| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.241 | | leniency | 0.483 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1629 | | 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) | |
| 81.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1629 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "charged" | | 1 | "velvet" | | 2 | "etched" | | 3 | "porcelain" | | 4 | "pulsed" | | 5 | "warmth" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 194 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 194 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 216 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1629 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 29.28% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1491 | | uniqueNames | 12 | | maxNameDensity | 2.41 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 2 | | Harlow | 1 | | Quinn | 36 | | Frith | 1 | | Street | 1 | | Underground | 1 | | Tube | 1 | | Camden | 1 | | Morris | 1 | | Veil | 1 | | Market | 1 | | One | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Market" |
| | places | | 0 | "Soho" | | 1 | "Frith" | | 2 | "Street" | | 3 | "Veil" | | 4 | "One" |
| | globalScore | 0.293 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 122 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a finger bone, though it had" |
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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 | 1629 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 216 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 128 | | mean | 12.73 | | std | 12.55 | | cv | 0.986 | | sampleLengths | | 0 | 13 | | 1 | 32 | | 2 | 1 | | 3 | 4 | | 4 | 38 | | 5 | 4 | | 6 | 54 | | 7 | 25 | | 8 | 38 | | 9 | 10 | | 10 | 20 | | 11 | 5 | | 12 | 5 | | 13 | 7 | | 14 | 10 | | 15 | 54 | | 16 | 10 | | 17 | 12 | | 18 | 18 | | 19 | 6 | | 20 | 2 | | 21 | 17 | | 22 | 19 | | 23 | 24 | | 24 | 21 | | 25 | 5 | | 26 | 4 | | 27 | 11 | | 28 | 6 | | 29 | 6 | | 30 | 35 | | 31 | 6 | | 32 | 6 | | 33 | 3 | | 34 | 5 | | 35 | 36 | | 36 | 4 | | 37 | 7 | | 38 | 2 | | 39 | 10 | | 40 | 27 | | 41 | 49 | | 42 | 14 | | 43 | 17 | | 44 | 5 | | 45 | 6 | | 46 | 46 | | 47 | 6 | | 48 | 54 | | 49 | 6 |
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| 99.84% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 194 | | matches | | 0 | "been carved" | | 1 | "been painted" | | 2 | "been scratched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 268 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 216 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1493 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.022103148024112524 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0020093770931011385 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 216 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 216 | | mean | 7.54 | | std | 4.72 | | cv | 0.626 | | sampleLengths | | 0 | 13 | | 1 | 16 | | 2 | 2 | | 3 | 2 | | 4 | 12 | | 5 | 1 | | 6 | 4 | | 7 | 2 | | 8 | 1 | | 9 | 6 | | 10 | 16 | | 11 | 13 | | 12 | 4 | | 13 | 9 | | 14 | 24 | | 15 | 21 | | 16 | 14 | | 17 | 6 | | 18 | 5 | | 19 | 10 | | 20 | 6 | | 21 | 22 | | 22 | 10 | | 23 | 5 | | 24 | 2 | | 25 | 13 | | 26 | 5 | | 27 | 5 | | 28 | 7 | | 29 | 4 | | 30 | 6 | | 31 | 10 | | 32 | 9 | | 33 | 13 | | 34 | 10 | | 35 | 12 | | 36 | 10 | | 37 | 4 | | 38 | 2 | | 39 | 6 | | 40 | 18 | | 41 | 6 | | 42 | 2 | | 43 | 4 | | 44 | 13 | | 45 | 11 | | 46 | 2 | | 47 | 2 | | 48 | 3 | | 49 | 1 |
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| 56.02% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.375 | | totalSentences | 216 | | uniqueOpeners | 81 | |
| 78.43% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 170 | | matches | | 0 | "Somewhere far beneath the street," | | 1 | "Then something sweeter reached her." | | 2 | "Even the thing beneath the" | | 3 | "Then she stepped past the" |
| | ratio | 0.024 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 170 | | matches | | 0 | "She saw Quinn’s badge, saw" | | 1 | "Her boots struck water and" | | 2 | "She pushed through a knot" | | 3 | "They always made the same" | | 4 | "They treated panic as speed." | | 5 | "Her knee hit the ground." | | 6 | "She rolled through it, rose," | | 7 | "It had no handle." | | 8 | "Her left wristwatch ticked beneath" | | 9 | "She checked the time, then" | | 10 | "She crouched and picked it" | | 11 | "It felt warm in her" | | 12 | "She drew her pistol." | | 13 | "She kept her pistol angled" | | 14 | "It streaked the stairs in" | | 15 | "Its face sagged around a" | | 16 | "Its nostrils widened." | | 17 | "She caught his wrist and" | | 18 | "She slammed against a pillar," | | 19 | "They moved through the crowd" |
| | ratio | 0.147 | |
| 45.29% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 141 | | totalSentences | 170 | | matches | | 0 | "Detective Harlow Quinn caught one" | | 1 | "A flash of pale fingers" | | 2 | "The figure looked back." | | 3 | "Blood ran from one nostril" | | 4 | "She saw Quinn’s badge, saw" | | 5 | "Quinn launched after her." | | 6 | "Her boots struck water and" | | 7 | "She pushed through a knot" | | 8 | "The woman ran with a" | | 9 | "Quinn had spent eighteen years" | | 10 | "They always made the same" | | 11 | "They treated panic as speed." | | 12 | "The woman cut down a" | | 13 | "Quinn followed, shoulder grazing wet" | | 14 | "Quinn planted one hand on" | | 15 | "Her knee hit the ground." | | 16 | "She rolled through it, rose," | | 17 | "The woman glanced back again." | | 18 | "This time, fear broke across" | | 19 | "Fear of what waited behind" |
| | ratio | 0.829 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 170 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 62 | | technicalSentenceCount | 2 | | matches | | 0 | "The woman ran with a limp that worsened each time her left foot hit the ground, but she kept her lead." | | 1 | "Quinn had spent eighteen years chasing people who believed the city belonged to them." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 46.55% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 3 | | fancyTags | | 0 | "he croaked (croak)" | | 1 | "it murmured (murmur)" | | 2 | "the woman whispered (whisper)" |
| | dialogueSentences | 29 | | tagDensity | 0.207 | | leniency | 0.414 | | rawRatio | 0.5 | | effectiveRatio | 0.207 | |