| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 38 | | tagDensity | 0.184 | | leniency | 0.368 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1585 | | 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) | |
| 68.45% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1585 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "warmth" | | 1 | "shattered" | | 2 | "silence" | | 3 | "footsteps" | | 4 | "raced" | | 5 | "gloom" | | 6 | "glistening" | | 7 | "flickered" |
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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 | 191 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 191 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 223 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1585 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 39.04% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 1442 | | uniqueNames | 10 | | maxNameDensity | 2.22 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 32 | | Raven | 2 | | Nest | 2 | | London | 1 | | Underground | 1 | | Morris | 1 | | Symbols | 1 | | One | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Morris" | | 5 | "Symbols" | | 6 | "One" |
| | places | | | globalScore | 0.39 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 113 | | 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 | 1585 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 223 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 129 | | mean | 12.29 | | std | 12.47 | | cv | 1.015 | | sampleLengths | | 0 | 10 | | 1 | 44 | | 2 | 1 | | 3 | 3 | | 4 | 25 | | 5 | 3 | | 6 | 41 | | 7 | 9 | | 8 | 8 | | 9 | 17 | | 10 | 6 | | 11 | 26 | | 12 | 4 | | 13 | 4 | | 14 | 66 | | 15 | 4 | | 16 | 2 | | 17 | 4 | | 18 | 17 | | 19 | 6 | | 20 | 10 | | 21 | 15 | | 22 | 12 | | 23 | 2 | | 24 | 3 | | 25 | 36 | | 26 | 6 | | 27 | 23 | | 28 | 4 | | 29 | 8 | | 30 | 7 | | 31 | 25 | | 32 | 7 | | 33 | 11 | | 34 | 4 | | 35 | 12 | | 36 | 5 | | 37 | 7 | | 38 | 31 | | 39 | 2 | | 40 | 37 | | 41 | 9 | | 42 | 15 | | 43 | 5 | | 44 | 2 | | 45 | 32 | | 46 | 1 | | 47 | 39 | | 48 | 5 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 191 | | matches | | 0 | "was gone" | | 1 | "been carved" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 271 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 223 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1039 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.016361886429258902 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0019249278152069298 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 223 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 223 | | mean | 7.11 | | std | 4.84 | | cv | 0.681 | | sampleLengths | | 0 | 10 | | 1 | 27 | | 2 | 17 | | 3 | 1 | | 4 | 3 | | 5 | 25 | | 6 | 3 | | 7 | 4 | | 8 | 6 | | 9 | 21 | | 10 | 10 | | 11 | 9 | | 12 | 8 | | 13 | 7 | | 14 | 6 | | 15 | 4 | | 16 | 6 | | 17 | 5 | | 18 | 3 | | 19 | 18 | | 20 | 4 | | 21 | 4 | | 22 | 17 | | 23 | 16 | | 24 | 5 | | 25 | 28 | | 26 | 4 | | 27 | 2 | | 28 | 4 | | 29 | 8 | | 30 | 9 | | 31 | 5 | | 32 | 1 | | 33 | 5 | | 34 | 5 | | 35 | 10 | | 36 | 2 | | 37 | 3 | | 38 | 12 | | 39 | 2 | | 40 | 3 | | 41 | 4 | | 42 | 2 | | 43 | 12 | | 44 | 4 | | 45 | 14 | | 46 | 6 | | 47 | 11 | | 48 | 12 | | 49 | 4 |
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| 46.34% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.30493273542600896 | | totalSentences | 223 | | uniqueOpeners | 68 | |
| 58.82% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 170 | | matches | | 0 | "Somewhere ahead, shoes hammered down" | | 1 | "Then his teeth separated into" | | 2 | "Then blue light returned in" |
| | ratio | 0.018 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 170 | | matches | | 0 | "He glanced back." | | 1 | "She pushed harder." | | 2 | "Her closely cropped salt-and-pepper hair" | | 3 | "Her left wrist snapped up" | | 4 | "He yanked the handle." | | 5 | "She caught herself against a" | | 6 | "His hand rested against the" | | 7 | "It did not empty." | | 8 | "It belonged to people with" | | 9 | "He grabbed a brass rail" | | 10 | "She jammed her shoulder into" | | 11 | "She forced herself through." | | 12 | "Its beam found a stairwell" | | 13 | "It smelled of rust, wet" | | 14 | "Her boots slipped on the" | | 15 | "She caught the rail and" | | 16 | "Her voice struck the walls" | | 17 | "Her hand settled near her" | | 18 | "His final case file sat" | | 19 | "His face looked human until" |
| | ratio | 0.194 | |
| 27.65% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 147 | | totalSentences | 170 | | matches | | 0 | "Detective Harlow Quinn drove through" | | 1 | "The suspect slipped between two" | | 2 | "He glanced back." | | 3 | "Quinn caught the flash of" | | 4 | "She pushed harder." | | 5 | "A taxi horn blared." | | 6 | "Someone swore as Quinn shouldered" | | 7 | "Her closely cropped salt-and-pepper hair" | | 8 | "Her left wrist snapped up" | | 9 | "The watch ticked beneath its" | | 10 | "He yanked the handle." | | 11 | "Quinn crossed the road without" | | 12 | "A motorbike clipped her coat." | | 13 | "The rider shouted." | | 14 | "She caught herself against a" | | 15 | "The suspect vanished inside." | | 16 | "Quinn entered behind him." | | 17 | "The Raven’s Nest swallowed the" | | 18 | "Maps covered the walls between" | | 19 | "Bottles glimmered behind the bar." |
| | ratio | 0.865 | |
| 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 | 51 | | technicalSentenceCount | 3 | | matches | | 0 | "A handful of patrons turned towards the door, then returned to their drinks with the careful speed of people who had seen enough trouble to recognise its shape." | | 1 | "The tunnel stretched ahead, lit by blue lamps that hummed behind wire cages." | | 2 | "A stallholder displayed knives that breathed steam along their blades." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 38 | | tagDensity | 0.105 | | leniency | 0.211 | | rawRatio | 0.25 | | effectiveRatio | 0.053 | |