| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn knelt again [again]" |
| | dialogueSentences | 57 | | tagDensity | 0.158 | | leniency | 0.316 | | rawRatio | 0.111 | | effectiveRatio | 0.035 | |
| 93.29% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1491 | | 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) | |
| 63.11% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1491 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "echoed" | | 1 | "footfall" | | 2 | "stomach" | | 3 | "weight" | | 4 | "furrowed" | | 5 | "etched" | | 6 | "racing" | | 7 | "standard" | | 8 | "shimmered" | | 9 | "mechanical" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 107 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 107 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 156 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1472 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 995 | | uniqueNames | 12 | | maxNameDensity | 1.81 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 18 | | London | 2 | | Sanjeev | 1 | | Rao | 12 | | Britannia | 1 | | Airways | 1 | | Cats | 1 | | Italian | 1 | | Morris | 2 | | Etched | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Rao" | | 3 | "Morris" |
| | places | | | globalScore | 0.595 | | windowScore | 0.5 | |
| 76.47% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 2 | | matches | | 0 | "It was as if he'd materialised right where he lay" | | 1 | "looked like angular script" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.679 | | wordCount | 1472 | | matches | | 0 | "not random, but purposeful" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 156 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 76 | | mean | 19.37 | | std | 16.26 | | cv | 0.839 | | sampleLengths | | 0 | 55 | | 1 | 3 | | 2 | 62 | | 3 | 43 | | 4 | 28 | | 5 | 53 | | 6 | 5 | | 7 | 25 | | 8 | 4 | | 9 | 23 | | 10 | 10 | | 11 | 5 | | 12 | 6 | | 13 | 2 | | 14 | 43 | | 15 | 7 | | 16 | 41 | | 17 | 4 | | 18 | 56 | | 19 | 13 | | 20 | 10 | | 21 | 37 | | 22 | 33 | | 23 | 33 | | 24 | 9 | | 25 | 16 | | 26 | 20 | | 27 | 8 | | 28 | 45 | | 29 | 43 | | 30 | 1 | | 31 | 17 | | 32 | 10 | | 33 | 8 | | 34 | 41 | | 35 | 19 | | 36 | 3 | | 37 | 13 | | 38 | 3 | | 39 | 30 | | 40 | 4 | | 41 | 37 | | 42 | 24 | | 43 | 7 | | 44 | 12 | | 45 | 4 | | 46 | 7 | | 47 | 3 | | 48 | 2 | | 49 | 41 |
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| 95.43% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 107 | | matches | | 0 | "been sealed" | | 1 | "was curled" | | 2 | "been altered" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 179 | | matches | | 0 | "was racing" | | 1 | "was getting" |
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| 14.65% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 156 | | ratio | 0.045 | | matches | | 0 | "The abandoned Tube station smelt of wet concrete and something else—something copper-sweet that Harlow Quinn had learned to associate with bad nights." | | 1 | "Ancient advertisements peeled from the walls—Britannia Airways, a production of Cats, something about a phone service that no longer existed." | | 2 | "But there was something about his expression—a lingering surprise, as if death had arrived without warning." | | 3 | "But her instinct—honed over eighteen years on the force, sharpened further by the case that had taken DS Morris from her three years ago—told her this was different." | | 4 | "Rao was right—nothing here but rust and rodent droppings." | | 5 | "Scratches in the concrete that formed a pattern—not random, but purposeful." | | 6 | "But she had questions now—better questions, the kind that could crack open a case if she followed them far enough." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 553 | | adjectiveStacks | 1 | | stackExamples | | 0 | "post-an abandoned Tube" |
| | adverbCount | 16 | | adverbRatio | 0.028933092224231464 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.009041591320072333 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 156 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 156 | | mean | 9.44 | | std | 6.74 | | cv | 0.714 | | sampleLengths | | 0 | 22 | | 1 | 20 | | 2 | 5 | | 3 | 8 | | 4 | 3 | | 5 | 9 | | 6 | 15 | | 7 | 14 | | 8 | 24 | | 9 | 8 | | 10 | 20 | | 11 | 15 | | 12 | 14 | | 13 | 14 | | 14 | 5 | | 15 | 15 | | 16 | 7 | | 17 | 12 | | 18 | 14 | | 19 | 5 | | 20 | 4 | | 21 | 21 | | 22 | 4 | | 23 | 5 | | 24 | 5 | | 25 | 2 | | 26 | 11 | | 27 | 10 | | 28 | 5 | | 29 | 4 | | 30 | 2 | | 31 | 2 | | 32 | 7 | | 33 | 36 | | 34 | 3 | | 35 | 4 | | 36 | 24 | | 37 | 17 | | 38 | 4 | | 39 | 16 | | 40 | 12 | | 41 | 12 | | 42 | 6 | | 43 | 10 | | 44 | 13 | | 45 | 10 | | 46 | 4 | | 47 | 33 | | 48 | 3 | | 49 | 13 |
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| 67.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4230769230769231 | | totalSentences | 156 | | uniqueOpeners | 66 | |
| 34.36% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 97 | | matches | | | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 97 | | matches | | 0 | "She stepped over the yellow" | | 1 | "He was young, eager, and" | | 2 | "She descended the stairs with" | | 3 | "His shoes were Italian leather," | | 4 | "She could see her own" | | 5 | "It was as if he'd" | | 6 | "She'd seen enough of London's" | | 7 | "She studied the victim's face." | | 8 | "She couldn't argue with that" | | 9 | "She walked the perimeter of" | | 10 | "She approached it anyway." | | 11 | "She crouched, angling her torch." | | 12 | "He joined her, squeezing into" | | 13 | "It reminded her of something," | | 14 | "She photographed it with her" | | 15 | "Her mind was racing now," | | 16 | "Her torch beam caught the" | | 17 | "She stepped closer, water seeping" | | 18 | "He sloshed through the water" | | 19 | "She pulled her hand back." |
| | ratio | 0.216 | |
| 83.71% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 97 | | matches | | 0 | "The abandoned Tube station smelt" | | 1 | "She stepped over the yellow" | | 2 | "The hour when London showed" | | 3 | "DC Sanjeev Rao's voice echoed" | | 4 | "He was young, eager, and" | | 5 | "She descended the stairs with" | | 6 | "Water dripped somewhere in the" | | 7 | "The platform stretched before her," | | 8 | "Rao gestured toward the corpse" | | 9 | "Quinn crouched beside the body." | | 10 | "The man wore a tailored" | | 11 | "His shoes were Italian leather," | | 12 | "Rao shifted his weight." | | 13 | "Rao aimed his beam downward." | | 14 | "The victim's fingernails were clean." | | 15 | "The skin around his cuticles" | | 16 | "The torchlight swept back." | | 17 | "Quinn stood, her sharp jaw" | | 18 | "Rao's brow furrowed." | | 19 | "Quinn circled the body slowly" |
| | ratio | 0.753 | |
| 51.55% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 97 | | matches | | | ratio | 0.01 | |
| 9.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 8 | | matches | | 0 | "Water dripped somewhere in the darkness beyond the police cordon, a steady rhythm that would drive a person mad if they listened long enough." | | 1 | "But there was something about his expression—a lingering surprise, as if death had arrived without warning." | | 2 | "But her instinct—honed over eighteen years on the force, sharpened further by the case that had taken DS Morris from her three years ago—told her this was diffe…" | | 3 | "Scratches in the concrete that formed a pattern—not random, but purposeful." | | 4 | "Nothing that would explain how a well-dressed man had died in the middle of an abandoned station without getting his shoes wet." | | 5 | "As if the wall itself had been altered at a fundamental level, the molecules rearranged into something that shimmered almost imperceptibly in the artificial lig…" | | 6 | "Quinn stood alone in the tunnel, water soaking through her shoes, staring at the spot on the wall." | | 7 | "But she had questions now—better questions, the kind that could crack open a case if she followed them far enough." |
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| 13.89% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn stood, her sharp jaw tight" | | 1 | "Quinn knelt again, this time examining the area around the body" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "But Quinn doubted (doubt)" |
| | dialogueSentences | 57 | | tagDensity | 0.018 | | leniency | 0.035 | | rawRatio | 1 | | effectiveRatio | 0.035 | |