| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 3 | | adverbTags | | 0 | "Tomás said simply [simply]" | | 1 | "He looked away [away]" | | 2 | "a voice rasped like [like]" |
| | dialogueSentences | 25 | | tagDensity | 0.32 | | leniency | 0.64 | | rawRatio | 0.375 | | effectiveRatio | 0.24 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1098 | | 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) | |
| 40.80% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1098 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "symphony" | | 1 | "treacherous" | | 2 | "warmth" | | 3 | "chill" | | 4 | "gloom" | | 5 | "constructed" | | 6 | "tracing" | | 7 | "scanned" | | 8 | "glinting" | | 9 | "flicked" | | 10 | "velvet" | | 11 | "pulsed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "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 | 106 | | matches | (empty) | |
| 88.95% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 106 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 124 | | 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 | 2 | | markdownWords | 4 | | totalWords | 1097 | | ratio | 0.004 | | matches | | 0 | "Got you." | | 1 | "accidental discharge" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 904 | | uniqueNames | 15 | | maxNameDensity | 0.88 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Tomás" | | discoveredNames | | Harlow | 1 | | Quinn | 8 | | Met | 1 | | Berwick | 1 | | Street | 1 | | Morris | 2 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 1 | | Tomás | 5 | | Bone | 2 | | Yard | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Met" | | 3 | "Morris" | | 4 | "Market" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Herrera" | | 8 | "Tomás" |
| | places | | 0 | "Berwick" | | 1 | "Street" | | 2 | "Bone" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | glossingSentenceCount | 1 | | matches | | 0 | "luminescence that seemed to seep from the brickwork itself" |
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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 | 1097 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 124 | | matches | | 0 | "knew that smell" | | 1 | "moved, that required" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 24.38 | | std | 18.95 | | cv | 0.777 | | sampleLengths | | 0 | 23 | | 1 | 42 | | 2 | 2 | | 3 | 53 | | 4 | 2 | | 5 | 19 | | 6 | 64 | | 7 | 5 | | 8 | 16 | | 9 | 3 | | 10 | 30 | | 11 | 11 | | 12 | 63 | | 13 | 27 | | 14 | 3 | | 15 | 69 | | 16 | 48 | | 17 | 25 | | 18 | 54 | | 19 | 5 | | 20 | 57 | | 21 | 1 | | 22 | 31 | | 23 | 7 | | 24 | 18 | | 25 | 13 | | 26 | 41 | | 27 | 39 | | 28 | 5 | | 29 | 24 | | 30 | 17 | | 31 | 39 | | 32 | 8 | | 33 | 42 | | 34 | 12 | | 35 | 4 | | 36 | 6 | | 37 | 15 | | 38 | 15 | | 39 | 27 | | 40 | 41 | | 41 | 8 | | 42 | 26 | | 43 | 17 | | 44 | 20 |
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| 98.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 106 | | matches | | 0 | "was gone" | | 1 | "were obscured" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 152 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 124 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 555 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 4 | | adverbRatio | 0.007207207207207207 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0036036036036036037 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 124 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 124 | | mean | 8.85 | | std | 5.83 | | cv | 0.659 | | sampleLengths | | 0 | 17 | | 1 | 2 | | 2 | 4 | | 3 | 6 | | 4 | 14 | | 5 | 14 | | 6 | 8 | | 7 | 2 | | 8 | 15 | | 9 | 9 | | 10 | 18 | | 11 | 8 | | 12 | 3 | | 13 | 2 | | 14 | 5 | | 15 | 14 | | 16 | 5 | | 17 | 3 | | 18 | 9 | | 19 | 21 | | 20 | 4 | | 21 | 16 | | 22 | 6 | | 23 | 3 | | 24 | 2 | | 25 | 10 | | 26 | 6 | | 27 | 3 | | 28 | 5 | | 29 | 12 | | 30 | 6 | | 31 | 7 | | 32 | 8 | | 33 | 3 | | 34 | 8 | | 35 | 4 | | 36 | 20 | | 37 | 11 | | 38 | 20 | | 39 | 10 | | 40 | 8 | | 41 | 9 | | 42 | 3 | | 43 | 4 | | 44 | 3 | | 45 | 13 | | 46 | 15 | | 47 | 13 | | 48 | 21 | | 49 | 3 |
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| 54.84% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.3870967741935484 | | totalSentences | 124 | | uniqueOpeners | 48 | |
| 33.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 99 | | matches | | | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 99 | | matches | | 0 | "She vaulted the spilled rubbish," | | 1 | "It reached a rusted service" | | 2 | "She knew that smell." | | 3 | "It had lingered in the" | | 4 | "Her radio crackled." | | 5 | "She thumbed the button, her" | | 6 | "She went down." | | 7 | "She drew her torch, the" | | 8 | "She’d heard the whispers." | | 9 | "She scanned the crowd." | | 10 | "Her military bearing made her" | | 11 | "She forced herself to amble," | | 12 | "His file photo didn’t do" | | 13 | "He gestured with his chin" | | 14 | "His eyes flicked to her" | | 15 | "He pushed off the stall" | | 16 | "She kept her face a" | | 17 | "He looked away, his fingers" | | 18 | "She unclipped her badge, held" | | 19 | "She walked towards the Bone" |
| | ratio | 0.273 | |
| 25.66% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 86 | | totalSentences | 99 | | matches | | 0 | "The suspect’s shoulder clipped a" | | 1 | "A symphony of horns." | | 2 | "Detective Harlow Quinn didn’t break" | | 3 | "She vaulted the spilled rubbish," | | 4 | "The figure ahead, a blur" | | 5 | "Quinn followed, the rain-slick cobbles" | | 6 | "The air shifted from the" | | 7 | "The alley narrowed, a canyon" | | 8 | "A dead end." | | 9 | "It reached a rusted service" | | 10 | "Quinn skidded to a halt." | | 11 | "A maintenance hatch, hanging open" | | 12 | "A gust of damp, subterranean" | | 13 | "She knew that smell." | | 14 | "It had lingered in the" | | 15 | "Her radio crackled." | | 16 | "She thumbed the button, her" | | 17 | "The suspect was getting away." | | 18 | "The shaft led down a" | | 19 | "Quinn clipped the radio back" |
| | ratio | 0.869 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 99 | | matches | (empty) | | ratio | 0 | |
| 81.63% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 3 | | matches | | 0 | "A gust of damp, subterranean air washed over her, carrying a faint, coppery tang that had nothing to do with pipes." | | 1 | "The light from the alley faded, replaced by a faint, greenish luminescence that seemed to seep from the brickwork itself." | | 2 | "The known world of procedure and evidence, and this whispering, living darkness that had taken her partner." |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "He looked away, his fingers tracing his medallion" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 25 | | tagDensity | 0.08 | | leniency | 0.16 | | rawRatio | 0 | | effectiveRatio | 0 | |