| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1337 | | 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) | |
| 88.78% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1337 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "predictable" | | 1 | "traced" | | 2 | "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 | 83 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 83 | | 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 | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1350 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 1203 | | uniqueNames | 13 | | maxNameDensity | 0.83 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 10 | | Tomás | 1 | | Herrera | 8 | | Raven | 1 | | Nest | 2 | | Soho | 1 | | London | 2 | | Saint | 1 | | Christopher | 1 | | Morris | 3 | | Camden | 1 | | Transport | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Raven" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Morris" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Camden" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 68.03% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 2 | | matches | | 0 | "'t take to A&E apparently ended up on his tab" | | 1 | "felt like a held breath — before she ca" |
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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 | 1350 | | 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 | 42 | | mean | 32.14 | | std | 28.36 | | cv | 0.882 | | sampleLengths | | 0 | 23 | | 1 | 76 | | 2 | 56 | | 3 | 1 | | 4 | 31 | | 5 | 13 | | 6 | 27 | | 7 | 4 | | 8 | 41 | | 9 | 2 | | 10 | 78 | | 11 | 19 | | 12 | 2 | | 13 | 83 | | 14 | 60 | | 15 | 20 | | 16 | 3 | | 17 | 8 | | 18 | 91 | | 19 | 3 | | 20 | 58 | | 21 | 5 | | 22 | 71 | | 23 | 22 | | 24 | 58 | | 25 | 70 | | 26 | 41 | | 27 | 26 | | 28 | 6 | | 29 | 31 | | 30 | 7 | | 31 | 2 | | 32 | 39 | | 33 | 61 | | 34 | 98 | | 35 | 40 | | 36 | 5 | | 37 | 17 | | 38 | 30 | | 39 | 8 | | 40 | 1 | | 41 | 13 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 83 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 190 | | matches | | 0 | "was running" | | 1 | "was letting" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 96 | | ratio | 0.094 | | matches | | 0 | "He was also predictable — three years of chasing people through this city had taught her that everyone runs the way they live, and Herrera ran like a man who fixed things: straight lines, no waste." | | 1 | "He tore down the alley and hooked right onto the back street, and she lost sight of him for four seconds — four seconds that felt like a held breath — before she caught the flash of his medallion again under a sodium lamp." | | 2 | "And underneath it, underneath all of it, Morris's face floated up the way it always did when her body hit its limit — the last photograph of him, laughing outside the station, three weeks before the night nobody could explain to her satisfaction." | | 3 | "She could hear him — boots on wet stone, fading." | | 4 | "Herrera held something up between his fingers — small, pale, carved — and the woman turned it in the lantern light." | | 5 | "Before he did, he looked back — Quinn would swear to it, he looked straight at her across the dead platform — and shook his head once." | | 6 | "The light washed over Quinn's face and the woman studied her the way a butcher studies a cut of meat — unhurried, professional." | | 7 | "Cold air breathed out of it, carrying smells she couldn't name — smoke, incense, something metallic and alive." | | 8 | "Every other instinct — the older kind, the kind that had started whispering the night Morris died and never stopped — told her that the rules she lived by ended at this tunnel mouth, and that the people who'd gone looking for answers past this line before her hadn't all come back." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1193 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.028499580888516344 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.002514668901927913 | |
| 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 | 14.06 | | std | 12.21 | | cv | 0.868 | | sampleLengths | | 0 | 23 | | 1 | 28 | | 2 | 26 | | 3 | 22 | | 4 | 6 | | 5 | 30 | | 6 | 14 | | 7 | 6 | | 8 | 1 | | 9 | 3 | | 10 | 28 | | 11 | 7 | | 12 | 6 | | 13 | 19 | | 14 | 8 | | 15 | 4 | | 16 | 14 | | 17 | 27 | | 18 | 2 | | 19 | 39 | | 20 | 3 | | 21 | 36 | | 22 | 12 | | 23 | 7 | | 24 | 2 | | 25 | 44 | | 26 | 7 | | 27 | 15 | | 28 | 17 | | 29 | 3 | | 30 | 2 | | 31 | 6 | | 32 | 43 | | 33 | 3 | | 34 | 3 | | 35 | 20 | | 36 | 3 | | 37 | 8 | | 38 | 25 | | 39 | 15 | | 40 | 3 | | 41 | 5 | | 42 | 43 | | 43 | 3 | | 44 | 48 | | 45 | 1 | | 46 | 1 | | 47 | 8 | | 48 | 5 | | 49 | 12 |
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| 65.63% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.46875 | | totalSentences | 96 | | uniqueOpeners | 45 | |
| 43.86% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 76 | | matches | | | ratio | 0.013 | |
| 72.63% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 76 | | matches | | 0 | "She knew him from the" | | 1 | "His shoulders locked." | | 2 | "He turned just enough for" | | 3 | "He said it like a" | | 4 | "She stepped off the kerb" | | 5 | "She let the name land" | | 6 | "He went left through the" | | 7 | "He was fast." | | 8 | "He was also predictable —" | | 9 | "he shouted over his shoulder," | | 10 | "He tore down the alley" | | 11 | "He wasn't running like a" | | 12 | "He was running like a" | | 13 | "He squeezed through a gap" | | 14 | "Her knee screamed." | | 15 | "She ignored it." | | 16 | "She burst out onto the" | | 17 | "Her breath burned." | | 18 | "Her heartbeat filled her ears." | | 19 | "She ran faster." |
| | ratio | 0.368 | |
| 65.26% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 76 | | matches | | 0 | "Detective Harlow Quinn had been" | | 1 | "The rain had started as" | | 2 | "Quinn stood beneath a dead" | | 3 | "Herrera stepped into the downpour" | | 4 | "She knew him from the" | | 5 | "Tonight that was going to" | | 6 | "His shoulders locked." | | 7 | "He turned just enough for" | | 8 | "He said it like a" | | 9 | "She stepped off the kerb" | | 10 | "She let the name land" | | 11 | "He went left through the" | | 12 | "He was fast." | | 13 | "He was also predictable —" | | 14 | "he shouted over his shoulder," | | 15 | "He tore down the alley" | | 16 | "He wasn't running like a" | | 17 | "That was the thing that" | | 18 | "He was running like a" | | 19 | "The streets blurred." |
| | ratio | 0.789 | |
| 65.79% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 76 | | matches | | 0 | "Before he did, he looked" |
| | ratio | 0.013 | |
| 11.28% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 7 | | matches | | 0 | "The rain had started as a drizzle around ten and turned serious by midnight, hammering the Soho pavement in sheets that turned the streetlights into smears of o…" | | 1 | "He went left through the gap between a shuttered kebab shop and a sex shop's blinking sign, and Quinn followed without a moment's hesitation, her boots hitting …" | | 2 | "Below, a corridor of brick arched away into the dark, lit at intervals by caged bulbs that had no business working in an abandoned station." | | 3 | "The shape was a woman, broad as a wardrobe, holding a lantern that burned with a light Quinn's eyes kept insisting was the wrong colour." | | 4 | "Every instinct from eighteen years of service told her the same thing: this was a crime scene waiting to be catalogued, a network waiting to be mapped, and the …" | | 5 | "Every other instinct — the older kind, the kind that had started whispering the night Morris died and never stopped — told her that the rules she lived by ended…" | | 6 | "Three years of files that contradicted themselves, of witnesses who changed their stories overnight, of a partner's death wrapped in a silence no warrant had ev…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 2 | | matches | | 0 | "Herrera called, his voice bouncing off brick," | | 1 | "he called, his voice strange and flat in the vaulted dark" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 22 | | tagDensity | 0.227 | | leniency | 0.455 | | rawRatio | 0.2 | | effectiveRatio | 0.091 | |