| 66.67% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 24 | | adverbTagCount | 4 | | adverbTags | | 0 | "Imogen said finally [finally]" | | 1 | "She gestured vaguely [vaguely]" | | 2 | "she said quietly [quietly]" | | 3 | "she said finally [finally]" |
| | dialogueSentences | 60 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.167 | | effectiveRatio | 0.133 | |
| 89.54% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1434 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "quickly" | | 1 | "really" | | 2 | "slowly" |
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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) | |
| 65.13% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1434 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "beacon" | | 1 | "warmth" | | 2 | "familiar" | | 3 | "silence" | | 4 | "flickered" | | 5 | "traced" | | 6 | "whisper" | | 7 | "disrupting" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 101 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 101 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 135 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1426 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 59 | | wordCount | 984 | | uniqueNames | 13 | | maxNameDensity | 2.54 | | worstName | "Aurora" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 25 | | Carter | 1 | | Raven | 2 | | Nest | 2 | | Tuesday | 1 | | Soho | 1 | | Old | 1 | | British | 1 | | Rory | 1 | | Imogen | 17 | | Silas | 5 | | Evan | 1 | | London | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Carter" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Rory" | | 5 | "Imogen" | | 6 | "Silas" | | 7 | "Evan" |
| | places | | | globalScore | 0.23 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed familiar in a way Aurora couldn't place" |
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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 | 1426 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 135 | | matches | | 0 | "learned that everything" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 25.93 | | std | 23.44 | | cv | 0.904 | | sampleLengths | | 0 | 85 | | 1 | 70 | | 2 | 5 | | 3 | 12 | | 4 | 48 | | 5 | 59 | | 6 | 5 | | 7 | 1 | | 8 | 24 | | 9 | 11 | | 10 | 46 | | 11 | 35 | | 12 | 6 | | 13 | 39 | | 14 | 54 | | 15 | 8 | | 16 | 27 | | 17 | 22 | | 18 | 2 | | 19 | 33 | | 20 | 15 | | 21 | 20 | | 22 | 48 | | 23 | 2 | | 24 | 23 | | 25 | 1 | | 26 | 3 | | 27 | 1 | | 28 | 91 | | 29 | 6 | | 30 | 3 | | 31 | 43 | | 32 | 20 | | 33 | 5 | | 34 | 33 | | 35 | 7 | | 36 | 5 | | 37 | 22 | | 38 | 47 | | 39 | 3 | | 40 | 41 | | 41 | 3 | | 42 | 59 | | 43 | 33 | | 44 | 9 | | 45 | 26 | | 46 | 29 | | 47 | 14 | | 48 | 7 | | 49 | 30 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 101 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 178 | | matches | (empty) | |
| 79.37% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 135 | | ratio | 0.022 | | matches | | 0 | "Only one person had ever called her that—had ever been allowed to." | | 1 | "\"In the flesh.\" The woman—Imogen—crossed the bar in three long strides and pulled Aurora into a hug that smelled of rain and expensive perfume." | | 2 | "But for a moment, in that dimly lit bar with the green neon glowing through the window, she'd seen herself in someone else—the same lost, the same searching, the same quiet desperation to find a reason to stay." |
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| 85.51% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 990 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 56 | | adverbRatio | 0.05656565656565657 | | lyAdverbCount | 19 | | lyAdverbRatio | 0.01919191919191919 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 135 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 135 | | mean | 10.56 | | std | 8.24 | | cv | 0.781 | | sampleLengths | | 0 | 6 | | 1 | 28 | | 2 | 5 | | 3 | 18 | | 4 | 28 | | 5 | 6 | | 6 | 14 | | 7 | 24 | | 8 | 15 | | 9 | 11 | | 10 | 5 | | 11 | 8 | | 12 | 2 | | 13 | 2 | | 14 | 12 | | 15 | 14 | | 16 | 8 | | 17 | 11 | | 18 | 3 | | 19 | 4 | | 20 | 12 | | 21 | 26 | | 22 | 17 | | 23 | 3 | | 24 | 2 | | 25 | 1 | | 26 | 7 | | 27 | 5 | | 28 | 12 | | 29 | 5 | | 30 | 6 | | 31 | 8 | | 32 | 17 | | 33 | 21 | | 34 | 6 | | 35 | 14 | | 36 | 15 | | 37 | 6 | | 38 | 24 | | 39 | 6 | | 40 | 1 | | 41 | 8 | | 42 | 12 | | 43 | 14 | | 44 | 5 | | 45 | 10 | | 46 | 13 | | 47 | 8 | | 48 | 27 | | 49 | 7 |
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| 47.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3333333333333333 | | totalSentences | 135 | | uniqueOpeners | 45 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 91 | | matches | | 0 | "Somewhere in the back, a" | | 1 | "Then she stopped." | | 2 | "Only one person had ever" | | 3 | "Then university had pulled them" | | 4 | "Somewhere in the back, the" |
| | ratio | 0.055 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 91 | | matches | | 0 | "She hadn't planned on drinking." | | 1 | "He'd told her once that" | | 2 | "She still didn't understand what" | | 3 | "She stopped herself" | | 4 | "He poured it anyway, sliding" | | 5 | "She didn't look." | | 6 | "She was tall, maybe an" | | 7 | "She pointed at her own" | | 8 | "She pressed her thumb against" | | 9 | "She felt thinner than Aurora" | | 10 | "She took a long sip" | | 11 | "They'd been inseparable through secondary" | | 12 | "She gestured vaguely at the" | | 13 | "Her fingers traced the rim" | | 14 | "she said quietly" | | 15 | "She paused at the door" | | 16 | "She thought about the deliveries" | | 17 | "She thought about Silas and" | | 18 | "she said finally" | | 19 | "She didn't know if she'd" |
| | ratio | 0.264 | |
| 14.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 81 | | totalSentences | 91 | | matches | | 0 | "The rain had driven her" | | 1 | "That was the only reason" | | 2 | "She hadn't planned on drinking." | | 3 | "The delivery rounds had finished" | | 4 | "The bar was quieter than" | | 5 | "A Tuesday night in Soho," | | 6 | "Silas stood behind the counter," | | 7 | "He'd told her once that" | | 8 | "She still didn't understand what" | | 9 | "Silas called out" | | 10 | "She stopped herself" | | 11 | "He poured it anyway, sliding" | | 12 | "Aurora wrapped her hands around" | | 13 | "The television above the bar" | | 14 | "She didn't look." | | 15 | "The door opened again." | | 16 | "A woman stepped in, shaking" | | 17 | "She was tall, maybe an" | | 18 | "The woman glanced around the" | | 19 | "The name hit Aurora like" |
| | ratio | 0.89 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 91 | | matches | (empty) | | ratio | 0 | |
| 37.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 5 | | matches | | 0 | "But the green neon sign had glowed through the downpour like a beacon, and her jacket was soaked through, and sometimes convenience was the only logic that matt…" | | 1 | "Silas stood behind the counter, polishing a glass with the slow patience of a man who had learned that everything worth doing took time." | | 2 | "She was tall, maybe an inch taller than Aurora, with close-cropped blonde hair and a sharp jawline that seemed familiar in a way Aurora couldn't place." | | 3 | "The woman glanced around the bar, her eyes landing on Aurora for a moment, then moving on." | | 4 | "The Imogen she remembered had been wild, careless, the kind of girl who snuck out to parties and dared Aurora to do things she'd never have done on her own." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 24 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 1 | | fancyTags | | 0 | "Aurora corrected (correct)" |
| | dialogueSentences | 60 | | tagDensity | 0.15 | | leniency | 0.3 | | rawRatio | 0.111 | | effectiveRatio | 0.033 | |