| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "Tomás said quietly [quietly]" |
| | dialogueSentences | 22 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0.125 | | effectiveRatio | 0.091 | |
| 79.45% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 973 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "very" | | 2 | "sharply" |
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| 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) | |
| 12.64% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 973 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "dancing" | | 1 | "weight" | | 2 | "flicker" | | 3 | "flicked" | | 4 | "footsteps" | | 5 | "echoed" | | 6 | "flickered" | | 7 | "shimmered" | | 8 | "fractured" | | 9 | "silk" | | 10 | "whisper" | | 11 | "trembled" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "let out a breath" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "let out a breath" | | 1 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 108 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 108 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 122 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 962 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 90.76% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 844 | | uniqueNames | 13 | | maxNameDensity | 1.18 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 10 | | London | 1 | | Sauer | 1 | | Saint | 1 | | Christopher | 1 | | Raven | 2 | | Nest | 2 | | English | 1 | | Europe | 1 | | Edwardian | 1 | | Tomás | 7 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sauer" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Raven" | | 6 | "Nest" | | 7 | "Tomás" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Europe" |
| | globalScore | 0.908 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like the service entrance of a cel" | | 1 | "tasted like burnt sugar and iron" | | 2 | "looked like ink, but shimmered faintly, l" |
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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 | 962 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 122 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 20.04 | | std | 17.1 | | cv | 0.853 | | sampleLengths | | 0 | 57 | | 1 | 58 | | 2 | 54 | | 3 | 64 | | 4 | 48 | | 5 | 37 | | 6 | 9 | | 7 | 39 | | 8 | 12 | | 9 | 5 | | 10 | 2 | | 11 | 2 | | 12 | 5 | | 13 | 11 | | 14 | 21 | | 15 | 16 | | 16 | 20 | | 17 | 22 | | 18 | 40 | | 19 | 27 | | 20 | 11 | | 21 | 9 | | 22 | 7 | | 23 | 63 | | 24 | 29 | | 25 | 16 | | 26 | 8 | | 27 | 6 | | 28 | 8 | | 29 | 35 | | 30 | 8 | | 31 | 17 | | 32 | 15 | | 33 | 25 | | 34 | 9 | | 35 | 7 | | 36 | 4 | | 37 | 10 | | 38 | 18 | | 39 | 12 | | 40 | 11 | | 41 | 5 | | 42 | 6 | | 43 | 26 | | 44 | 20 | | 45 | 11 | | 46 | 13 | | 47 | 4 |
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| 98.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 108 | | matches | | 0 | "were lined" | | 1 | "being torn" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 134 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 122 | | ratio | 0.082 | | matches | | 0 | "She kept her eyes locked on the shadow ahead—six foot something, black hoodie, jeans clinging to his legs." | | 1 | "The suspect—tall, lean, hands shoved deep in his pockets—ducked into a narrow alley." | | 2 | "Then a flicker—a hood disappearing down a rusted metal staircase that descended into darkness." | | 3 | "The beam cut through the dark—brick walls slick with moisture, graffiti in shifting languages, and at the very bottom, a faint green glow pulsing like a heartbeat." | | 4 | "The green glow dilated—no longer a glow, but a sign." | | 5 | "Beyond lay a corridor—too clean for a cellar, too narrow for a tunnel." | | 6 | "Black-and-white photographs of people she couldn’t place—some dressed in Edwardian suits, others in modern gear—all stared at her with the same hollow eyes." | | 7 | "The air was thick with the scent of damp wool, ozone, and something older—like wet stone and old blood." | | 8 | "Then from below—a sound like wet silk being torn." | | 9 | "The sound of something heavy breathing filled the air—not from the stairs, not from the corridor." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 860 | | adjectiveStacks | 2 | | stackExamples | | 0 | "suspect—tall, lean, hands" | | 1 | "Short curly dark hair." |
| | adverbCount | 34 | | adverbRatio | 0.03953488372093023 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.009302325581395349 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 122 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 122 | | mean | 7.89 | | std | 6.31 | | cv | 0.8 | | sampleLengths | | 0 | 18 | | 1 | 15 | | 2 | 24 | | 3 | 18 | | 4 | 9 | | 5 | 4 | | 6 | 2 | | 7 | 3 | | 8 | 3 | | 9 | 19 | | 10 | 13 | | 11 | 4 | | 12 | 2 | | 13 | 9 | | 14 | 4 | | 15 | 22 | | 16 | 13 | | 17 | 18 | | 18 | 15 | | 19 | 4 | | 20 | 14 | | 21 | 5 | | 22 | 28 | | 23 | 3 | | 24 | 2 | | 25 | 10 | | 26 | 10 | | 27 | 27 | | 28 | 2 | | 29 | 4 | | 30 | 3 | | 31 | 2 | | 32 | 22 | | 33 | 3 | | 34 | 4 | | 35 | 8 | | 36 | 12 | | 37 | 5 | | 38 | 2 | | 39 | 2 | | 40 | 5 | | 41 | 8 | | 42 | 3 | | 43 | 7 | | 44 | 14 | | 45 | 7 | | 46 | 9 | | 47 | 7 | | 48 | 13 | | 49 | 12 |
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| 36.61% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.30327868852459017 | | totalSentences | 122 | | uniqueOpeners | 37 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 90 | | matches | | 0 | "Maybe someone else." | | 1 | "Then a flicker—a hood disappearing" | | 2 | "Just a black door with" | | 3 | "Then from below—a sound like" | | 4 | "Then it winked out." |
| | ratio | 0.056 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 90 | | matches | | 0 | "She kept her eyes locked" | | 1 | "He wasn’t running like he" | | 2 | "He was leading someone." | | 3 | "She adjusted the strap of" | | 4 | "She clipped the raindrops from" | | 5 | "She slid between two buildings," | | 6 | "She pulled her torch from" | | 7 | "She didn’t lower the torch." | | 8 | "She stepped onto the first" | | 9 | "It groaned under her weight," | | 10 | "She paused at the bottom." | | 11 | "She pushed the door." | | 12 | "She heard footsteps above." | | 13 | "She looked up." | | 14 | "She gripped the railing." | | 15 | "His medallion was warm too." | | 16 | "It curled around her ankles" | | 17 | "His face wasn’t visible in" | | 18 | "he said, calm, almost amused" | | 19 | "His voice dropped." |
| | ratio | 0.256 | |
| 82.22% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 90 | | matches | | 0 | "The rain came down in" | | 1 | "Neon signs bled pink and" | | 2 | "Detective Harlow Quinn moved against" | | 3 | "She kept her eyes locked" | | 4 | "He wasn’t running like he" | | 5 | "He was leading someone." | | 6 | "Quinn’s jaw tightened." | | 7 | "She adjusted the strap of" | | 8 | "The suspect—tall, lean, hands shoved" | | 9 | "A common evasion against pursuers" | | 10 | "Quinn didn’t break stride." | | 11 | "She clipped the raindrops from" | | 12 | "She slid between two buildings," | | 13 | "The alley smelled of fried" | | 14 | "Quinn paused at the top." | | 15 | "The staircase spiraled down into" | | 16 | "She pulled her torch from" | | 17 | "The beam cut through the" | | 18 | "A man in a worn" | | 19 | "A Saint Christopher medallion glinted" |
| | ratio | 0.756 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 90 | | matches | (empty) | | ratio | 0 | |
| 99.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 2 | | matches | | 0 | "Detective Harlow Quinn moved against the current, her breath steady, boots splashing through puddles that pooled in the cracks of the old London cobblestones." | | 1 | "Then a flicker—a hood disappearing down a rusted metal staircase that descended into darkness." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 22 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0.125 | | effectiveRatio | 0.091 | |