| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 94.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 970 | | totalAiIsmAdverbs | 1 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 970 | | totalAiIsms | 29 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "reminder" | | 1 | "measured" | | 2 | "predator" | | 3 | "could feel" | | 4 | "weight" | | 5 | "scanning" | | 6 | "warmth" | | 7 | "scanned" | | 8 | "echo" | | 9 | "footsteps" | | 10 | "depths" | | 11 | "resolve" | | 12 | "cacophony" | | 13 | "otherworldly" | | 14 | "familiar" | | 15 | "etched" | | 16 | "amidst" | | 17 | "beacon" | | 18 | "pulse" | | 19 | "echoing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "heart pounded in chest" | | count | 1 |
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| | highlights | | 0 | "heart pounded in her chest" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 62 | | matches | (empty) | |
| 50.69% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 62 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 62 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 968 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 77.69% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 968 | | uniqueNames | 10 | | maxNameDensity | 1.45 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 14 | | Soho | 1 | | Raven | 1 | | Nest | 2 | | Morris | 1 | | Veil | 3 | | Market | 2 | | London | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Morris" |
| | places | | | globalScore | 0.777 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 1 | | matches | | 0 | "photographs that seemed to watch her every move" |
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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 | 968 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 62 | | matches | (empty) | |
| 6.32% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 19 | | mean | 50.95 | | std | 8.77 | | cv | 0.172 | | sampleLengths | | 0 | 66 | | 1 | 65 | | 2 | 55 | | 3 | 55 | | 4 | 44 | | 5 | 63 | | 6 | 40 | | 7 | 45 | | 8 | 49 | | 9 | 41 | | 10 | 53 | | 11 | 46 | | 12 | 45 | | 13 | 51 | | 14 | 57 | | 15 | 43 | | 16 | 43 | | 17 | 41 | | 18 | 66 |
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| 93.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 62 | | matches | | 0 | "was known" | | 1 | "being exchanged" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 151 | | matches | | |
| 96.77% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 62 | | ratio | 0.016 | | matches | | 0 | "The suspect—a man in a dark hooded jacket—glanced back, his face obscured by the shadows." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 973 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.020554984583761562 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0041109969167523125 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 62 | | echoCount | 0 | | echoWords | (empty) | |
| 82.45% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 62 | | mean | 15.61 | | std | 5.56 | | cv | 0.356 | | sampleLengths | | 0 | 27 | | 1 | 17 | | 2 | 22 | | 3 | 15 | | 4 | 14 | | 5 | 9 | | 6 | 27 | | 7 | 15 | | 8 | 18 | | 9 | 22 | | 10 | 13 | | 11 | 16 | | 12 | 23 | | 13 | 3 | | 14 | 14 | | 15 | 16 | | 16 | 8 | | 17 | 6 | | 18 | 15 | | 19 | 29 | | 20 | 19 | | 21 | 14 | | 22 | 10 | | 23 | 16 | | 24 | 17 | | 25 | 14 | | 26 | 14 | | 27 | 22 | | 28 | 27 | | 29 | 8 | | 30 | 16 | | 31 | 17 | | 32 | 19 | | 33 | 3 | | 34 | 20 | | 35 | 11 | | 36 | 17 | | 37 | 16 | | 38 | 13 | | 39 | 10 | | 40 | 17 | | 41 | 18 | | 42 | 18 | | 43 | 16 | | 44 | 17 | | 45 | 11 | | 46 | 27 | | 47 | 19 | | 48 | 8 | | 49 | 11 |
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| 46.77% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.2903225806451613 | | totalSentences | 62 | | uniqueOpeners | 18 | |
| 53.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 62 | | matches | | 0 | "Then he turned, breaking into" |
| | ratio | 0.016 | |
| 97.42% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 62 | | matches | | 0 | "Her breath came in measured" | | 1 | "Her quarry was fast, but" | | 2 | "She could feel the weight" | | 3 | "She pushed herself harder, her" | | 4 | "She rounded the corner, her" | | 5 | "She pushed through the door," | | 6 | "It was slightly ajar, revealing" | | 7 | "She moved toward it, her" | | 8 | "She paused, listening, and heard" | | 9 | "Her quarry was close, but" | | 10 | "She stepped forward, the darkness" | | 11 | "Her heart beat a steady" | | 12 | "She had never expected to" | | 13 | "He was speaking with a" | | 14 | "She hesitated, the weight of" | | 15 | "She couldn't let him escape," | | 16 | "She took a step forward," | | 17 | "She was a hunter in" | | 18 | "She would not let him" |
| | ratio | 0.306 | |
| 40.65% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 62 | | matches | | 0 | "Rain lashed against the city" | | 1 | "Her breath came in measured" | | 2 | "The streets of Soho glistened" | | 3 | "Quinn's eyes, sharp and unyielding," | | 4 | "Her quarry was fast, but" | | 5 | "She could feel the weight" | | 6 | "The suspect—a man in a" | | 7 | "Quinn caught a glimpse of" | | 8 | "She pushed herself harder, her" | | 9 | "The streets narrowed, the buildings" | | 10 | "Quinn's heart pounded in her" | | 11 | "She rounded the corner, her" | | 12 | "The Raven's Nest." | | 13 | "Quinn hesitated for a fraction" | | 14 | "The Nest was known for" | | 15 | "She pushed through the door," | | 16 | "The air inside was thick" | | 17 | "Patrons turned to look as" | | 18 | "Quinn scanned the room, her" | | 19 | "It was slightly ajar, revealing" |
| | ratio | 0.839 | |
| 80.65% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 62 | | matches | | 0 | "To follow him into the" |
| | ratio | 0.016 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 11 | | matches | | 0 | "Rain lashed against the city like a thousand tiny daggers, each drop a reminder of the relentless pursuit that had brought Detective Harlow Quinn to this moment…" | | 1 | "The streets of Soho glistened under the streetlights, the reflections of neon signs bleeding into the puddles that pooled along the curbs." | | 2 | "She could feel the weight of her worn leather watch on her wrist, a constant reminder of time slipping away, of the urgency that drove her forward." | | 3 | "She pushed herself harder, her boots splashing through the water, her mind a focused blade cutting through the chaos of the chase." | | 4 | "Quinn's heart pounded in her chest, a steady drumbeat that matched the rhythm of her footfalls." | | 5 | "She rounded the corner, her eyes scanning the alleyway, and saw him again, slipping through a door beneath a distinctive green neon sign." | | 6 | "The air inside was thick with the scent of smoke and aged wood, the walls lined with old maps and black-and-white photographs that seemed to watch her every mov…" | | 7 | "Patrons turned to look as she entered, their conversations pausing, eyes flicking to the badge clipped to her belt." | | 8 | "The memory of her partner's death was a shadow that never left her, a reminder of the supernatural forces that lurked beneath the surface of her world." | | 9 | "Enchanted trinkets glowed with an otherworldly light, casting eerie shadows that danced across the stone floor." | | 10 | "Then he turned, breaking into a run, his footsteps echoing through the market." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |