| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 1 | | adverbTags | | 0 | "she shouted again [again]" |
| | dialogueSentences | 8 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.25 | | effectiveRatio | 0.25 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1519 | | 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) | |
| 73.67% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1519 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "pumping" | | 1 | "footsteps" | | 2 | "electric" | | 3 | "wavering" | | 4 | "pulse" | | 5 | "velvet" | | 6 | "stomach" |
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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 | 1 | | narrationSentences | 160 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 160 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 164 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1519 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 76.57% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1498 | | uniqueNames | 9 | | maxNameDensity | 1.47 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Detective | 1 | | Harlow | 1 | | Quinn | 22 | | Met | 1 | | Morris | 2 | | Tube | 2 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Morris" |
| | places | | | globalScore | 0.766 | | windowScore | 0.833 | |
| 83.04% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 112 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like a knuckle bone, polished smoo" | | 1 | "seemed surprised by her" | | 2 | "looked like Morris’s, the battered one he" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.658 | | wordCount | 1519 | | matches | | 0 | "not close yet, but coming" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 164 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 27.13 | | std | 21.71 | | cv | 0.8 | | sampleLengths | | 0 | 15 | | 1 | 50 | | 2 | 11 | | 3 | 4 | | 4 | 55 | | 5 | 3 | | 6 | 13 | | 7 | 59 | | 8 | 29 | | 9 | 59 | | 10 | 7 | | 11 | 27 | | 12 | 10 | | 13 | 52 | | 14 | 1 | | 15 | 24 | | 16 | 37 | | 17 | 6 | | 18 | 28 | | 19 | 7 | | 20 | 30 | | 21 | 52 | | 22 | 4 | | 23 | 63 | | 24 | 22 | | 25 | 3 | | 26 | 55 | | 27 | 5 | | 28 | 36 | | 29 | 18 | | 30 | 5 | | 31 | 61 | | 32 | 3 | | 33 | 28 | | 34 | 47 | | 35 | 7 | | 36 | 2 | | 37 | 45 | | 38 | 22 | | 39 | 32 | | 40 | 5 | | 41 | 76 | | 42 | 8 | | 43 | 71 | | 44 | 13 | | 45 | 7 | | 46 | 44 | | 47 | 4 | | 48 | 26 | | 49 | 66 |
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| 98.68% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 160 | | matches | | 0 | "been turned" | | 1 | "was said" | | 2 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 271 | | matches | | 0 | "was trying" | | 1 | "was already wrenching" | | 2 | "was disappearing" | | 3 | "was bleeding" |
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| 90.59% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 4 | | flaggedSentences | 3 | | totalSentences | 164 | | ratio | 0.018 | | matches | | 0 | "Rain blurred the face; the minute hand had crawled almost to the top." | | 1 | "Some wore ordinary coats; others had wrapped themselves in fabrics that caught the light like fish scales." | | 2 | "She had three choices: go back, call for help when she found a signal, and let the man disappear; stay and fight a crowd that had not decided what she was; or follow him deeper into the dark." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1501 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.023984010659560292 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.002664890073284477 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 164 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 164 | | mean | 9.26 | | std | 5.81 | | cv | 0.627 | | sampleLengths | | 0 | 15 | | 1 | 21 | | 2 | 17 | | 3 | 6 | | 4 | 2 | | 5 | 2 | | 6 | 2 | | 7 | 11 | | 8 | 4 | | 9 | 8 | | 10 | 11 | | 11 | 20 | | 12 | 16 | | 13 | 3 | | 14 | 4 | | 15 | 9 | | 16 | 11 | | 17 | 11 | | 18 | 4 | | 19 | 26 | | 20 | 7 | | 21 | 10 | | 22 | 5 | | 23 | 1 | | 24 | 13 | | 25 | 18 | | 26 | 5 | | 27 | 21 | | 28 | 15 | | 29 | 3 | | 30 | 4 | | 31 | 11 | | 32 | 7 | | 33 | 9 | | 34 | 5 | | 35 | 3 | | 36 | 2 | | 37 | 9 | | 38 | 19 | | 39 | 11 | | 40 | 13 | | 41 | 1 | | 42 | 6 | | 43 | 8 | | 44 | 10 | | 45 | 4 | | 46 | 10 | | 47 | 17 | | 48 | 6 | | 49 | 6 |
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| 45.19% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.3006134969325153 | | totalSentences | 163 | | uniqueOpeners | 49 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 148 | | matches | | 0 | "Then he’d looked straight at" | | 1 | "Then he stumbled on the" | | 2 | "Only the soft patter of" | | 3 | "Then footsteps, receding." | | 4 | "Somewhere in front of her," |
| | ratio | 0.034 | |
| 95.68% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 46 | | totalSentences | 148 | | matches | | 0 | "He cut between two black" | | 1 | "She kept her eyes on" | | 2 | "He ran with his head" | | 3 | "He shoved through a knot" | | 4 | "She didn’t look back." | | 5 | "Her worn leather watch knocked" | | 6 | "She glanced at it anyway." | | 7 | "He looked over his shoulder." | | 8 | "He was hurt." | | 9 | "Her other hand went to" | | 10 | "She tried again." | | 11 | "He looked at her once" | | 12 | "He slipped through the door" | | 13 | "It gave onto a set" | | 14 | "She stopped at the top" | | 15 | "She lifted it higher, as" | | 16 | "She could go back." | | 17 | "It was the smell." | | 18 | "She had smelled it once" | | 19 | "They’d found no second exit," |
| | ratio | 0.311 | |
| 41.08% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 124 | | totalSentences | 148 | | matches | | 0 | "The man saw her in" | | 1 | "The man’s face had been" | | 2 | "He cut between two black" | | 3 | "Quinn went after him." | | 4 | "A horn blared as she" | | 5 | "Tires hissed through standing water," | | 6 | "She kept her eyes on" | | 7 | "He ran with his head" | | 8 | "The word went nowhere." | | 9 | "Soho swallowed it in wet" | | 10 | "He shoved through a knot" | | 11 | "Quinn followed, clipping a shoulder," | | 12 | "She didn’t look back." | | 13 | "The rest was lungs, footing," | | 14 | "Her worn leather watch knocked" | | 15 | "She glanced at it anyway." | | 16 | "Rain blurred the face; the" | | 17 | "The man darted down a" | | 18 | "He looked over his shoulder." | | 19 | "Quinn caught a glimpse of" |
| | ratio | 0.838 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 148 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 71 | | technicalSentenceCount | 2 | | matches | | 0 | "A murmur of many people, rising and falling in a way that didn’t belong underground." | | 1 | "Somewhere in front of her, a suspect was bleeding and fleeing through a place that should not exist." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, and the guard turned" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "she shouted (shout)" | | 1 | "she shouted again (shout)" |
| | dialogueSentences | 8 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |