| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said instead [instead]" |
| | dialogueSentences | 119 | | tagDensity | 0.16 | | leniency | 0.319 | | rawRatio | 0.053 | | effectiveRatio | 0.017 | |
| 95.39% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2167 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 90.77% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2167 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "depths" | | 1 | "stark" | | 2 | "efficient" | | 3 | "vibrated" |
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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 | 131 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 131 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 232 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 61 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2167 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 33 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 95 | | wordCount | 1286 | | uniqueNames | 9 | | maxNameDensity | 3.27 | | worstName | "Eva" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Yu-Fei | 2 | | French | 1 | | Cardiff | 1 | | Eva | 42 | | Rory | 39 | | Silas | 7 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Yu-Fei" | | 3 | "Eva" | | 4 | "Rory" | | 5 | "Silas" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 91 | | 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 | 2167 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 232 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 152 | | mean | 14.26 | | std | 15.95 | | cv | 1.119 | | sampleLengths | | 0 | 63 | | 1 | 18 | | 2 | 2 | | 3 | 14 | | 4 | 2 | | 5 | 5 | | 6 | 5 | | 7 | 22 | | 8 | 1 | | 9 | 52 | | 10 | 90 | | 11 | 4 | | 12 | 14 | | 13 | 1 | | 14 | 31 | | 15 | 9 | | 16 | 14 | | 17 | 3 | | 18 | 3 | | 19 | 19 | | 20 | 3 | | 21 | 34 | | 22 | 7 | | 23 | 24 | | 24 | 13 | | 25 | 2 | | 26 | 3 | | 27 | 16 | | 28 | 5 | | 29 | 4 | | 30 | 7 | | 31 | 2 | | 32 | 16 | | 33 | 55 | | 34 | 27 | | 35 | 2 | | 36 | 1 | | 37 | 2 | | 38 | 9 | | 39 | 27 | | 40 | 3 | | 41 | 7 | | 42 | 5 | | 43 | 3 | | 44 | 22 | | 45 | 18 | | 46 | 6 | | 47 | 3 | | 48 | 24 | | 49 | 15 |
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| 94.55% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 131 | | matches | | 0 | "been edited" | | 1 | "was frightened" | | 2 | "being asked" | | 3 | "been allowed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 219 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 232 | | ratio | 0.009 | | matches | | 0 | "Not collapse; something more guarded." | | 1 | "Below him, the green neon painted one side of the bar; above them, the floorboards of her flat crossed the ceiling in dark seams." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1094 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.015539305301645339 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0018281535648994515 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 232 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 232 | | mean | 9.34 | | std | 7.58 | | cv | 0.811 | | sampleLengths | | 0 | 14 | | 1 | 18 | | 2 | 7 | | 3 | 24 | | 4 | 6 | | 5 | 12 | | 6 | 2 | | 7 | 14 | | 8 | 2 | | 9 | 5 | | 10 | 5 | | 11 | 9 | | 12 | 13 | | 13 | 1 | | 14 | 7 | | 15 | 14 | | 16 | 15 | | 17 | 16 | | 18 | 15 | | 19 | 7 | | 20 | 25 | | 21 | 15 | | 22 | 12 | | 23 | 16 | | 24 | 4 | | 25 | 8 | | 26 | 6 | | 27 | 1 | | 28 | 15 | | 29 | 16 | | 30 | 7 | | 31 | 2 | | 32 | 14 | | 33 | 3 | | 34 | 3 | | 35 | 7 | | 36 | 12 | | 37 | 3 | | 38 | 9 | | 39 | 11 | | 40 | 14 | | 41 | 7 | | 42 | 24 | | 43 | 5 | | 44 | 8 | | 45 | 2 | | 46 | 3 | | 47 | 7 | | 48 | 9 | | 49 | 5 |
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| 43.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.25 | | totalSentences | 232 | | uniqueOpeners | 58 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 111 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 111 | | matches | | 0 | "Her black hair clung to" | | 1 | "His signet ring tapped the" | | 2 | "Her knee caught the edge," | | 3 | "It had once shouted abuse" | | 4 | "It had recited the whole" | | 5 | "Her hair, once dyed the" | | 6 | "She wore a charcoal coat" | | 7 | "She had owned a violin" | | 8 | "She had never learned to" | | 9 | "He waited for the rest" | | 10 | "Hers had a pale stripe" | | 11 | "He took the accounts with" | | 12 | "She had acquired the stillness" | | 13 | "She put her fingers over" | | 14 | "He moved on before either" | | 15 | "She laid her watch face" | | 16 | "She could remember Eva’s boarding" | | 17 | "She covered it with her" | | 18 | "She pressed the heel of" | | 19 | "She had once treated every" |
| | ratio | 0.261 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 103 | | totalSentences | 111 | | matches | | 0 | "The green neon above The" | | 1 | "Rory came in with her" | | 2 | "Rain darkened the shoulders of" | | 3 | "Her black hair clung to" | | 4 | "Silas glanced up from the" | | 5 | "His signet ring tapped the" | | 6 | "A woman rose from the" | | 7 | "Her knee caught the edge," | | 8 | "Rory knew the voice before" | | 9 | "It had once shouted abuse" | | 10 | "It had recited the whole" | | 11 | "Age had lowered it and" | | 12 | "The woman had Eva’s mouth" | | 13 | "The rest of her had" | | 14 | "Her hair, once dyed the" | | 15 | "She wore a charcoal coat" | | 16 | "She had owned a violin" | | 17 | "Rory touched the damp ends" | | 18 | "Eva’s gaze moved over the" | | 19 | "She had never learned to" |
| | ratio | 0.928 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 111 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 2 | | matches | | 0 | "Her black hair clung to her cheeks, and she pushed it back with the hand that bore the small crescent scar on its wrist." | | 1 | "For an instant Rory saw the old evening resume its hold on her: flight, inbox, another city, messages reduced to symbols that asked nothing difficult." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 119 | | tagDensity | 0.126 | | leniency | 0.252 | | rawRatio | 0 | | effectiveRatio | 0 | |