| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 111 | | tagDensity | 0.135 | | leniency | 0.27 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.80% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2083 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 90.40% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2083 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "trembled" | | 1 | "silence" | | 2 | "flicked" |
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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 | 165 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 165 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 261 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2083 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 32 | | unquotedAttributions | 1 | | matches | | 0 | "I should have come, it said." |
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| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 108 | | wordCount | 1607 | | uniqueNames | 15 | | maxNameDensity | 2.74 | | worstName | "Rory" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Nest | 2 | | Rory | 44 | | Chinatown | 1 | | Silas | 10 | | London | 2 | | Underground | 1 | | Soho | 1 | | Eva | 37 | | Evan | 3 | | Brighton | 1 | | You | 1 | | Cardiff | 2 | | University | 1 | | Pre-Law | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Silas" | | 4 | "Underground" | | 5 | "Eva" | | 6 | "Evan" | | 7 | "You" |
| | places | | 0 | "Chinatown" | | 1 | "London" | | 2 | "Soho" | | 3 | "Brighton" | | 4 | "Cardiff" |
| | globalScore | 0.131 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 109 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like someone who had stopped askin" | | 1 | "seemed more exhausting than agreeing" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.48 | | wordCount | 2083 | | matches | | 0 | "not by replacing every stone, but by leaving certain windows boarded" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 261 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 170 | | mean | 12.25 | | std | 16.49 | | cv | 1.346 | | sampleLengths | | 0 | 32 | | 1 | 43 | | 2 | 18 | | 3 | 9 | | 4 | 3 | | 5 | 4 | | 6 | 2 | | 7 | 4 | | 8 | 90 | | 9 | 47 | | 10 | 3 | | 11 | 1 | | 12 | 1 | | 13 | 4 | | 14 | 4 | | 15 | 7 | | 16 | 10 | | 17 | 76 | | 18 | 9 | | 19 | 10 | | 20 | 3 | | 21 | 10 | | 22 | 9 | | 23 | 56 | | 24 | 11 | | 25 | 7 | | 26 | 3 | | 27 | 1 | | 28 | 16 | | 29 | 83 | | 30 | 3 | | 31 | 13 | | 32 | 24 | | 33 | 9 | | 34 | 6 | | 35 | 5 | | 36 | 69 | | 37 | 6 | | 38 | 12 | | 39 | 4 | | 40 | 2 | | 41 | 32 | | 42 | 6 | | 43 | 5 | | 44 | 3 | | 45 | 14 | | 46 | 10 | | 47 | 62 | | 48 | 7 | | 49 | 5 |
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| 92.50% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 165 | | matches | | 0 | "was combed" | | 1 | "been trimmed" | | 2 | "being displayed" | | 3 | "been eleven" | | 4 | "was supposed" | | 5 | "was supposed" | | 6 | "was written" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 298 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 261 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1614 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 46 | | adverbRatio | 0.028500619578686492 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.004956629491945477 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 261 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 261 | | mean | 7.98 | | std | 6.67 | | cv | 0.835 | | sampleLengths | | 0 | 32 | | 1 | 7 | | 2 | 17 | | 3 | 19 | | 4 | 4 | | 5 | 14 | | 6 | 7 | | 7 | 2 | | 8 | 3 | | 9 | 4 | | 10 | 2 | | 11 | 4 | | 12 | 5 | | 13 | 20 | | 14 | 18 | | 15 | 17 | | 16 | 30 | | 17 | 12 | | 18 | 21 | | 19 | 14 | | 20 | 3 | | 21 | 1 | | 22 | 1 | | 23 | 4 | | 24 | 4 | | 25 | 6 | | 26 | 1 | | 27 | 10 | | 28 | 10 | | 29 | 15 | | 30 | 12 | | 31 | 25 | | 32 | 14 | | 33 | 9 | | 34 | 6 | | 35 | 4 | | 36 | 3 | | 37 | 10 | | 38 | 9 | | 39 | 10 | | 40 | 7 | | 41 | 20 | | 42 | 9 | | 43 | 10 | | 44 | 11 | | 45 | 7 | | 46 | 3 | | 47 | 1 | | 48 | 6 | | 49 | 10 |
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| 44.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.25287356321839083 | | totalSentences | 261 | | uniqueOpeners | 66 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 146 | | matches | | 0 | "Then the woman looked directly" | | 1 | "Once, she had been incapable" | | 2 | "Somewhere in the bar, a" | | 3 | "Instead she sat in the" | | 4 | "Then Rory had gone to" | | 5 | "Then she turned toward the" |
| | ratio | 0.041 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 146 | | matches | | 0 | "It glittered on the shoulders" | | 1 | "She set the delivery bag" | | 2 | "His grey-streaked auburn hair was" | | 3 | "He leaned one hand on" | | 4 | "He gave her a look," | | 5 | "She rubbed at the crescent-shaped" | | 6 | "She thought of the flat" | | 7 | "She wrapped both hands around" | | 8 | "She wore no hat despite" | | 9 | "Her hair, once long and" | | 10 | "She held an untouched glass" | | 11 | "She had changed in the" | | 12 | "Her face was thinner." | | 13 | "Her coat was expensive, black" | | 14 | "She looked like someone who" | | 15 | "His hazel eyes moved from" | | 16 | "He poured Eva’s whisky into" | | 17 | "he asked Rory" | | 18 | "He limped toward the bookshelf" | | 19 | "He pressed two fingers to" |
| | ratio | 0.281 | |
| 55.89% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 118 | | totalSentences | 146 | | matches | | 0 | "The green neon above the" | | 1 | "Rain had followed her up" | | 2 | "It glittered on the shoulders" | | 3 | "She set the delivery bag" | | 4 | "Silas looked up from polishing" | | 5 | "The bar was nearly empty." | | 6 | "A woman in a red" | | 7 | "The Nest smelled of beer," | | 8 | "Every surface seemed to hold" | | 9 | "Silas took the bag from" | | 10 | "His grey-streaked auburn hair was" | | 11 | "He leaned one hand on" | | 12 | "Rory dropped onto the nearest" | | 13 | "He gave her a look," | | 14 | "She rubbed at the crescent-shaped" | | 15 | "The old habit returned whenever" | | 16 | "She thought of the flat" | | 17 | "London had become a place" | | 18 | "Silas set a chipped mug" | | 19 | "She wrapped both hands around" |
| | ratio | 0.808 | |
| 34.25% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 146 | | matches | | 0 | "Now her face gave away" |
| | ratio | 0.007 | |
| 99.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 66 | | technicalSentenceCount | 4 | | matches | | 0 | "The green neon above the Raven’s Nest had begun to stutter by the time Rory came in through the side door, carrying a paper bag that had gone soft at the bottom…" | | 1 | "Every surface seemed to hold a past life: maps pinned to the walls, photographs of strangers, bottles that had survived longer than most of the people who drank…" | | 2 | "The shelves held old atlases, cracked novels, and several objects that had no business being displayed in a public house: a brass compass, a rusted camera, a fr…" | | 3 | "Her name was written on it in Eva’s handwriting, rounded and hurried, the same handwriting that had once filled the margins of Rory’s schoolbooks with jokes." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 111 | | tagDensity | 0.126 | | leniency | 0.252 | | rawRatio | 0 | | effectiveRatio | 0 | |