| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 158 | | tagDensity | 0.051 | | leniency | 0.101 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2539 | | 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) | |
| 90.15% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2539 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "pulse" | | 1 | "stomach" | | 2 | "stark" | | 3 | "quivered" | | 4 | "aligned" |
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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 | 0 | | narrationSentences | 219 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 219 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 370 | | 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 | 2539 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 123 | | wordCount | 1770 | | uniqueNames | 23 | | maxNameDensity | 2.49 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 44 | | Tube | 1 | | Camden | 1 | | London | 1 | | Transport | 1 | | Sergeant | 1 | | Owen | 1 | | Leach | 24 | | Farah | 1 | | Basu | 11 | | Queen | 1 | | Victoria | 1 | | Bank | 1 | | England | 1 | | Pears | 1 | | Greek | 1 | | Latin | 1 | | Eva | 19 | | Veil | 2 | | Compass | 2 | | Hall | 3 | | Mud | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Transport" | | 3 | "Sergeant" | | 4 | "Owen" | | 5 | "Leach" | | 6 | "Farah" | | 7 | "Basu" | | 8 | "Queen" | | 9 | "Victoria" | | 10 | "Eva" | | 11 | "Hall" | | 12 | "Mud" |
| | places | | 0 | "London" | | 1 | "England" | | 2 | "Greek" |
| | globalScore | 0.257 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 145 | | glossingSentenceCount | 1 | | matches | | 0 | "as though seeing it for the first time" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.394 | | wordCount | 2539 | | matches | | 0 | "not from his warning but from the object’s texture" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 370 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 272 | | mean | 9.33 | | std | 10.79 | | cv | 1.155 | | sampleLengths | | 0 | 36 | | 1 | 53 | | 2 | 8 | | 3 | 19 | | 4 | 6 | | 5 | 1 | | 6 | 14 | | 7 | 8 | | 8 | 1 | | 9 | 2 | | 10 | 4 | | 11 | 3 | | 12 | 10 | | 13 | 1 | | 14 | 5 | | 15 | 29 | | 16 | 2 | | 17 | 7 | | 18 | 5 | | 19 | 1 | | 20 | 5 | | 21 | 35 | | 22 | 4 | | 23 | 4 | | 24 | 2 | | 25 | 20 | | 26 | 4 | | 27 | 12 | | 28 | 2 | | 29 | 4 | | 30 | 3 | | 31 | 1 | | 32 | 3 | | 33 | 52 | | 34 | 46 | | 35 | 20 | | 36 | 4 | | 37 | 7 | | 38 | 6 | | 39 | 11 | | 40 | 4 | | 41 | 3 | | 42 | 9 | | 43 | 7 | | 44 | 7 | | 45 | 4 | | 46 | 25 | | 47 | 3 | | 48 | 4 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 219 | | matches | | 0 | "been removed" | | 1 | "been scraped" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 290 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 370 | | ratio | 0.005 | | matches | | 0 | "Labels marked shelves where goods had been removed in haste: MEMORY, FIRST QUALITY; CURSES, DOMESTIC; SAINTS’ TEETH, ASSORTED." | | 1 | "Beneath the gouges, blue lettering showed in fragments: MORN—." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 750 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 11 | | adverbRatio | 0.014666666666666666 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.004 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 370 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 370 | | mean | 6.86 | | std | 4.91 | | cv | 0.716 | | sampleLengths | | 0 | 27 | | 1 | 9 | | 2 | 10 | | 3 | 19 | | 4 | 24 | | 5 | 6 | | 6 | 2 | | 7 | 11 | | 8 | 8 | | 9 | 6 | | 10 | 1 | | 11 | 14 | | 12 | 8 | | 13 | 1 | | 14 | 2 | | 15 | 4 | | 16 | 3 | | 17 | 10 | | 18 | 1 | | 19 | 5 | | 20 | 3 | | 21 | 26 | | 22 | 2 | | 23 | 7 | | 24 | 5 | | 25 | 1 | | 26 | 5 | | 27 | 4 | | 28 | 12 | | 29 | 8 | | 30 | 11 | | 31 | 4 | | 32 | 4 | | 33 | 2 | | 34 | 13 | | 35 | 4 | | 36 | 3 | | 37 | 4 | | 38 | 12 | | 39 | 2 | | 40 | 4 | | 41 | 3 | | 42 | 1 | | 43 | 3 | | 44 | 15 | | 45 | 15 | | 46 | 8 | | 47 | 14 | | 48 | 8 | | 49 | 6 |
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| 51.71% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3216216216216216 | | totalSentences | 370 | | uniqueOpeners | 119 | |
| 16.03% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 208 | | matches | | 0 | "Instead, the air carried burnt" |
| | ratio | 0.005 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 208 | | matches | | 0 | "She checked her worn leather" | | 1 | "His mouth tightened." | | 2 | "His skin had the grainy" | | 3 | "She reached for it." | | 4 | "Their flames burned blue inside" | | 5 | "They struck the bars whenever" | | 6 | "He led her through the" | | 7 | "He wore an evening suit," | | 8 | "His right fist clutched a" | | 9 | "His left hand rested open" | | 10 | "Her gloved fingers worked around" | | 11 | "She peeled back the top" | | 12 | "She tucked a coil behind" | | 13 | "Its needle quivered towards the" | | 14 | "Its brass casing felt warm," | | 15 | "It aimed lower, towards his" | | 16 | "She walked around the body." | | 17 | "She aligned her pen with" | | 18 | "She turned his left cuff" | | 19 | "She unfastened two buttons and" |
| | ratio | 0.12 | |
| 51.35% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 170 | | totalSentences | 208 | | matches | | 0 | "Detective Harlow Quinn descended into" | | 1 | "The stairwell dropped farther than" | | 2 | "She checked her worn leather" | | 3 | "Blood striped one sleeve of" | | 4 | "Quinn halted three steps above" | | 5 | "The constable glanced at his" | | 6 | "His mouth tightened." | | 7 | "Quinn studied him." | | 8 | "His skin had the grainy" | | 9 | "Quinn descended the remaining steps." | | 10 | "The gate stood open." | | 11 | "A chalky white disc rested" | | 12 | "A hole pierced its centre," | | 13 | "She reached for it." | | 14 | "Hall caught his breath." | | 15 | "Quinn withdrew her fingers, not" | | 16 | "The disc had pores." | | 17 | "Quinn stepped through." | | 18 | "The station beyond the gate" | | 19 | "Lamps hung from cables along" |
| | ratio | 0.817 | |
| 24.04% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 208 | | matches | | 0 | "Whoever had emptied the place" |
| | ratio | 0.005 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 1 | | matches | | 0 | "After another fifty-two, music began to seep through the brickwork: a thin scrape of strings, then a drumbeat that vanished whenever she stopped walking." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "she announced (announce)" | | 1 | "Basu murmured (murmur)" |
| | dialogueSentences | 158 | | tagDensity | 0.025 | | leniency | 0.051 | | rawRatio | 0.5 | | effectiveRatio | 0.025 | |