 1 | | Harlow | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Herrera" | | 2 | "Morris" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Tomás" | | 6 | "Harlow" |
| | places | | 0 | "Soho" | | 1 | "Veil" | | 2 | "Metropolitan" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | 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 | 1019 | | 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 | 22 | | mean | 46.32 | | std | 34.95 | | cv | 0.755 | | sampleLengths | | 0 | 56 | | 1 | 58 | | 2 | 33 | | 3 | 54 | | 4 | 3 | | 5 | 63 | | 6 | 25 | | 7 | 22 | | 8 | 7 | | 9 | 20 | | 10 | 13 | | 11 | 14 | | 12 | 68 | | 13 | 27 | | 14 | 44 | | 15 | 17 | | 16 | 159 | | 17 | 63 | | 18 | 73 | | 19 | 34 | | 20 | 66 | | 21 | 100 |
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| 91.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 104 | | matches | | 0 | "been gone" | | 1 | "was swept" | | 2 | "were clustered" | | 3 | "was gone" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 156 | | matches | | 0 | "was navigating" | | 1 | "wasn’t just running" | | 2 | "wasn’t running" | | 3 | "was talking" | | 4 | "was buying" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 2 | | flaggedSentences | 9 | | totalSentences | 106 | | ratio | 0.085 | | matches | | 0 | "Her breath came in controlled, even bursts—years of discipline keeping panic at bay." | | 1 | "Eighteen years on the force didn’t build speed; it built stubbornness." | | 2 | "Her watch caught the light—the worn leather strap, the plain face." | | 3 | "He wasn’t just running; he was navigating." | | 4 | "The metal edges were wet, not with rain—with the grease from a recent, hasty grip." | | 5 | "The walls, covered in a century of grime, bore faint scuff marks—furniture moved, maybe." | | 6 | "It was a concourse—a dead, abandoned Tube station, tiled in that iconic, grimy white brickwork." | | 7 | "People moved among the stalls—a strange, quiet crowd in hooded coats, haggling in low murmurs." | | 8 | "Herrera handed something over—a small, glinting object." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 794 | | adjectiveStacks | 1 | | stackExamples | | 0 | "iconic, grimy white brickwork." |
| | adverbCount | 21 | | adverbRatio | 0.02644836272040302 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003778337531486146 | |
| 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 | 9.61 | | std | 6.34 | | cv | 0.66 | | sampleLengths | | 0 | 19 | | 1 | 15 | | 2 | 9 | | 3 | 13 | | 4 | 19 | | 5 | 2 | | 6 | 18 | | 7 | 8 | | 8 | 11 | | 9 | 15 | | 10 | 11 | | 11 | 4 | | 12 | 3 | | 13 | 9 | | 14 | 5 | | 15 | 21 | | 16 | 9 | | 17 | 3 | | 18 | 7 | | 19 | 3 | | 20 | 3 | | 21 | 17 | | 22 | 10 | | 23 | 18 | | 24 | 15 | | 25 | 2 | | 26 | 17 | | 27 | 3 | | 28 | 3 | | 29 | 2 | | 30 | 7 | | 31 | 4 | | 32 | 1 | | 33 | 4 | | 34 | 2 | | 35 | 1 | | 36 | 1 | | 37 | 3 | | 38 | 4 | | 39 | 20 | | 40 | 4 | | 41 | 9 | | 42 | 5 | | 43 | 1 | | 44 | 4 | | 45 | 4 | | 46 | 14 | | 47 | 15 | | 48 | 14 | | 49 | 20 |
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| 43.40% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.33962264150943394 | | totalSentences | 106 | | uniqueOpeners | 36 | |
| 70.92% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 94 | | matches | | 0 | "Then he vanished." | | 1 | "Then he’d been gone." |
| | ratio | 0.021 | |
| 62.55% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 94 | | matches | | 0 | "Her coat was a dead" | | 1 | "Her breath came in controlled," | | 2 | "She’d had him dead to" | | 3 | "He was fast, younger, but" | | 4 | "She skidded around the corner," | | 5 | "Her watch caught the light—the" | | 6 | "She pushed harder." | | 7 | "Her feet splashed through debris." | | 8 | "Her quarry vaulted a stack" | | 9 | "He moved like a man" | | 10 | "She noted that." | | 11 | "He wasn’t just running; he" | | 12 | "She pulled her torch, the" | | 13 | "Her radio crackled." | | 14 | "She thumbed the switch." | | 15 | "She clipped the radio back." | | 16 | "She swung her legs into" | | 17 | "Her torch beam found brickwork," | | 18 | "Her feet hit solid ground." | | 19 | "She killed the torch, letting" |
| | ratio | 0.394 | |
| 45.11% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 94 | | matches | | 0 | "The rain hit the pavement" | | 1 | "Harlow Quinn’s shoes slapped through" | | 2 | "Her coat was a dead" | | 3 | "Her breath came in controlled," | | 4 | "She’d had him dead to" | | 5 | "He was fast, younger, but" | | 6 | "She skidded around the corner," | | 7 | "Her watch caught the light—the" | | 8 | "A gift from Morris." | | 9 | "She pushed harder." | | 10 | "The alley stank of rotting" | | 11 | "Her feet splashed through debris." | | 12 | "Her quarry vaulted a stack" | | 13 | "He moved like a man" | | 14 | "She noted that." | | 15 | "He wasn’t just running; he" | | 16 | "Harlow stopped dead." | | 17 | "The alley ended in a" | | 18 | "She pulled her torch, the" | | 19 | "A grate, set into the" |
| | ratio | 0.83 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 94 | | matches | | 0 | "Before Herrera slipped away into" | | 1 | "Now she would see what" |
| | ratio | 0.021 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 3 | | matches | | 0 | "She’d had him dead to rights outside the club, a twenty-minute tail that ended with him spotting her." | | 1 | "An old ticket booth, its glass shattered, stood sentinel at the entrance to a platform that had long since seen its last train." | | 2 | "She looked at the stall selling things that pulsed with their own light, things in jars that shouldn’t be alive." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 2 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |