| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1039 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 32.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1039 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "pulse" | | 1 | "tension" | | 2 | "flicked" | | 3 | "dancing" | | 4 | "echoed" | | 5 | "footsteps" | | 6 | "glinting" | | 7 | "echoing" | | 8 | "whisper" | | 9 | "weight" |
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| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
| | 2 | | label | "sent a shiver through" | | count | 1 |
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| | highlights | | 0 | "eyes widened" | | 1 | "The air was thick with" | | 2 | "sent a shiver down" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 88 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 88 | | filterMatches | (empty) | | hedgeMatches | | 0 | "happened 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 | 111 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 7 | | markdownWords | 19 | | totalWords | 1030 | | ratio | 0.018 | | matches | | 0 | "\"You’re bleeding.\"" | | 1 | "\"You always were a quick one.\"" | | 2 | "if that’s what he was" | | 3 | "\"You’re too late.\"" | | 4 | "they" | | 5 | "twitch" | | 6 | "him" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 44.44% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 900 | | uniqueNames | 5 | | maxNameDensity | 2.11 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 19 | | Herrera | 1 | | Tomás | 13 | | Morris | 1 | | Silas | 5 |
| | persons | | 0 | "Quinn" | | 1 | "Herrera" | | 2 | "Tomás" | | 3 | "Morris" | | 4 | "Silas" |
| | places | (empty) | | globalScore | 0.444 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 1 | | matches | | 0 | "something like damp earth and rotting leaves" |
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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 | 1030 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 111 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 21.46 | | std | 15.78 | | cv | 0.735 | | sampleLengths | | 0 | 1 | | 1 | 60 | | 2 | 2 | | 3 | 35 | | 4 | 15 | | 5 | 11 | | 6 | 53 | | 7 | 51 | | 8 | 42 | | 9 | 3 | | 10 | 11 | | 11 | 1 | | 12 | 42 | | 13 | 15 | | 14 | 15 | | 15 | 35 | | 16 | 24 | | 17 | 24 | | 18 | 8 | | 19 | 38 | | 20 | 13 | | 21 | 52 | | 22 | 33 | | 23 | 13 | | 24 | 18 | | 25 | 23 | | 26 | 30 | | 27 | 7 | | 28 | 36 | | 29 | 16 | | 30 | 8 | | 31 | 7 | | 32 | 5 | | 33 | 18 | | 34 | 15 | | 35 | 15 | | 36 | 47 | | 37 | 22 | | 38 | 32 | | 39 | 5 | | 40 | 6 | | 41 | 44 | | 42 | 6 | | 43 | 16 | | 44 | 14 | | 45 | 11 | | 46 | 27 | | 47 | 5 |
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| 97.29% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 88 | | matches | | 0 | "being dragged" | | 1 | "being ripped" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 156 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 111 | | ratio | 0.063 | | matches | | 0 | "The suspect—*if that’s what he was*—had vanished into the crowd." | | 1 | "A sound cut through the night—a wet, guttural groan, like something being dragged across pavement." | | 2 | "The air was thick with the scent of damp earth and something else—something sharp and chemical, like alchemical residue." | | 3 | "A distant sound echoed through the tunnel—footsteps, heavy and deliberate." | | 4 | "The first figure emerged from the shadows—a man in a long, tattered coat, his face obscured by a hood." | | 5 | "A sound cut through the air—a wet, tearing noise, like fabric being ripped." | | 6 | "The stairs were slick with rain and something else—something darker, something that clung to her boots like tar." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 911 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.014270032930845226 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0043907793633369925 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 111 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 111 | | mean | 9.26 | | std | 5.51 | | cv | 0.595 | | sampleLengths | | 0 | 16 | | 1 | 22 | | 2 | 19 | | 3 | 3 | | 4 | 2 | | 5 | 14 | | 6 | 3 | | 7 | 4 | | 8 | 14 | | 9 | 15 | | 10 | 5 | | 11 | 6 | | 12 | 14 | | 13 | 20 | | 14 | 10 | | 15 | 7 | | 16 | 2 | | 17 | 9 | | 18 | 23 | | 19 | 5 | | 20 | 14 | | 21 | 15 | | 22 | 3 | | 23 | 12 | | 24 | 12 | | 25 | 3 | | 26 | 11 | | 27 | 12 | | 28 | 14 | | 29 | 16 | | 30 | 8 | | 31 | 7 | | 32 | 3 | | 33 | 9 | | 34 | 3 | | 35 | 15 | | 36 | 15 | | 37 | 5 | | 38 | 6 | | 39 | 13 | | 40 | 5 | | 41 | 10 | | 42 | 8 | | 43 | 6 | | 44 | 8 | | 45 | 15 | | 46 | 11 | | 47 | 12 | | 48 | 3 | | 49 | 8 |
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| 47.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.23423423423423423 | | totalSentences | 111 | | uniqueOpeners | 26 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 85 | | matches | | 0 | "She didn’t slow." | | 1 | "She knew that voice." | | 2 | "she said, her breath fogging" | | 3 | "She ducked under a sagging" | | 4 | "She pressed forward, her pulse" | | 5 | "She lunged, her fingers closing" | | 6 | "His olive skin was slick" | | 7 | "His gaze flicked over her" | | 8 | "He shoved past her, his" | | 9 | "They turned a corner, and" | | 10 | "He grabbed Quinn’s arm and" | | 11 | "She didn’t argue." | | 12 | "He pressed her against the" | | 13 | "She didn’t have time." | | 14 | "She wrenched her arm free" | | 15 | "His eyes gleamed with something" | | 16 | "He raised a hand, and" | | 17 | "She fired, the shot echoing" | | 18 | "He grabbed Quinn’s arm and" | | 19 | "She didn’t argue." |
| | ratio | 0.259 | |
| 1.18% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 85 | | matches | | 0 | "The alley stank of wet" | | 1 | "Quinn’s boots splashed through a" | | 2 | "The neon glow of a" | | 3 | "She didn’t slow." | | 4 | "The voice came from behind" | | 5 | "Quinn didn’t turn." | | 6 | "She knew that voice." | | 7 | "she said, her breath fogging" | | 8 | "A laugh, sharp and wet." | | 9 | "She ducked under a sagging" | | 10 | "The alley opened into a" | | 11 | "The suspect—*if that’s what he" | | 12 | "She pressed forward, her pulse" | | 13 | "The city was a labyrinth" | | 14 | "The air hummed with an" | | 15 | "A figure moved ahead of" | | 16 | "Quinn didn’t hesitate." | | 17 | "She lunged, her fingers closing" | | 18 | "The fabric tore as she" | | 19 | "Detective Quinn froze." |
| | ratio | 0.918 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 82.07% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 47 | | technicalSentenceCount | 4 | | matches | | 0 | "At the bottom, the tunnel stretched before them, its walls lined with flickering gas lamps that cast long, dancing shadows." | | 1 | "Silas chuckled, a sound that sent a shiver down Quinn’s spine." | | 2 | "The tunnel was alive with movement now, figures emerging from the dark, their eyes glowing with an unnatural light." | | 3 | "The stairs were slick with rain and something else—something darker, something that clung to her boots like tar." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 3 | | matches | | 0 | "she said, her breath fogging in the frigid air" | | 1 | "Quinn said, her grip loosening" | | 2 | "Silas said, his voice smooth as oil" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |