| 88.89% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 2 | | adverbTags | | 0 | "Miller stepped back [back]" | | 1 | "Quinn said flatly [flatly]" |
| | dialogueSentences | 36 | | tagDensity | 0.417 | | leniency | 0.833 | | rawRatio | 0.133 | | effectiveRatio | 0.111 | |
| 72.63% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1096 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "sharply" | | 1 | "completely" | | 2 | "nervously" | | 3 | "precisely" | | 4 | "softly" | | 5 | "slowly" |
| |
| 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) | |
| 27.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1096 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "shattered" | | 1 | "pumping" | | 2 | "navigate" | | 3 | "gloom" | | 4 | "silk" | | 5 | "velvet" | | 6 | "chill" | | 7 | "intricate" | | 8 | "etched" | | 9 | "vibrated" | | 10 | "magnetic" | | 11 | "wavering" | | 12 | "glistening" | | 13 | "shimmered" | | 14 | "echoed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 67 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 67 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 88 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1096 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 62.69% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 859 | | uniqueNames | 8 | | maxNameDensity | 1.75 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 15 | | Miller | 11 | | Victorian | 2 | | Rotherhithe | 1 | | Morris | 1 | | White | 1 | | Glock | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Miller" | | 3 | "Victorian" | | 4 | "Rotherhithe" | | 5 | "Morris" |
| | places | (empty) | | globalScore | 0.627 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1096 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 88 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 24.36 | | std | 16.18 | | cv | 0.664 | | sampleLengths | | 0 | 23 | | 1 | 31 | | 2 | 41 | | 3 | 45 | | 4 | 30 | | 5 | 19 | | 6 | 30 | | 7 | 10 | | 8 | 48 | | 9 | 23 | | 10 | 11 | | 11 | 24 | | 12 | 21 | | 13 | 9 | | 14 | 10 | | 15 | 50 | | 16 | 65 | | 17 | 13 | | 18 | 18 | | 19 | 55 | | 20 | 6 | | 21 | 1 | | 22 | 31 | | 23 | 9 | | 24 | 1 | | 25 | 60 | | 26 | 34 | | 27 | 16 | | 28 | 9 | | 29 | 8 | | 30 | 22 | | 31 | 7 | | 32 | 12 | | 33 | 27 | | 34 | 19 | | 35 | 23 | | 36 | 14 | | 37 | 39 | | 38 | 12 | | 39 | 16 | | 40 | 23 | | 41 | 31 | | 42 | 54 | | 43 | 39 | | 44 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 67 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 134 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 88 | | ratio | 0 | | matches | (empty) | |
| 76.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 863 | | adjectiveStacks | 4 | | stackExamples | | 0 | "icy cold against her" | | 1 | "delicate, jagged geometric paths." | | 2 | "rapid counter-clockwise turns," | | 3 | "same silk-lined pocket," |
| | adverbCount | 20 | | adverbRatio | 0.023174971031286212 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.011587485515643106 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 88 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 88 | | mean | 12.45 | | std | 6.24 | | cv | 0.501 | | sampleLengths | | 0 | 23 | | 1 | 18 | | 2 | 13 | | 3 | 31 | | 4 | 10 | | 5 | 9 | | 6 | 23 | | 7 | 13 | | 8 | 13 | | 9 | 17 | | 10 | 13 | | 11 | 6 | | 12 | 8 | | 13 | 22 | | 14 | 7 | | 15 | 3 | | 16 | 7 | | 17 | 24 | | 18 | 17 | | 19 | 13 | | 20 | 10 | | 21 | 11 | | 22 | 7 | | 23 | 17 | | 24 | 9 | | 25 | 5 | | 26 | 7 | | 27 | 9 | | 28 | 10 | | 29 | 12 | | 30 | 14 | | 31 | 11 | | 32 | 13 | | 33 | 7 | | 34 | 21 | | 35 | 14 | | 36 | 23 | | 37 | 13 | | 38 | 10 | | 39 | 8 | | 40 | 16 | | 41 | 12 | | 42 | 17 | | 43 | 10 | | 44 | 6 | | 45 | 1 | | 46 | 9 | | 47 | 8 | | 48 | 14 | | 49 | 9 |
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| 78.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.48863636363636365 | | totalSentences | 88 | | uniqueOpeners | 43 | |
| 51.28% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 65 | | matches | | 0 | "Dark, viscous liquid bubbled from" |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 65 | | matches | | 0 | "His expensive charcoal suit coat" | | 1 | "She leaned closer to the" | | 2 | "Her dark brown eyes narrowed." | | 3 | "She pinched the cloth of" | | 4 | "They formed sharp lines, radiating" | | 5 | "She reached into the dead" | | 6 | "Her fingers struck something heavy" | | 7 | "She drew out a small" | | 8 | "It did not point magnetic" | | 9 | "It spun three rapid counter-clockwise" | | 10 | "She walked slowly toward the" | | 11 | "She reached out a gloved" | | 12 | "It wore a heavy leather" |
| | ratio | 0.2 | |
| 13.85% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 65 | | matches | | 0 | "Detective Harlow Quinn ducked beneath" | | 1 | "Miller cursed behind her, his" | | 2 | "Quinn unbuttoned her damp wool" | | 3 | "The body lay contorted across" | | 4 | "The man's legs twisted sharply" | | 5 | "His expensive charcoal suit coat" | | 6 | "Miller said, shuffling closer and" | | 7 | "Quinn pulled a pair of" | | 8 | "Miller flashed his light upward" | | 9 | "The rusted shaft stretched twenty" | | 10 | "She leaned closer to the" | | 11 | "The man wore a bespoke" | | 12 | "A worn leather satchel lay" | | 13 | "Miller muttered, tapping his radio" | | 14 | "Miller swept his torch along" | | 15 | "The soot lay thick and" | | 16 | "Her dark brown eyes narrowed." | | 17 | "Quinn's voice cut like a" | | 18 | "She pinched the cloth of" | | 19 | "The shirt beneath was soaked" |
| | ratio | 0.892 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 4 | | matches | | 0 | "Detective Harlow Quinn ducked, her heavy boots crunching on wet shattered glass" | | 1 | "Miller stepped back, his hand resting on his leather holster" | | 2 | "Miller whispered, his boots skittering backward on the slick stone" | | 3 | "Quinn stood up, her military precision taking over her tall frame" |
| |
| 38.89% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 4 | | fancyTags | | 0 | "Miller muttered (mutter)" | | 1 | "Quinn pressed (press)" | | 2 | "Miller whispered (whisper)" | | 3 | "Miller choked (choke)" |
| | dialogueSentences | 36 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.444 | | effectiveRatio | 0.222 | |