| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "His voice carried easily [easily]" |
| | dialogueSentences | 30 | | tagDensity | 0.267 | | leniency | 0.533 | | rawRatio | 0.125 | | effectiveRatio | 0.067 | |
| 93.03% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1435 | | totalAiIsmAdverbs | 2 | | 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) | |
| 75.61% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1435 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "pounding" | | 1 | "familiar" | | 2 | "flickered" | | 3 | "silence" | | 4 | "velvet" | | 5 | "could feel" | | 6 | "shattered" |
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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 | 114 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 114 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 134 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1435 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 82.20% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 1180 | | uniqueNames | 14 | | maxNameDensity | 1.36 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 16 | | Soho | 2 | | Raven | 1 | | Nest | 1 | | Silas | 1 | | Thorne | 1 | | Camden | 1 | | Town | 1 | | Saint | 2 | | Christopher | 2 | | Morris | 2 | | Tomás | 1 | | Herrera | 3 | | English | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Thorne" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" | | 7 | "Tomás" | | 8 | "Herrera" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "Camden" | | 3 | "Town" |
| | globalScore | 0.822 | | windowScore | 1 | |
| 44.37% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 3 | | matches | | 0 | "appeared, thin as a razor cut, and a section of the tiled surface swung inward on hidden hinges" | | 1 | "felt like the kind of mistake you only" | | 2 | "something between a souk and a fever dream" |
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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 | 1435 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 134 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 28.7 | | std | 23.43 | | cv | 0.816 | | sampleLengths | | 0 | 51 | | 1 | 2 | | 2 | 40 | | 3 | 62 | | 4 | 69 | | 5 | 2 | | 6 | 63 | | 7 | 8 | | 8 | 26 | | 9 | 8 | | 10 | 4 | | 11 | 73 | | 12 | 50 | | 13 | 22 | | 14 | 24 | | 15 | 6 | | 16 | 48 | | 17 | 4 | | 18 | 30 | | 19 | 15 | | 20 | 64 | | 21 | 3 | | 22 | 58 | | 23 | 12 | | 24 | 22 | | 25 | 5 | | 26 | 9 | | 27 | 66 | | 28 | 85 | | 29 | 7 | | 30 | 39 | | 31 | 43 | | 32 | 3 | | 33 | 62 | | 34 | 9 | | 35 | 37 | | 36 | 4 | | 37 | 26 | | 38 | 5 | | 39 | 19 | | 40 | 41 | | 41 | 22 | | 42 | 5 | | 43 | 49 | | 44 | 16 | | 45 | 21 | | 46 | 39 | | 47 | 47 | | 48 | 3 | | 49 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 114 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 193 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 134 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1185 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 41 | | adverbRatio | 0.03459915611814346 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.008438818565400843 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 134 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 134 | | mean | 10.71 | | std | 8.69 | | cv | 0.812 | | sampleLengths | | 0 | 21 | | 1 | 2 | | 2 | 1 | | 3 | 27 | | 4 | 2 | | 5 | 6 | | 6 | 4 | | 7 | 30 | | 8 | 6 | | 9 | 14 | | 10 | 1 | | 11 | 1 | | 12 | 13 | | 13 | 14 | | 14 | 13 | | 15 | 6 | | 16 | 14 | | 17 | 7 | | 18 | 28 | | 19 | 14 | | 20 | 2 | | 21 | 23 | | 22 | 40 | | 23 | 8 | | 24 | 6 | | 25 | 3 | | 26 | 3 | | 27 | 14 | | 28 | 8 | | 29 | 4 | | 30 | 18 | | 31 | 2 | | 32 | 10 | | 33 | 12 | | 34 | 3 | | 35 | 5 | | 36 | 15 | | 37 | 8 | | 38 | 5 | | 39 | 4 | | 40 | 36 | | 41 | 5 | | 42 | 8 | | 43 | 10 | | 44 | 4 | | 45 | 24 | | 46 | 4 | | 47 | 1 | | 48 | 1 | | 49 | 3 |
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| 72.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.47761194029850745 | | totalSentences | 134 | | uniqueOpeners | 64 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 93 | | matches | | 0 | "Of course they did." | | 1 | "Dark curly hair plastered to" | | 2 | "Too steady for someone who" | | 3 | "Somewhere behind her, a stall" |
| | ratio | 0.043 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 93 | | matches | | 0 | "Her lungs burned against the" | | 1 | "Her wrist ached where she'd" | | 2 | "They burst out onto a" | | 3 | "She was already gone." | | 4 | "He was young." | | 5 | "She had been building a" | | 6 | "She still didn't have an" | | 7 | "She stopped three steps from" | | 8 | "She had seen things." | | 9 | "He looked up as if" | | 10 | "Their eyes met across the" | | 11 | "He already knew what she" | | 12 | "She became aware of a" | | 13 | "He didn't answer." | | 14 | "He was already gone, melting" | | 15 | "His voice carried easily, an" | | 16 | "He lifted a folded cloth" | | 17 | "She stopped it." |
| | ratio | 0.194 | |
| 40.65% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 93 | | matches | | 0 | "The runner took the corner" | | 1 | "Her lungs burned against the" | | 2 | "The words disappeared into the" | | 3 | "Nobody in Soho stopped for" | | 4 | "The runner ducked into an" | | 5 | "Quinn followed, feet pounding through" | | 6 | "Her wrist ached where she'd" | | 7 | "The runner vaulted a low" | | 8 | "Quinn scrambled over after him," | | 9 | "They burst out onto a" | | 10 | "The neon from The Raven's" | | 11 | "Anyone who knew Silas Thorne" | | 12 | "The runner cut hard right," | | 13 | "Quinn sprinted after him, badge" | | 14 | "The attendant blinked at the" | | 15 | "Quinn wanted to reach across" | | 16 | "She was already gone." | | 17 | "The platform stretched out in" | | 18 | "The board said last service" | | 19 | "The runner stood at the" |
| | ratio | 0.839 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 93 | | matches | (empty) | | ratio | 0 | |
| 43.19% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 6 | | matches | | 0 | "Quinn followed, feet pounding through puddles that splashed her trousers up to the knees." | | 1 | "Anyone who knew Silas Thorne would have a tab and a hiding spot there." | | 2 | "The runner cut hard right, dodging a taxi that blared its horn, and plunged down the steps of the Camden Town tube station." | | 3 | "Quinn sprinted after him, badge already in her hand, and thrust it at the attendant who looked up from his newspaper with the bored expression of a man who had …" | | 4 | "Back before they had found him in that warehouse, perfectly unmarked, perfectly drained, with an expression on his face that said he had seen something he could…" | | 5 | "Skulls of indeterminate origin sat on display alongside stoppered bottles of powder, hand-stitched journals, and daggers that hummed at frequencies Quinn could …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 83.33% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn laughed (laugh)" | | 1 | "he muttered (mutter)" |
| | dialogueSentences | 30 | | tagDensity | 0.133 | | leniency | 0.267 | | rawRatio | 0.5 | | effectiveRatio | 0.133 | |