| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 61 | | tagDensity | 0.344 | | leniency | 0.689 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 82.34% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1416 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "suddenly" | | 1 | "very" | | 2 | "perfectly" | | 3 | "really" | | 4 | "quickly" |
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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) | |
| 57.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1416 | | totalAiIsms | 12 | | found | | 0 | | | 1 | | | 2 | | | 3 | | word | "down her spine" | | count | 1 |
| | 4 | | | 5 | | | 6 | | | 7 | | | 8 | |
| | highlights | | 0 | "potential" | | 1 | "chill" | | 2 | "familiar" | | 3 | "down her spine" | | 4 | "silence" | | 5 | "crystal" | | 6 | "weight" | | 7 | "tracing" | | 8 | "flicker" |
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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 | 144 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 144 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 183 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 6 | | totalWords | 1404 | | ratio | 0.004 | | matches | | 0 | "Waste of ambition, Rory. Wasted potential." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 34 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1021 | | uniqueNames | 20 | | maxNameDensity | 1.18 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Golden | 1 | | Empress | 1 | | Chinese | 1 | | Raven | 2 | | Nest | 2 | | Tuesday | 1 | | Cardiff | 1 | | Rory | 12 | | Ellis | 2 | | Silas | 6 | | Leo | 8 | | Soho | 1 | | French | 1 | | Evan | 2 | | Italy | 1 | | Garth | 1 | | Hill | 1 | | Eliza | 1 | | North | 1 | | Star | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Ellis" | | 4 | "Silas" | | 5 | "Leo" | | 6 | "Evan" | | 7 | "Eliza" |
| | places | | 0 | "Cardiff" | | 1 | "Soho" | | 2 | "Italy" | | 3 | "Garth" | | 4 | "Hill" |
| | globalScore | 0.912 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 1 | | matches | | 0 | "smelled like a hospital" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1404 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 183 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 82 | | mean | 17.12 | | std | 16.02 | | cv | 0.935 | | sampleLengths | | 0 | 44 | | 1 | 38 | | 2 | 7 | | 3 | 4 | | 4 | 18 | | 5 | 5 | | 6 | 4 | | 7 | 58 | | 8 | 1 | | 9 | 22 | | 10 | 21 | | 11 | 25 | | 12 | 3 | | 13 | 35 | | 14 | 2 | | 15 | 28 | | 16 | 8 | | 17 | 29 | | 18 | 9 | | 19 | 33 | | 20 | 34 | | 21 | 10 | | 22 | 4 | | 23 | 26 | | 24 | 4 | | 25 | 13 | | 26 | 2 | | 27 | 12 | | 28 | 10 | | 29 | 12 | | 30 | 5 | | 31 | 28 | | 32 | 15 | | 33 | 17 | | 34 | 41 | | 35 | 4 | | 36 | 2 | | 37 | 41 | | 38 | 8 | | 39 | 12 | | 40 | 2 | | 41 | 6 | | 42 | 6 | | 43 | 44 | | 44 | 2 | | 45 | 32 | | 46 | 1 | | 47 | 43 | | 48 | 9 | | 49 | 5 |
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| 93.08% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 144 | | matches | | 0 | "was gone" | | 1 | "was practiced" | | 2 | "was fixed" | | 3 | "was gone" | | 4 | "was banked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 177 | | matches | | |
| 96.02% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 183 | | ratio | 0.016 | | matches | | 0 | "She looked at Leo—this stranger in her best friend’s face." | | 1 | "The signet ring on his right hand—an Ellis family heirloom—glinted." | | 2 | "He stood, leaving his half-finished whiskey on the bar—a rejected prop." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1032 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.03488372093023256 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.00872093023255814 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 183 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 183 | | mean | 7.67 | | std | 5.89 | | cv | 0.767 | | sampleLengths | | 0 | 11 | | 1 | 23 | | 2 | 6 | | 3 | 4 | | 4 | 6 | | 5 | 9 | | 6 | 1 | | 7 | 3 | | 8 | 13 | | 9 | 4 | | 10 | 2 | | 11 | 7 | | 12 | 4 | | 13 | 9 | | 14 | 4 | | 15 | 5 | | 16 | 5 | | 17 | 4 | | 18 | 18 | | 19 | 20 | | 20 | 1 | | 21 | 2 | | 22 | 17 | | 23 | 1 | | 24 | 13 | | 25 | 3 | | 26 | 2 | | 27 | 4 | | 28 | 3 | | 29 | 12 | | 30 | 6 | | 31 | 11 | | 32 | 11 | | 33 | 3 | | 34 | 3 | | 35 | 14 | | 36 | 8 | | 37 | 5 | | 38 | 8 | | 39 | 2 | | 40 | 5 | | 41 | 11 | | 42 | 12 | | 43 | 8 | | 44 | 20 | | 45 | 9 | | 46 | 9 | | 47 | 3 | | 48 | 4 | | 49 | 8 |
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| 52.64% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.37158469945355194 | | totalSentences | 183 | | uniqueOpeners | 68 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 120 | | matches | (empty) | | ratio | 0 | |
| 40.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 54 | | totalSentences | 120 | | matches | | 0 | "she muttered to herself" | | 1 | "It would cover her half" | | 2 | "She didn’t look up." | | 3 | "She saw a boy in" | | 4 | "he said, calm, pulling out" | | 5 | "It didn’t scrape." | | 6 | "He had new movements." | | 7 | "Her side ached." | | 8 | "He gave a small, professional" | | 9 | "It was a real estate" | | 10 | "He gestured to Silas, who" | | 11 | "His eyes, once a warm" | | 12 | "He didn’t say it with" | | 13 | "He swirled it once, inhaled," | | 14 | "He’d never drunk whiskey before." | | 15 | "he said, resting his glass" | | 16 | "His suit was midnight blue," | | 17 | "He’d sought her out in" | | 18 | "He tilted his head." | | 19 | "He didn’t spit them." |
| | ratio | 0.45 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 112 | | totalSentences | 120 | | matches | | 0 | "The pint glass landed on" | | 1 | "Rory counted receipts from her" | | 2 | "The Raven’s Nest was quiet" | | 3 | "A Tuesday death-rattle quiet." | | 4 | "she muttered to herself" | | 5 | "It would cover her half" | | 6 | "The numbers blurred." | | 7 | "Evan’s voice still whispered from" | | 8 | "*Waste of ambition, Rory." | | 9 | "A new shadow fell across" | | 10 | "A chill, precise and familiar," | | 11 | "She didn’t look up." | | 12 | "Rory’s head snapped up." | | 13 | "She saw a boy in" | | 14 | "he said, calm, pulling out" | | 15 | "It didn’t scrape." | | 16 | "He had new movements." | | 17 | "Her side ached." | | 18 | "A phantom pain where a" | | 19 | "He gave a small, professional" |
| | ratio | 0.933 | |
| 41.67% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 120 | | matches | | 0 | "Now he’d mastered this." |
| | ratio | 0.008 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 2 | | matches | | 0 | "For a moment, she didn’t see the tailored suit, the silver-streaked temples, the hands that bore no calluses." | | 1 | "He looked at the girl who’d been his North Star once." |
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| 5.95% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 5 | | matches | | 0 | "Rory said, flat" | | 1 | "he said, suddenly" | | 2 | "he said, not moving" | | 3 | "she said, not turning" | | 4 | "he noted, his voice a low rumble" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 18 | | fancyCount | 3 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "He didn’t (do)" | | 2 | "he noted (note)" |
| | dialogueSentences | 61 | | tagDensity | 0.295 | | leniency | 0.59 | | rawRatio | 0.167 | | effectiveRatio | 0.098 | |