| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said softly [softly]" |
| | dialogueSentences | 27 | | tagDensity | 0.407 | | leniency | 0.815 | | rawRatio | 0.091 | | effectiveRatio | 0.074 | |
| 84.56% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1295 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "sharply" | | 1 | "really" | | 2 | "completely" | | 3 | "softly" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 7.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1295 | | totalAiIsms | 24 | | found | | | highlights | | 0 | "flickered" | | 1 | "rhythmic" | | 2 | "electric" | | 3 | "traced" | | 4 | "measured" | | 5 | "sanctuary" | | 6 | "scanning" | | 7 | "sense of" | | 8 | "calculating" | | 9 | "weight" | | 10 | "silence" | | 11 | "clandestine" | | 12 | "flicker" | | 13 | "tension" | | 14 | "resolve" | | 15 | "unspoken" | | 16 | "whisper" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "weight of words/silence" | | count | 1 |
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| | highlights | | 0 | "The weight of the silence" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 66 | | matches | (empty) | |
| 77.92% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 66 | | filterMatches | (empty) | | hedgeMatches | | 0 | "managed to" | | 1 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 82 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1290 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 959 | | uniqueNames | 8 | | maxNameDensity | 1.25 | | worstName | "Aurora" | | maxWindowNameDensity | 3 | | worstWindowName | "Evan" | | discoveredNames | | Raven | 1 | | Nest | 4 | | Soho | 1 | | London | 1 | | Aurora | 12 | | Cardiff | 1 | | Evan | 11 | | Silas | 6 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Aurora" | | 3 | "Evan" | | 4 | "Silas" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Cardiff" |
| | globalScore | 0.874 | | windowScore | 0.667 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 5 | | matches | | 0 | "quite managed to kill" | | 1 | "not quite touching" | | 2 | "looked like the terrified boy he had been" | | 3 | "sounded like a final punctuation mark" | | 4 | "breath that seemed to collapse her shoulders" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.775 | | wordCount | 1290 | | matches | | 0 | "not just by Aurora’s resolve, but by the environment she had built for herself" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 82 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 36.86 | | std | 22.69 | | cv | 0.616 | | sampleLengths | | 0 | 94 | | 1 | 89 | | 2 | 45 | | 3 | 34 | | 4 | 1 | | 5 | 40 | | 6 | 1 | | 7 | 78 | | 8 | 31 | | 9 | 21 | | 10 | 38 | | 11 | 9 | | 12 | 57 | | 13 | 23 | | 14 | 51 | | 15 | 27 | | 16 | 55 | | 17 | 20 | | 18 | 44 | | 19 | 49 | | 20 | 34 | | 21 | 21 | | 22 | 9 | | 23 | 66 | | 24 | 57 | | 25 | 33 | | 26 | 47 | | 27 | 31 | | 28 | 38 | | 29 | 25 | | 30 | 6 | | 31 | 56 | | 32 | 13 | | 33 | 17 | | 34 | 30 |
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| 84.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 66 | | matches | | 0 | "was dressed" | | 1 | "were sunken" | | 2 | "were fixed" | | 3 | "was outmatched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 149 | | matches | | |
| 38.33% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 82 | | ratio | 0.037 | | matches | | 0 | "She wore her delivery jacket, the fabric worn thin at the elbows, and her fingers traced the small crescent-shaped scar on her left wrist—a nervous habit she hadn't quite managed to kill." | | 1 | "He looked at her—really looked at her—and his expression shifted from shock to a twisted kind of longing." | | 2 | "Around them, the other patrons of the Nest—a few regulars and a couple of clandestine types huddled in the corners—seemed to fade away." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 968 | | adjectiveStacks | 2 | | stackExamples | | 0 | "small crescent-shaped scar" | | 1 | "dim, map-lined sanctuary" |
| | adverbCount | 25 | | adverbRatio | 0.025826446280991736 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.011363636363636364 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 15.73 | | std | 9.63 | | cv | 0.612 | | sampleLengths | | 0 | 24 | | 1 | 18 | | 2 | 20 | | 3 | 32 | | 4 | 20 | | 5 | 20 | | 6 | 17 | | 7 | 32 | | 8 | 10 | | 9 | 27 | | 10 | 8 | | 11 | 7 | | 12 | 27 | | 13 | 1 | | 14 | 22 | | 15 | 18 | | 16 | 1 | | 17 | 3 | | 18 | 3 | | 19 | 12 | | 20 | 29 | | 21 | 31 | | 22 | 9 | | 23 | 12 | | 24 | 10 | | 25 | 6 | | 26 | 7 | | 27 | 8 | | 28 | 16 | | 29 | 18 | | 30 | 4 | | 31 | 9 | | 32 | 8 | | 33 | 34 | | 34 | 15 | | 35 | 13 | | 36 | 10 | | 37 | 8 | | 38 | 27 | | 39 | 16 | | 40 | 10 | | 41 | 17 | | 42 | 16 | | 43 | 39 | | 44 | 7 | | 45 | 13 | | 46 | 4 | | 47 | 40 | | 48 | 7 | | 49 | 23 |
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| 36.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.3048780487804878 | | totalSentences | 82 | | uniqueOpeners | 25 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 33.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 60 | | matches | | 0 | "She wore her delivery jacket," | | 1 | "He moved with a quiet," | | 2 | "He was polishing a highball" | | 3 | "He didn't look up when" | | 4 | "He was dressed in a" | | 5 | "It was a voice that" | | 6 | "She didn't blink." | | 7 | "She simply stared at him," | | 8 | "She looked at the man" | | 9 | "He took a step forward," | | 10 | "Her voice was flat, a" | | 11 | "He looked at her—really looked" | | 12 | "He hadn't stopped polishing the" | | 13 | "He shifted his weight, the" | | 14 | "She shifted her weight, her" | | 15 | "she countered, her voice gaining" | | 16 | "she said, and for the" | | 17 | "He looked small." | | 18 | "He looked like the terrified" | | 19 | "He opened his mouth to" |
| | ratio | 0.467 | |
| 1.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 60 | | matches | | 0 | "The green neon sign of" | | 1 | "Aurora leaned against the mahogany" | | 2 | "She wore her delivery jacket," | | 3 | "Silas was at the other" | | 4 | "He moved with a quiet," | | 5 | "He was polishing a highball" | | 6 | "He didn't look up when" | | 7 | "The stranger stopped dead in" | | 8 | "He was dressed in a" | | 9 | "Aurora felt the air leave" | | 10 | "The world narrowed until there" | | 11 | "The voice was deeper than" | | 12 | "It was a voice that" | | 13 | "Aurora didn’t move." | | 14 | "She didn't blink." | | 15 | "She simply stared at him," | | 16 | "She looked at the man" | | 17 | "The suit was a mask," | | 18 | "He took a step forward," | | 19 | "Her voice was flat, a" |
| | ratio | 0.917 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 6.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 8 | | matches | | 0 | "Aurora leaned against the mahogany bar, her shoulder-length black hair framing a face that had learned the art of neutrality." | | 1 | "He didn't look up when the door creaked open, admitting a gust of London rain and a man who looked entirely out of place in the dim, map-lined sanctuary of the …" | | 2 | "He was dressed in a charcoal suit that cost more than Aurora’s annual rent, his posture rigid, his eyes scanning the room with a frantic, predatory energy." | | 3 | "She looked at the man who had spent three years convincing her that she was nothing, and she realized with a jarring sense of detachment that he looked diminish…" | | 4 | "He hadn't stopped polishing the glass, but his hazel eyes were fixed on Evan, calculating the threat level with the clinical efficiency of a man who had spent d…" | | 5 | "She shifted her weight, her mind already calculating the fastest route to the exit, the way through the kitchen, the alleyway that led toward the main road." | | 6 | "The room became a vacuum, containing only the debris of a relationship that had burned through everything it touched." | | 7 | "Evan looked at Silas, seeing the silver ring, the steady gaze, and the quiet authority of a man who had seen far worse things than a heartbroken ex-boyfriend." |
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| 34.09% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 2 | | matches | | 0 | "she countered, her voice gaining a sharp, rhythmic edge" | | 1 | "she admitted, her voice barely a whisper" |
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| 38.89% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 3 | | fancyTags | | 0 | "she snapped (snap)" | | 1 | "he whispered (whisper)" | | 2 | "she admitted (admit)" |
| | dialogueSentences | 27 | | tagDensity | 0.37 | | leniency | 0.741 | | rawRatio | 0.3 | | effectiveRatio | 0.222 | |