| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "She swallowed hard [hard]" |
| | dialogueSentences | 40 | | tagDensity | 0.275 | | leniency | 0.55 | | rawRatio | 0.091 | | effectiveRatio | 0.05 | |
| 88.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1332 | | totalAiIsmAdverbs | 3 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
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| | 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) | |
| 51.20% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1332 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "gloom" | | 1 | "echoing" | | 2 | "chill" | | 3 | "weight" | | 4 | "pristine" | | 5 | "measured" | | 6 | "chaotic" | | 7 | "shattered" | | 8 | "database" | | 9 | "vibrated" | | 10 | "footsteps" | | 11 | "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 | 1 | | narrationSentences | 100 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 100 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 129 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1328 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1041 | | uniqueNames | 18 | | maxNameDensity | 1.92 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 20 | | Savile | 1 | | Row | 1 | | Sergeant | 1 | | Miller | 9 | | Tube | 1 | | Camden | 1 | | West | 1 | | End | 1 | | Met | 1 | | Morris | 2 | | Rotherhithe | 1 | | Greek | 1 | | Latin | 1 | | Hampstead | 1 | | Internal | 1 | | Affairs | 1 | | Eva | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Sergeant" | | 2 | "Miller" | | 3 | "Morris" | | 4 | "Affairs" | | 5 | "Eva" |
| | places | | 0 | "West" | | 1 | "End" | | 2 | "Greek" | | 3 | "Hampstead" |
| | globalScore | 0.539 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | 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 | 1328 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 129 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 66 | | mean | 20.12 | | std | 16.06 | | cv | 0.798 | | sampleLengths | | 0 | 41 | | 1 | 33 | | 2 | 17 | | 3 | 5 | | 4 | 6 | | 5 | 8 | | 6 | 7 | | 7 | 9 | | 8 | 12 | | 9 | 74 | | 10 | 22 | | 11 | 28 | | 12 | 44 | | 13 | 5 | | 14 | 10 | | 15 | 4 | | 16 | 8 | | 17 | 7 | | 18 | 6 | | 19 | 50 | | 20 | 3 | | 21 | 43 | | 22 | 8 | | 23 | 10 | | 24 | 10 | | 25 | 38 | | 26 | 25 | | 27 | 5 | | 28 | 38 | | 29 | 38 | | 30 | 19 | | 31 | 5 | | 32 | 26 | | 33 | 25 | | 34 | 3 | | 35 | 2 | | 36 | 11 | | 37 | 60 | | 38 | 12 | | 39 | 11 | | 40 | 35 | | 41 | 40 | | 42 | 8 | | 43 | 18 | | 44 | 17 | | 45 | 45 | | 46 | 28 | | 47 | 29 | | 48 | 4 | | 49 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 100 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 182 | | matches | | |
| 98.56% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 129 | | ratio | 0.016 | | matches | | 0 | "She bypassed the shattered skull—blood pooled beneath the head, dark and coagulated, far too little of it for a fatal head wound—and checked his pockets." | | 1 | "Strange, jagged sigils—nothing from Greek, Latin, or any criminal gang tattoo database Quinn knew—ringed the cracked glass face." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1056 | | adjectiveStacks | 1 | | stackExamples | | 0 | "White, polished smooth, warming" |
| | adverbCount | 21 | | adverbRatio | 0.019886363636363636 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.003787878787878788 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 129 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 129 | | mean | 10.29 | | std | 6.64 | | cv | 0.645 | | sampleLengths | | 0 | 18 | | 1 | 23 | | 2 | 6 | | 3 | 11 | | 4 | 16 | | 5 | 12 | | 6 | 5 | | 7 | 5 | | 8 | 6 | | 9 | 8 | | 10 | 7 | | 11 | 9 | | 12 | 3 | | 13 | 9 | | 14 | 15 | | 15 | 22 | | 16 | 12 | | 17 | 5 | | 18 | 13 | | 19 | 7 | | 20 | 22 | | 21 | 3 | | 22 | 19 | | 23 | 1 | | 24 | 5 | | 25 | 12 | | 26 | 32 | | 27 | 5 | | 28 | 10 | | 29 | 4 | | 30 | 8 | | 31 | 3 | | 32 | 4 | | 33 | 6 | | 34 | 11 | | 35 | 5 | | 36 | 20 | | 37 | 14 | | 38 | 2 | | 39 | 1 | | 40 | 28 | | 41 | 10 | | 42 | 2 | | 43 | 3 | | 44 | 8 | | 45 | 10 | | 46 | 10 | | 47 | 18 | | 48 | 20 | | 49 | 10 |
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| 98.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.6046511627906976 | | totalSentences | 129 | | uniqueOpeners | 78 | |
| 77.52% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 86 | | matches | | 0 | "Slowly, deliberately, fighting a sluggish" | | 1 | "Right before Internal Affairs seized" |
| | ratio | 0.023 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 86 | | matches | | 0 | "He chewed gum, the wet" | | 1 | "She pulled on nitrile gloves." | | 2 | "He shifted his weight, boots" | | 3 | "She checked the worn leather" | | 4 | "He scratched his stubble." | | 5 | "She walked the platform edge." | | 6 | "She pinched a fleck of" | | 7 | "Her beam climbed the curved" | | 8 | "She bypassed the shattered skull—blood" | | 9 | "Her fingers brushed the lining" | | 10 | "She extracted it with tweezers." | | 11 | "She bagged the token and" | | 12 | "She hopped down into the" | | 13 | "She crouched and nudged the" | | 14 | "His heavy footsteps faded, swallowed" | | 15 | "She walked toward the bricked-up" | | 16 | "Her breath plumed white in" | | 17 | "Her voice shook, refined and" | | 18 | "She swallowed hard, green eyes" |
| | ratio | 0.221 | |
| 93.72% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 86 | | matches | | 0 | "Harlow Quinn stepped over a" | | 1 | "The dead man on the" | | 2 | "Detective Sergeant Miller said" | | 3 | "He chewed gum, the wet" | | 4 | "Quinn crouched beside the body," | | 5 | "She pulled on nitrile gloves." | | 6 | "Miller stopped chewing." | | 7 | "He shifted his weight, boots" | | 8 | "Quinn turned her torch away" | | 9 | "Decades of grime coated the" | | 10 | "Water dripped somewhere in the" | | 11 | "Ozone, scorched copper, and sweet," | | 12 | "The same scent that clung" | | 13 | "Quinn's jaw tightened." | | 14 | "She checked the worn leather" | | 15 | "Rigor mortis locked his jaw." | | 16 | "Miller said, flipping shut his" | | 17 | "Quinn pointed at the dead" | | 18 | "Miller squinted down." | | 19 | "He scratched his stubble." |
| | ratio | 0.733 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 55.39% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 6 | | matches | | 0 | "Decades of grime coated the walls, peeling away from vintage posters for West End shows that closed before she joined the Met." | | 1 | "The same scent that clung to DS Morris's jacket three years ago, right before his heart stopped in an empty Rotherhithe warehouse." | | 2 | "A clean circular perimeter stretched across the floor, twelve feet wide, as if a giant glass jar had covered the tiles for years and someone just lifted it." | | 3 | "Whatever brass object he clutched before dying had been ripped from his grasp, tearing a sliver of skin with it." | | 4 | "A low, sub-audible hum crawled up her wrist, rattling the small bones of her forearm and setting her back teeth on edge." | | 5 | "Curly red hair spilled over a thick coat, framing a pale, freckled face and round glasses that flashed white in the glare." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn barked (bark)" | | 1 | "Quinn ordered (order)" |
| | dialogueSentences | 40 | | tagDensity | 0.175 | | leniency | 0.35 | | rawRatio | 0.286 | | effectiveRatio | 0.1 | |