| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 2 | | adverbTags | | 0 | "Oliver gestured vaguely [vaguely]" | | 1 | "Oliver said softly [softly]" |
| | dialogueSentences | 51 | | tagDensity | 0.196 | | leniency | 0.392 | | rawRatio | 0.2 | | effectiveRatio | 0.078 | |
| 79.99% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1499 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "slightly" | | 1 | "really" | | 2 | "perfectly" | | 3 | "softly" | | 4 | "truly" |
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| 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) | |
| 49.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1499 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "electric" | | 1 | "vibrated" | | 2 | "traced" | | 3 | "sanctuary" | | 4 | "familiar" | | 5 | "lilt" | | 6 | "weight" | | 7 | "imposing" | | 8 | "silence" | | 9 | "perfect" | | 10 | "tracing" | | 11 | "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 | 0 | | narrationSentences | 77 | | matches | (empty) | |
| 68.65% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 77 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 117 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 70 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1494 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 55 | | wordCount | 995 | | uniqueNames | 15 | | maxNameDensity | 1.51 | | worstName | "Rory" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Oliver" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Soho | 1 | | Prague | 1 | | Glamorgan | 1 | | Silas | 10 | | Cardiff | 2 | | Chancery | 1 | | Lane | 1 | | Rory | 15 | | Oxfords | 1 | | Welsh | 2 | | Oliver | 14 | | Evan | 1 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Rory" | | 4 | "Oxfords" | | 5 | "Oliver" | | 6 | "Evan" |
| | places | | 0 | "Soho" | | 1 | "Prague" | | 2 | "Glamorgan" | | 3 | "Cardiff" | | 4 | "Chancery" | | 5 | "Lane" | | 6 | "London" |
| | globalScore | 0.746 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | 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 | 1494 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 117 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 60 | | mean | 24.9 | | std | 20.14 | | cv | 0.809 | | sampleLengths | | 0 | 53 | | 1 | 67 | | 2 | 70 | | 3 | 20 | | 4 | 62 | | 5 | 5 | | 6 | 27 | | 7 | 1 | | 8 | 35 | | 9 | 8 | | 10 | 1 | | 11 | 26 | | 12 | 21 | | 13 | 53 | | 14 | 3 | | 15 | 27 | | 16 | 4 | | 17 | 4 | | 18 | 3 | | 19 | 30 | | 20 | 24 | | 21 | 25 | | 22 | 9 | | 23 | 12 | | 24 | 47 | | 25 | 6 | | 26 | 31 | | 27 | 23 | | 28 | 37 | | 29 | 15 | | 30 | 17 | | 31 | 39 | | 32 | 87 | | 33 | 21 | | 34 | 25 | | 35 | 18 | | 36 | 4 | | 37 | 28 | | 38 | 3 | | 39 | 19 | | 40 | 22 | | 41 | 16 | | 42 | 4 | | 43 | 91 | | 44 | 22 | | 45 | 38 | | 46 | 45 | | 47 | 23 | | 48 | 35 | | 49 | 33 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 77 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 155 | | matches | | |
| 94.02% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 117 | | ratio | 0.017 | | matches | | 0 | "He worked with a quiet, deliberate efficiency, his right hand—adorned with his heavy silver signet ring—polishing a tumbler." | | 1 | "A vision of her father—once an imposing, fierce man who demanded silence when he entered a room—sitting quietly in a damp cottage made Rory's throat tight." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1004 | | adjectiveStacks | 1 | | stackExamples | | 0 | "warm, beer-scented sanctuary." |
| | adverbCount | 24 | | adverbRatio | 0.02390438247011952 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.008964143426294821 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 117 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 117 | | mean | 12.77 | | std | 9.7 | | cv | 0.76 | | sampleLengths | | 0 | 18 | | 1 | 11 | | 2 | 24 | | 3 | 6 | | 4 | 14 | | 5 | 18 | | 6 | 29 | | 7 | 16 | | 8 | 14 | | 9 | 8 | | 10 | 10 | | 11 | 22 | | 12 | 9 | | 13 | 11 | | 14 | 12 | | 15 | 11 | | 16 | 17 | | 17 | 22 | | 18 | 5 | | 19 | 4 | | 20 | 10 | | 21 | 13 | | 22 | 1 | | 23 | 35 | | 24 | 8 | | 25 | 1 | | 26 | 11 | | 27 | 15 | | 28 | 16 | | 29 | 5 | | 30 | 12 | | 31 | 16 | | 32 | 22 | | 33 | 3 | | 34 | 3 | | 35 | 11 | | 36 | 16 | | 37 | 4 | | 38 | 4 | | 39 | 3 | | 40 | 15 | | 41 | 9 | | 42 | 6 | | 43 | 24 | | 44 | 25 | | 45 | 9 | | 46 | 12 | | 47 | 16 | | 48 | 31 | | 49 | 6 |
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| 41.88% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3076923076923077 | | totalSentences | 117 | | uniqueOpeners | 36 | |
| 44.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 75 | | matches | | 0 | "Instead, she kept her focus" |
| | ratio | 0.013 | |
| 76.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 75 | | matches | | 0 | "His auburn hair, streaked with" | | 1 | "He worked with a quiet," | | 2 | "His left leg hitched slightly" | | 3 | "It was a cruel coincidence" | | 4 | "Her left thumb traced the" | | 5 | "He wore a dark, tailored" | | 6 | "His face was damp, his" | | 7 | "He looked around the dimly" | | 8 | "His eyes settled on her." | | 9 | "He walked toward her booth," | | 10 | "He stood over the table," | | 11 | "He set his wet umbrella" | | 12 | "He looked her over, his" | | 13 | "He laid a cardboard coaster" | | 14 | "She kept her face perfectly" | | 15 | "She remembered the sound of" | | 16 | "He’s just a young man" | | 17 | "You have to support him." | | 18 | "He reached across the table," | | 19 | "She saw the old maps," |
| | ratio | 0.36 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 75 | | matches | | 0 | "The green neon of The" | | 1 | "Silas stood behind the mahogany" | | 2 | "His auburn hair, streaked with" | | 3 | "He worked with a quiet," | | 4 | "His left leg hitched slightly" | | 5 | "Rory sat in her usual" | | 6 | "It was a cruel coincidence" | | 7 | "Her left thumb traced the" | | 8 | "The scar was white and" | | 9 | "The brass bell above the" | | 10 | "A draft of wet air" | | 11 | "A man stepped in, shaking" | | 12 | "He wore a dark, tailored" | | 13 | "His face was damp, his" | | 14 | "He looked around the dimly" | | 15 | "His eyes settled on her." | | 16 | "The man’s posture shifted." | | 17 | "The professional mask slipped, revealing" | | 18 | "He walked toward her booth," | | 19 | "The Welsh lilt in his" |
| | ratio | 0.947 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 75 | | matches | (empty) | | ratio | 0 | |
| 65.22% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 5 | | matches | | 0 | "The green neon of The Raven's Nest buzzed, a low, electric hum that vibrated through the damp windowpanes." | | 1 | "He wore a dark, tailored overcoat that screamed of Chancery Lane." | | 2 | "A vision of her father—once an imposing, fierce man who demanded silence when he entered a room—sitting quietly in a damp cottage made Rory's throat tight." | | 3 | "She thought of her small flat upstairs, the radiator that clanked, the absolute freedom of having nothing but her own name and her own time." | | 4 | "He limped back to his bar, leaving Rory alone with the hum of the green light and the rain washing the city clean." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 51 | | tagDensity | 0.098 | | leniency | 0.196 | | rawRatio | 0 | | effectiveRatio | 0 | |