| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 26 | | tagDensity | 0.154 | | leniency | 0.308 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1309 | | 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) | |
| 31.25% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1309 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "weight" | | 1 | "glint" | | 2 | "whisper" | | 3 | "calculated" | | 4 | "tension" | | 5 | "pounding" | | 6 | "tracing" | | 7 | "flickered" | | 8 | "chill" | | 9 | "gloom" | | 10 | "flicked" | | 11 | "echoing" | | 12 | "scanned" | | 13 | "velvet" | | 14 | "pulsed" | | 15 | "echo" | | 16 | "pulse" |
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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 | 103 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 103 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 126 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1291 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 1124 | | uniqueNames | 13 | | maxNameDensity | 1.42 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Herrera" | | discoveredNames | | Quinn | 16 | | Berwick | 1 | | Street | 1 | | Saint | 2 | | Christopher | 2 | | Herrera | 16 | | Morris | 1 | | English | 1 | | Soho | 1 | | Camden | 1 | | London | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Saint" | | 2 | "Christopher" | | 3 | "Herrera" | | 4 | "Morris" | | 5 | "Veil" | | 6 | "Market" |
| | places | | 0 | "Berwick" | | 1 | "Street" | | 2 | "Soho" | | 3 | "London" |
| | globalScore | 0.788 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 84 | | 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 | 1291 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 126 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 63 | | mean | 20.49 | | std | 20.73 | | cv | 1.011 | | sampleLengths | | 0 | 120 | | 1 | 69 | | 2 | 7 | | 3 | 13 | | 4 | 30 | | 5 | 47 | | 6 | 41 | | 7 | 8 | | 8 | 6 | | 9 | 32 | | 10 | 57 | | 11 | 7 | | 12 | 28 | | 13 | 8 | | 14 | 7 | | 15 | 39 | | 16 | 16 | | 17 | 22 | | 18 | 10 | | 19 | 7 | | 20 | 6 | | 21 | 5 | | 22 | 13 | | 23 | 21 | | 24 | 13 | | 25 | 26 | | 26 | 4 | | 27 | 5 | | 28 | 62 | | 29 | 39 | | 30 | 5 | | 31 | 58 | | 32 | 5 | | 33 | 56 | | 34 | 10 | | 35 | 2 | | 36 | 5 | | 37 | 3 | | 38 | 10 | | 39 | 5 | | 40 | 15 | | 41 | 10 | | 42 | 27 | | 43 | 17 | | 44 | 11 | | 45 | 5 | | 46 | 18 | | 47 | 5 | | 48 | 40 | | 49 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 103 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 192 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 2 | | flaggedSentences | 13 | | totalSentences | 126 | | ratio | 0.103 | | matches | | 0 | "Eyes up, body forwards, hand brushing the weight of her radio at the hip, she fixed every muscle on the man running ahead—a short, broad figure, the glint of a Saint Christopher medallion bouncing at his throat as he darted between cabs." | | 1 | "Brown eyes wide in his olive face, not wild—calculated." | | 2 | "She trusted her training; she trusted the blade-like calm she’d forged after Morris—" | | 3 | "A voice called out inside—low, harsh, not English." | | 4 | "A steep stone stairwell plunged downward, framed by a gust of chill air carrying a tang—a sharp metallic scent, and something older, stranger, beneath it." | | 5 | "She remembered his file—a paramedic barred by the NHS for treating \"odd\" wounds." | | 6 | "The medallion glinted—Saint Christopher, patron of travelers." | | 7 | "Voices filtered upward, a language she couldn’t grasp, but under it, London’s constant hum frayed—replaced by something older, like the trapped memory of train wheels and the heaviness of earth packed around the living." | | 8 | "The stairwell twisted; the concrete walls grew rougher, graffiti scratched in symbols that coiled then knotted on themselves." | | 9 | "He held up a pale chip—bone-white, carved with symbols." | | 10 | "The crowd flattened in a ripple, some stepping back—the market wary, not afraid, Quinn noted." | | 11 | "Herrera looked back once—eyes warm, hand out." | | 12 | "A distant clang rang through the station—the wild echo of old tracks, or something heavier." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 727 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 11 | | adverbRatio | 0.015130674002751032 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005502063273727648 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 126 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 126 | | mean | 10.25 | | std | 6.34 | | cv | 0.618 | | sampleLengths | | 0 | 16 | | 1 | 14 | | 2 | 12 | | 3 | 42 | | 4 | 19 | | 5 | 3 | | 6 | 3 | | 7 | 11 | | 8 | 22 | | 9 | 15 | | 10 | 9 | | 11 | 20 | | 12 | 3 | | 13 | 7 | | 14 | 13 | | 15 | 3 | | 16 | 14 | | 17 | 13 | | 18 | 4 | | 19 | 17 | | 20 | 23 | | 21 | 3 | | 22 | 13 | | 23 | 9 | | 24 | 19 | | 25 | 8 | | 26 | 6 | | 27 | 10 | | 28 | 2 | | 29 | 9 | | 30 | 11 | | 31 | 13 | | 32 | 20 | | 33 | 24 | | 34 | 4 | | 35 | 3 | | 36 | 25 | | 37 | 1 | | 38 | 2 | | 39 | 8 | | 40 | 7 | | 41 | 11 | | 42 | 13 | | 43 | 15 | | 44 | 8 | | 45 | 8 | | 46 | 11 | | 47 | 11 | | 48 | 10 | | 49 | 7 |
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| 60.32% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.38095238095238093 | | totalSentences | 126 | | uniqueOpeners | 48 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 99 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 99 | | matches | | 0 | "She ignored the damp seeping" | | 1 | "He vanished down an alley" | | 2 | "She pressed a hand to" | | 3 | "Her voice, clipped." | | 4 | "She trusted her training; she" | | 5 | "She darted down the alley," | | 6 | "Her hand hovered near her" | | 7 | "They were nervous in there," | | 8 | "She noted how he used" | | 9 | "She remembered his file—a paramedic" | | 10 | "Her coat dripped onto the" | | 11 | "her voice matched the cold" | | 12 | "They darted down the stairs," | | 13 | "He dropped into the darkness." | | 14 | "She crouched at the top" | | 15 | "She forced herself down, boots" | | 16 | "She entered The Veil Market." | | 17 | "She scanned the crowd." | | 18 | "She kept her voice flat." | | 19 | "He held up a pale" |
| | ratio | 0.232 | |
| 35.76% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 99 | | matches | | 0 | "Harlow Quinn cut across the" | | 1 | "The rain painted her bare" | | 2 | "She ignored the damp seeping" | | 3 | "That runner had already risked" | | 4 | "Something else made these men" | | 5 | "Quinn’s breath drew tight, the" | | 6 | "The runner, Herrera the police" | | 7 | "Brown eyes wide in his" | | 8 | "He vanished down an alley" | | 9 | "Quinn surged forward." | | 10 | "She pressed a hand to" | | 11 | "Her voice, clipped." | | 12 | "She trusted her training; she" | | 13 | "She darted down the alley," | | 14 | "Herrera ducked inside." | | 15 | "Quinn pressed her back into" | | 16 | "Rain dripped off her jaw," | | 17 | "Her hand hovered near her" | | 18 | "A voice called out inside—low," | | 19 | "Another reply in the same" |
| | ratio | 0.848 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 99 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 3 | | matches | | 0 | "Off-the-books jobs flagged by informants, all in Soho and Camden, never a charge that stuck." | | 1 | "The stairwell twisted; the concrete walls grew rougher, graffiti scratched in symbols that coiled then knotted on themselves." | | 2 | "Some faces too sharp, eyes too black, one jaw pocked by barnacles that glistened." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 26 | | tagDensity | 0.038 | | leniency | 0.077 | | rawRatio | 1 | | effectiveRatio | 0.077 | |