| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said slowly [slowly]" |
| | dialogueSentences | 46 | | tagDensity | 0.326 | | leniency | 0.652 | | rawRatio | 0.067 | | effectiveRatio | 0.043 | |
| 94.10% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1695 | | 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) | |
| 79.35% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1695 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "fractured" | | 1 | "marble" | | 2 | "streaming" | | 3 | "familiar" | | 4 | "flickered" | | 5 | "could feel" | | 6 | "weight" |
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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 | 1 | | narrationSentences | 111 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 111 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 141 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1697 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 74.50% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 1192 | | uniqueNames | 17 | | maxNameDensity | 1.51 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Harlow | 1 | | Quinn | 18 | | November | 1 | | Tomás | 11 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | London | 4 | | Morris | 5 | | Whitechapel | 1 | | Soho | 1 | | Glock | 1 | | Tube | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Raven" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Tomás" | | 4 | "Herrera" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Morris" | | 8 | "Market" |
| | places | | 0 | "London" | | 1 | "Whitechapel" | | 2 | "Soho" |
| | globalScore | 0.745 | | windowScore | 0.833 | |
| 89.76% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like it hadn't been opened in deca" | | 1 | "sounds that seemed to twist in her ears before they reached her brain" |
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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 | 1697 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 141 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 61 | | mean | 27.82 | | std | 19.48 | | cv | 0.7 | | sampleLengths | | 0 | 43 | | 1 | 53 | | 2 | 82 | | 3 | 3 | | 4 | 42 | | 5 | 70 | | 6 | 38 | | 7 | 33 | | 8 | 20 | | 9 | 9 | | 10 | 50 | | 11 | 32 | | 12 | 39 | | 13 | 40 | | 14 | 24 | | 15 | 12 | | 16 | 5 | | 17 | 33 | | 18 | 21 | | 19 | 47 | | 20 | 37 | | 21 | 36 | | 22 | 44 | | 23 | 6 | | 24 | 9 | | 25 | 42 | | 26 | 9 | | 27 | 82 | | 28 | 37 | | 29 | 41 | | 30 | 18 | | 31 | 11 | | 32 | 36 | | 33 | 11 | | 34 | 26 | | 35 | 8 | | 36 | 2 | | 37 | 7 | | 38 | 38 | | 39 | 4 | | 40 | 50 | | 41 | 18 | | 42 | 2 | | 43 | 49 | | 44 | 30 | | 45 | 18 | | 46 | 2 | | 47 | 53 | | 48 | 31 | | 49 | 21 |
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| 92.62% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 111 | | matches | | 0 | "were plastered" | | 1 | "been opened" | | 2 | "was exhausted" | | 3 | "was swallowed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 213 | | matches | | 0 | "was trying" | | 1 | "was still waiting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 141 | | ratio | 0.007 | | matches | | 0 | "The smells grew stronger - incense and blood and something chemical that burned her nostrils." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1194 | | adjectiveStacks | 1 | | stackExamples | | 0 | "thick, pressing against her" |
| | adverbCount | 21 | | adverbRatio | 0.017587939698492462 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0041876046901172526 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 141 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 141 | | mean | 12.04 | | std | 7.91 | | cv | 0.657 | | sampleLengths | | 0 | 19 | | 1 | 24 | | 2 | 15 | | 3 | 14 | | 4 | 24 | | 5 | 8 | | 6 | 27 | | 7 | 18 | | 8 | 6 | | 9 | 3 | | 10 | 20 | | 11 | 3 | | 12 | 3 | | 13 | 19 | | 14 | 16 | | 15 | 4 | | 16 | 10 | | 17 | 15 | | 18 | 23 | | 19 | 4 | | 20 | 8 | | 21 | 10 | | 22 | 8 | | 23 | 11 | | 24 | 19 | | 25 | 12 | | 26 | 14 | | 27 | 7 | | 28 | 12 | | 29 | 8 | | 30 | 9 | | 31 | 15 | | 32 | 4 | | 33 | 7 | | 34 | 14 | | 35 | 10 | | 36 | 6 | | 37 | 2 | | 38 | 7 | | 39 | 17 | | 40 | 19 | | 41 | 20 | | 42 | 10 | | 43 | 9 | | 44 | 11 | | 45 | 10 | | 46 | 6 | | 47 | 18 | | 48 | 4 | | 49 | 8 |
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| 55.08% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.36879432624113473 | | totalSentences | 141 | | uniqueOpeners | 52 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 105 | | matches | (empty) | | ratio | 0 | |
| 82.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 105 | | matches | | 0 | "His dark curls were plastered" | | 1 | "He was the linchpin, the" | | 2 | "She'd seen the marks on" | | 3 | "He vaulted over a rusted" | | 4 | "His left arm, the one" | | 5 | "He didn't slow down." | | 6 | "She ripped it free and" | | 7 | "She was forty-one, eighteen years" | | 8 | "He knew these streets the" | | 9 | "She gained ground as he" | | 10 | "His arms windmilled, and he" | | 11 | "She closed the gap to" | | 12 | "His voice carried an accent" | | 13 | "She pushed harder, closing to" | | 14 | "He pulled something from his" | | 15 | "He pressed it to a" | | 16 | "He stood at the threshold," | | 17 | "Her hand went to the" | | 18 | "He laughed, but there was" | | 19 | "He vanished into the darkness." |
| | ratio | 0.343 | |
| 7.62% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 95 | | totalSentences | 105 | | matches | | 0 | "The rain hit the cobblestones" | | 1 | "Detective Harlow Quinn's boots slapped" | | 2 | "His dark curls were plastered" | | 3 | "The Saint Christopher medallion caught" | | 4 | "Quinn had been tracking him" | | 5 | "He was the linchpin, the" | | 6 | "The case file said cardiac" | | 7 | "Quinn knew better." | | 8 | "She'd seen the marks on" | | 9 | "Tomás didn't stop." | | 10 | "He vaulted over a rusted" | | 11 | "His left arm, the one" | | 12 | "He didn't slow down." | | 13 | "Quinn followed, her leather jacket" | | 14 | "She ripped it free and" | | 15 | "She was forty-one, eighteen years" | | 16 | "This was the world Morris" | | 17 | "The world Quinn had spent" | | 18 | "Tomás turned left, then right," | | 19 | "He knew these streets the" |
| | ratio | 0.905 | |
| 47.62% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 105 | | matches | | 0 | "To see what was really" |
| | ratio | 0.01 | |
| 67.67% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 6 | | matches | | 0 | "Three years ago, her partner DS Morris had died chasing leads that ended in a warehouse in Whitechapel." | | 1 | "She ripped it free and kept moving, her thighs burning as she pushed herself harder." | | 2 | "Quinn pushed forward, keeping him in sight, ignoring the stares that followed her." | | 3 | "The vendor tilted his head, a gesture that was almost human." | | 4 | "He was trying the handle of a steel door, his hands shaking." | | 5 | "And somewhere deep beneath London, something that had taken her partner's life was still waiting." |
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| 91.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 1 | | matches | | 0 | "He turned, and his expression was exhausted, resigned" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 46 | | tagDensity | 0.087 | | leniency | 0.174 | | rawRatio | 0.25 | | effectiveRatio | 0.043 | |