| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.16% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1276 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 52.98% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1276 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "predictable" | | 1 | "footsteps" | | 2 | "echoed" | | 3 | "standard" | | 4 | "gleaming" | | 5 | "warmth" | | 6 | "stomach" | | 7 | "depths" | | 8 | "could feel" | | 9 | "weight" |
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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 | 99 | | matches | (empty) | |
| 70.71% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 3 | | narrationSentences | 99 | | 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 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1266 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 92.32% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1127 | | uniqueNames | 15 | | maxNameDensity | 1.15 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 13 | | Soho | 3 | | Morris | 3 | | Hackney | 1 | | Old | 1 | | Compton | 1 | | Street | 1 | | London | 1 | | Victorian-era | 1 | | Underground | 1 | | Victorians | 1 | | Saint | 1 | | Christopher | 1 | | Spaniard | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Victorian-era" | | 4 | "Saint" | | 5 | "Christopher" |
| | places | | 0 | "Soho" | | 1 | "Hackney" | | 2 | "Old" | | 3 | "Compton" | | 4 | "Street" | | 5 | "London" |
| | globalScore | 0.923 | | windowScore | 1 | |
| 13.01% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 4 | | matches | | 0 | "cigarettes that seemed to hang in the very air of this neighbourhood" | | 1 | "quite mould and wasn't quite metal" | | 2 | "quite metal" | | 3 | "seemed insufficient for what sprawled before her" | | 4 | "Bottles that seemed to contain something other than liquid" |
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| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 5 | | per1kWords | 3.949 | | wordCount | 1266 | | matches | | 0 | "not from exertion but from the accumulated smoke of a thousand cigarettes" | | 1 | "Not street-level maintenance infrastructure, but something older, something" | | 2 | "no longer running but" | | 3 | "not fresh but not ancient either" | | 4 | "Not a platform but something stranger" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 106 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 38.36 | | std | 23.72 | | cv | 0.618 | | sampleLengths | | 0 | 8 | | 1 | 60 | | 2 | 72 | | 3 | 5 | | 4 | 74 | | 5 | 69 | | 6 | 54 | | 7 | 49 | | 8 | 12 | | 9 | 72 | | 10 | 23 | | 11 | 58 | | 12 | 48 | | 13 | 66 | | 14 | 14 | | 15 | 59 | | 16 | 55 | | 17 | 7 | | 18 | 27 | | 19 | 3 | | 20 | 40 | | 21 | 63 | | 22 | 12 | | 23 | 22 | | 24 | 59 | | 25 | 29 | | 26 | 57 | | 27 | 5 | | 28 | 24 | | 29 | 52 | | 30 | 41 | | 31 | 24 | | 32 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 99 | | matches | (empty) | |
| 66.67% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 200 | | matches | | 0 | "wasn't heading" | | 1 | "were looking" | | 2 | "wasn't trying" | | 3 | "was going" |
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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) | |
| 98.83% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1137 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 47 | | adverbRatio | 0.04133685136323659 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.008795074758135445 | |
| 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 | 11.94 | | std | 7.67 | | cv | 0.642 | | sampleLengths | | 0 | 8 | | 1 | 22 | | 2 | 13 | | 3 | 25 | | 4 | 15 | | 5 | 12 | | 6 | 5 | | 7 | 11 | | 8 | 29 | | 9 | 5 | | 10 | 18 | | 11 | 17 | | 12 | 29 | | 13 | 2 | | 14 | 4 | | 15 | 4 | | 16 | 7 | | 17 | 24 | | 18 | 26 | | 19 | 7 | | 20 | 5 | | 21 | 30 | | 22 | 3 | | 23 | 21 | | 24 | 7 | | 25 | 14 | | 26 | 11 | | 27 | 17 | | 28 | 5 | | 29 | 4 | | 30 | 3 | | 31 | 17 | | 32 | 21 | | 33 | 3 | | 34 | 6 | | 35 | 25 | | 36 | 13 | | 37 | 6 | | 38 | 4 | | 39 | 17 | | 40 | 13 | | 41 | 5 | | 42 | 23 | | 43 | 9 | | 44 | 13 | | 45 | 3 | | 46 | 9 | | 47 | 14 | | 48 | 7 | | 49 | 6 |
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| 58.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.42452830188679247 | | totalSentences | 106 | | uniqueOpeners | 45 | |
| 69.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 96 | | matches | | 0 | "Instead he drove deeper into" | | 1 | "Then she moved." |
| | ratio | 0.021 | |
| 99.17% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 96 | | matches | | 0 | "She recognized him from the" | | 1 | "Her breath came steady, controlled." | | 2 | "Her partner would have made" | | 3 | "She pushed the thought away." | | 4 | "She could see the panic" | | 5 | "He wasn't heading toward the" | | 6 | "She'd worked these streets for" | | 7 | "She knew where they led." | | 8 | "She took the steps three" | | 9 | "She knew what this was." | | 10 | "She'd filed reports." | | 11 | "She'd watched them disappear from" | | 12 | "She'd stopped asking questions about" | | 13 | "He wasn't trying to escape" | | 14 | "He was going somewhere." | | 15 | "She recognized some of them" | | 16 | "He'd dissolved into the crowd" | | 17 | "She recognised the type." | | 18 | "She'd seen his file across" | | 19 | "He gestured at her hand" |
| | ratio | 0.302 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 80 | | totalSentences | 96 | | matches | | 0 | "The figure bolted from the" | | 1 | "Detective Harlow Quinn's worn leather" | | 2 | "She recognized him from the" | | 3 | "The rain hammered down in" | | 4 | "Quinn's oxfords splashed through puddles" | | 5 | "Her breath came steady, controlled." | | 6 | "Her partner would have made" | | 7 | "DS Morris had jokes about" | | 8 | "She pushed the thought away." | | 9 | "The suspect cut left at" | | 10 | "Quinn followed, her shorter frame" | | 11 | "She could see the panic" | | 12 | "That made him predictable." | | 13 | "That made him catchable." | | 14 | "He wasn't heading toward the" | | 15 | "Quinn's lungs burned, not from" | | 16 | "She'd worked these streets for" | | 17 | "She knew where they led." | | 18 | "The suspect skidded around a" | | 19 | "Quinn didn't slow." |
| | ratio | 0.833 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 96 | | matches | (empty) | | ratio | 0 | |
| 8.93% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 9 | | matches | | 0 | "She recognized him from the surveillance photos: mid-twenties, the kind of hollow-eyed desperation that came from owing money to people who collected more than …" | | 1 | "The suspect cut left at Old Compton Street, weaving between late-night revellers who cursed him as he passed." | | 2 | "She took the steps three at a time, her hand brushing the iron railing to maintain balance on the slick stone." | | 3 | "Not street-level maintenance infrastructure, but something older, something that belonged to London's previous iterations." | | 4 | "Brick walls sweated moisture that caught her torch beam like eyes." | | 5 | "The air tasted different down here, thick with something that wasn't quite mould and wasn't quite metal." | | 6 | "The kind of foundations that cities buried and then forgot, building new streets over top like a palimpsest written in concrete and steel." | | 7 | "Spanish accent, young, with a scar that ran like a zipper down his left forearm and a Saint Christopher medallion gleaming against his chest." | | 8 | "She'd been a detective long enough to recognize someone who knew exactly how far the law could reach." |
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| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 1 | | matches | | 0 | "The Spaniard stepped, his voice dropping so that only Quinn could hear" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |