| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 9 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1209 | | 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) | |
| 62.78% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1209 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "racing" | | 1 | "traced" | | 2 | "weight" | | 3 | "pulsed" | | 4 | "gloom" | | 5 | "velvet" | | 6 | "grave" | | 7 | "silence" |
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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 | 89 | | matches | (empty) | |
| 94.70% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 89 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1206 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.16% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1122 | | uniqueNames | 13 | | maxNameDensity | 1.34 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | High | 1 | | Street | 1 | | Quinn | 15 | | Herrera | 9 | | Saint | 1 | | Christopher | 1 | | Victorian | 2 | | Tube | 2 | | Veil | 1 | | Market | 1 | | Morris | 2 | | Deptford | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Herrera" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Market" | | 5 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Deptford" |
| | globalScore | 0.832 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | 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 | 1206 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 35.47 | | std | 37.5 | | cv | 1.057 | | sampleLengths | | 0 | 107 | | 1 | 9 | | 2 | 84 | | 3 | 33 | | 4 | 30 | | 5 | 2 | | 6 | 69 | | 7 | 1 | | 8 | 67 | | 9 | 9 | | 10 | 54 | | 11 | 10 | | 12 | 100 | | 13 | 18 | | 14 | 3 | | 15 | 46 | | 16 | 2 | | 17 | 168 | | 18 | 18 | | 19 | 7 | | 20 | 9 | | 21 | 53 | | 22 | 2 | | 23 | 14 | | 24 | 6 | | 25 | 14 | | 26 | 29 | | 27 | 5 | | 28 | 39 | | 29 | 50 | | 30 | 63 | | 31 | 64 | | 32 | 18 | | 33 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 89 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 192 | | matches | (empty) | |
| 53.57% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 96 | | ratio | 0.031 | | matches | | 0 | "A chalk mark on the nearest pillar tracked the lunar cycle—three days until the full moon, when the market would uproot and reappear somewhere else beneath the city's skin." | | 1 | "A vendor by the entrance waved a tray of tarnished silver; the liquid inside the vials crawled against the glass like tadpoles in a murky tank." | | 2 | "Quinn watched Herrera hand over his sliver—too regular for ivory, carved with symbols that ached the eye—and pass through." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1129 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.01948627103631532 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.002657218777679362 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 12.56 | | std | 9.48 | | cv | 0.754 | | sampleLengths | | 0 | 26 | | 1 | 31 | | 2 | 20 | | 3 | 4 | | 4 | 26 | | 5 | 9 | | 6 | 40 | | 7 | 6 | | 8 | 5 | | 9 | 4 | | 10 | 29 | | 11 | 16 | | 12 | 17 | | 13 | 5 | | 14 | 2 | | 15 | 5 | | 16 | 18 | | 17 | 2 | | 18 | 14 | | 19 | 16 | | 20 | 11 | | 21 | 28 | | 22 | 1 | | 23 | 6 | | 24 | 3 | | 25 | 22 | | 26 | 17 | | 27 | 12 | | 28 | 4 | | 29 | 3 | | 30 | 9 | | 31 | 18 | | 32 | 19 | | 33 | 8 | | 34 | 6 | | 35 | 3 | | 36 | 7 | | 37 | 3 | | 38 | 28 | | 39 | 5 | | 40 | 32 | | 41 | 5 | | 42 | 11 | | 43 | 5 | | 44 | 14 | | 45 | 18 | | 46 | 3 | | 47 | 28 | | 48 | 18 | | 49 | 2 |
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| 47.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.34375 | | totalSentences | 96 | | uniqueOpeners | 33 | |
| 79.37% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 84 | | matches | | 0 | "Just a flare of acknowledgment," | | 1 | "Somewhere in that labyrinth, the" |
| | ratio | 0.024 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 84 | | matches | | 0 | "Her left hand traced circles" | | 1 | "He moved like a man" | | 2 | "She didn't call out." | | 3 | "She'd stopped calling out three" | | 4 | "Her boots found the pavement" | | 5 | "Her voice cracked through the" | | 6 | "He didn't slow." | | 7 | "She landed in a puddle" | | 8 | "She ignored it." | | 9 | "She knew the façade: bricked" | | 10 | "It swung inward and vomited" | | 11 | "He vanished inside." | | 12 | "She pushed through." | | 13 | "She didn't draw her baton." | | 14 | "She moved, finding each step's" | | 15 | "He turned, keeping his face" | | 16 | "His breath reeked of aniseed" | | 17 | "She didn't flinch." | | 18 | "She kept her eyes on" | | 19 | "He didn't look back." |
| | ratio | 0.298 | |
| 19.52% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 84 | | matches | | 0 | "The rain had clawed at" | | 1 | "Harlow Quinn held her post" | | 2 | "Her left hand traced circles" | | 3 | "Tomás Herrera emerged between the" | | 4 | "He moved like a man" | | 5 | "Quinn peeled herself from the" | | 6 | "Water cascaded from her sleeve." | | 7 | "She didn't call out." | | 8 | "She'd stopped calling out three" | | 9 | "Her boots found the pavement" | | 10 | "Herrera cut past a shuttered" | | 11 | "Quinn matched him, her breath" | | 12 | "The alley between the Victorian" | | 13 | "Herrera vaulted a wheelie bin," | | 14 | "Quinn hurdled the spilled rubbish" | | 15 | "Her voice cracked through the" | | 16 | "He didn't slow." | | 17 | "A scar along his left" | | 18 | "Quinn followed, her fingers biting" | | 19 | "She landed in a puddle" |
| | ratio | 0.881 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 18.63% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 8 | | matches | | 0 | "He moved like a man who knew a lens lingered somewhere in the dark, shoulders curved inside a waxed jacket, the Saint Christopher medallion at his throat snatch…" | | 1 | "She landed in a puddle that swallowed her boot past the ankle." | | 2 | "Graffiti spiraled across its face, lines of paint that dipped and swirled like something alive beneath the sodium glare." | | 3 | "The stairs descended through a throat of Victorian brick slick with mineral stains and something blacker, something that resembled fungus but pulsed in rhythm w…" | | 4 | "She moved, finding each step's edge by instinct, her eyes adjusting to the gloom." | | 5 | "Stalls crowded the platform where trains no longer ran: copper stills bubbling with purple vapour that smelled of rotting lilies, crates stacked with banned alc…" | | 6 | "Near the center, an information broker sat at a card table covered in photographs that twitched like looping silent film, trading secrets by the gram." | | 7 | "Somewhere in that labyrinth, the clique conducted its real business, the business that had consumed six months of her life, the business that had swallowed DS M…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |