| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 23 | | tagDensity | 0.522 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.95% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1234 | | 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 | 1234 | | totalAiIsms | 30 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | |
| | highlights | | 0 | "glistening" | | 1 | "raced" | | 2 | "pounding" | | 3 | "echo" | | 4 | "footsteps" | | 5 | "calculating" | | 6 | "sinister" | | 7 | "flickered" | | 8 | "navigated" | | 9 | "echoed" | | 10 | "whisper" | | 11 | "glint" | | 12 | "oppressive" | | 13 | "loomed" | | 14 | "glinting" | | 15 | "stark" | | 16 | "scanning" | | 17 | "weight" | | 18 | "pulsed" | | 19 | "resolve" | | 20 | "etched" | | 21 | "cacophony" | | 22 | "stomach" |
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| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
| | 2 | | label | "weight of words/silence" | | count | 1 |
|
| | highlights | | 0 | "stomach dropped" | | 1 | "The air was thick with" | | 2 | "the weight of his words" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 85 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 85 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1227 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 88.21% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 1052 | | uniqueNames | 9 | | maxNameDensity | 1.24 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 13 | | Soho | 1 | | Veil | 1 | | Market | 1 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Tomás" |
| | places | | | globalScore | 0.882 | | windowScore | 1 | |
| 83.33% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 75 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a world away" | | 1 | "as if sensing her presence" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1227 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 96 | | matches | | |
| 99.76% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 33.16 | | std | 16.55 | | cv | 0.499 | | sampleLengths | | 0 | 63 | | 1 | 40 | | 2 | 50 | | 3 | 50 | | 4 | 59 | | 5 | 51 | | 6 | 48 | | 7 | 14 | | 8 | 45 | | 9 | 49 | | 10 | 71 | | 11 | 49 | | 12 | 12 | | 13 | 48 | | 14 | 14 | | 15 | 21 | | 16 | 17 | | 17 | 28 | | 18 | 18 | | 19 | 42 | | 20 | 35 | | 21 | 9 | | 22 | 22 | | 23 | 11 | | 24 | 31 | | 25 | 47 | | 26 | 28 | | 27 | 42 | | 28 | 30 | | 29 | 34 | | 30 | 15 | | 31 | 35 | | 32 | 14 | | 33 | 32 | | 34 | 5 | | 35 | 20 | | 36 | 28 |
| |
| 97.01% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 85 | | matches | | 0 | "were bought" | | 1 | "was lost" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 187 | | matches | | 0 | "was slipping" | | 1 | "was fumbling" |
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| 83.33% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 96 | | ratio | 0.021 | | matches | | 0 | "The suspect was a small-time dealer, but he had connections—dangerous ones." | | 1 | "The suspect had vanished into the throng, and she had to decide—follow him deeper into this unknown territory or retreat to the safety of the surface." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1058 | | adjectiveStacks | 1 | | stackExamples | | 0 | "former paramedic turned underground medic," |
| | adverbCount | 33 | | adverbRatio | 0.031190926275992438 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004725897920604915 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 12.78 | | std | 5.97 | | cv | 0.467 | | sampleLengths | | 0 | 14 | | 1 | 16 | | 2 | 12 | | 3 | 21 | | 4 | 9 | | 5 | 31 | | 6 | 8 | | 7 | 6 | | 8 | 11 | | 9 | 20 | | 10 | 5 | | 11 | 16 | | 12 | 22 | | 13 | 12 | | 14 | 17 | | 15 | 17 | | 16 | 9 | | 17 | 16 | | 18 | 12 | | 19 | 18 | | 20 | 14 | | 21 | 7 | | 22 | 13 | | 23 | 18 | | 24 | 17 | | 25 | 14 | | 26 | 19 | | 27 | 7 | | 28 | 19 | | 29 | 23 | | 30 | 3 | | 31 | 23 | | 32 | 11 | | 33 | 21 | | 34 | 12 | | 35 | 27 | | 36 | 3 | | 37 | 5 | | 38 | 15 | | 39 | 26 | | 40 | 9 | | 41 | 3 | | 42 | 14 | | 43 | 17 | | 44 | 17 | | 45 | 12 | | 46 | 2 | | 47 | 9 | | 48 | 12 | | 49 | 7 |
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| 52.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.3333333333333333 | | totalSentences | 96 | | uniqueOpeners | 32 | |
| 39.68% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 84 | | matches | | 0 | "Then he turned and bolted" |
| | ratio | 0.012 | |
| 77.14% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 84 | | matches | | 0 | "she shouted, her voice swallowed" | | 1 | "She had to close the" | | 2 | "She couldn't let that happen." | | 3 | "They rounded another corner, and" | | 4 | "She skidded to a halt," | | 5 | "She hesitated, glancing back at" | | 6 | "She could hear him ahead," | | 7 | "she muttered under her breath," | | 8 | "He was fumbling with something" | | 9 | "she barked, raising her badge," | | 10 | "He froze, eyes darting, and" | | 11 | "She followed, her feet pounding" | | 12 | "She had heard whispers of" | | 13 | "She had crossed into a" | | 14 | "She turned, her gaze locking" | | 15 | "He wore a Saint Christopher" | | 16 | "she replied, her voice steady" | | 17 | "He pushed off the stall," | | 18 | "she said, scanning the crowd" | | 19 | "He leaned in, lowering his" |
| | ratio | 0.357 | |
| 25.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 84 | | matches | | 0 | "The suspect darted around the" | | 1 | "Detective Harlow Quinn's heart raced" | | 2 | "The rain pelted down, drenching" | | 3 | "The world around her faded," | | 4 | "she shouted, her voice swallowed" | | 5 | "The figure ahead glanced back," | | 6 | "Quinn's mind raced, calculating the" | | 7 | "She had to close the" | | 8 | "The suspect was a small-time" | | 9 | "She couldn't let that happen." | | 10 | "They rounded another corner, and" | | 11 | "Quinn seized the moment, lunging" | | 12 | "She skidded to a halt," | | 13 | "The alley was dark, the" | | 14 | "She hesitated, glancing back at" | | 15 | "The laughter and music felt" | | 16 | "The alley twisted and turned," | | 17 | "The sound of her footsteps" | | 18 | "She could hear him ahead," | | 19 | "she muttered under her breath," |
| | ratio | 0.869 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 84 | | matches | | 0 | "If he slipped away now," | | 1 | "Before she could respond, a" |
| | ratio | 0.024 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 4 | | matches | | 0 | "He was fumbling with something in his hands, glancing over his shoulder as if sensing her presence." | | 1 | "She followed, her feet pounding against the concrete steps, the air growing colder and more oppressive with each descent." | | 2 | "The market pulsed with energy, a living entity that thrived on secrets and shadows." | | 3 | "Quinn followed, weaving through the crowd, her heart pounding in her chest." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 6 | | matches | | 0 | "she muttered, her voice barely a whisper" | | 1 | "she replied, her voice steady despite the unease creeping in" | | 2 | "she pressed, her eyes narrowing" | | 3 | "he said, his tone serious" | | 4 | "she shouted, but her voice was lost in the cacophony" | | 5 | "the man said, his voice smooth and menacing" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 6 | | fancyTags | | 0 | "she shouted (shout)" | | 1 | "she muttered (mutter)" | | 2 | "she barked (bark)" | | 3 | "she pressed (press)" | | 4 | "she shouted (shout)" | | 5 | "she yelled (yell)" |
| | dialogueSentences | 23 | | tagDensity | 0.435 | | leniency | 0.87 | | rawRatio | 0.6 | | effectiveRatio | 0.522 | |