| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 45 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0.05 | | effectiveRatio | 0.044 | |
| 92.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1378 | | 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) | |
| 45.57% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1378 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "silence" | | 1 | "familiar" | | 2 | "calculating" | | 3 | "flicker" | | 4 | "newfound" | | 5 | "fascinating" | | 6 | "measured" | | 7 | "warmth" | | 8 | "chilled" | | 9 | "encounter" | | 10 | "whisper" | | 11 | "intensity" | | 12 | "throbbed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 88 | | matches | | |
| 94.16% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 88 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | 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 | 1378 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 985 | | uniqueNames | 12 | | maxNameDensity | 0.51 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Julian" | | discoveredNames | | Rory | 5 | | Raven | 1 | | Nest | 1 | | Thursday | 1 | | Soho | 1 | | Aurora | 1 | | Golden | 1 | | Empress | 1 | | Julian | 5 | | Silas | 1 | | Cardiff | 1 | | Eva | 2 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Julian" | | 3 | "Silas" | | 4 | "Eva" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 75.37% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like he'd sold his soul and was di" | | 1 | "felt like a confession" |
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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 | 1378 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 35.33 | | std | 19.81 | | cv | 0.561 | | sampleLengths | | 0 | 82 | | 1 | 40 | | 2 | 12 | | 3 | 82 | | 4 | 7 | | 5 | 69 | | 6 | 21 | | 7 | 22 | | 8 | 66 | | 9 | 17 | | 10 | 52 | | 11 | 29 | | 12 | 37 | | 13 | 49 | | 14 | 33 | | 15 | 41 | | 16 | 21 | | 17 | 43 | | 18 | 18 | | 19 | 20 | | 20 | 11 | | 21 | 54 | | 22 | 41 | | 23 | 30 | | 24 | 13 | | 25 | 49 | | 26 | 29 | | 27 | 14 | | 28 | 18 | | 29 | 36 | | 30 | 35 | | 31 | 38 | | 32 | 7 | | 33 | 26 | | 34 | 17 | | 35 | 51 | | 36 | 46 | | 37 | 30 | | 38 | 72 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 88 | | matches | | |
| 30.15% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 157 | | matches | | 0 | "was already settling" | | 1 | "was rattling" | | 2 | "was starting" | | 3 | "were coming" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 110 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 992 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, crescent-shaped scar" |
| | adverbCount | 33 | | adverbRatio | 0.03326612903225806 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.007056451612903226 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 12.53 | | std | 7.95 | | cv | 0.635 | | sampleLengths | | 0 | 16 | | 1 | 24 | | 2 | 22 | | 3 | 4 | | 4 | 16 | | 5 | 11 | | 6 | 7 | | 7 | 6 | | 8 | 16 | | 9 | 12 | | 10 | 3 | | 11 | 4 | | 12 | 28 | | 13 | 21 | | 14 | 26 | | 15 | 3 | | 16 | 4 | | 17 | 11 | | 18 | 19 | | 19 | 23 | | 20 | 16 | | 21 | 18 | | 22 | 3 | | 23 | 11 | | 24 | 11 | | 25 | 18 | | 26 | 11 | | 27 | 19 | | 28 | 18 | | 29 | 9 | | 30 | 8 | | 31 | 30 | | 32 | 4 | | 33 | 2 | | 34 | 2 | | 35 | 14 | | 36 | 15 | | 37 | 6 | | 38 | 8 | | 39 | 10 | | 40 | 17 | | 41 | 10 | | 42 | 24 | | 43 | 25 | | 44 | 19 | | 45 | 14 | | 46 | 11 | | 47 | 2 | | 48 | 4 | | 49 | 24 |
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| 39.70% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3090909090909091 | | totalSentences | 110 | | uniqueOpeners | 34 | |
| 40.16% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 83 | | matches | | | ratio | 0.012 | |
| 17.59% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 42 | | totalSentences | 83 | | matches | | 0 | "She didn't apologise to the" | | 1 | "She needed the silence." | | 2 | "She needed the burn of" | | 3 | "It didn't belong in a" | | 4 | "It belonged in a lecture" | | 5 | "She didn't turn immediately." | | 6 | "She took a slow sip" | | 7 | "He wore a bespoke charcoal" | | 8 | "He smiled, a practised, hollow" | | 9 | "They were the same, those" | | 10 | "He'd been a philosopher then," | | 11 | "He raised a finger to" | | 12 | "she said, her voice flat" | | 13 | "He accepted a glass of" | | 14 | "She gestured to the worn" | | 15 | "She held his gaze, refusing" | | 16 | "He swirled the liquid in" | | 17 | "she warned, her voice dropping" | | 18 | "he said, each word measured" | | 19 | "she said, the words hanging" |
| | ratio | 0.506 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 77 | | totalSentences | 83 | | matches | | 0 | "The pint glass hit the" | | 1 | "She didn't apologise to the" | | 2 | "The Raven's Nest was quiet" | | 3 | "She needed the silence." | | 4 | "She needed the burn of" | | 5 | "A familiar scent cut through" | | 6 | "Sandalwood and something sharper, like" | | 7 | "It didn't belong in a" | | 8 | "It belonged in a lecture" | | 9 | "a voice said, smooth as" | | 10 | "Rory's spine stiffened." | | 11 | "She didn't turn immediately." | | 12 | "She took a slow sip" | | 13 | "He wore a bespoke charcoal" | | 14 | "The name tasted foreign." | | 15 | "He smiled, a practised, hollow" | | 16 | "They were the same, those" | | 17 | "He'd been a philosopher then," | | 18 | "He raised a finger to" | | 19 | "The words came out sharper" |
| | ratio | 0.928 | |
| 60.24% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 83 | | matches | | 0 | "Now he looked like he'd" |
| | ratio | 0.012 | |
| 61.22% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 4 | | matches | | 0 | "She took a slow sip of her whisky, letting the fire travel down her throat, using the moment to construct a wall between her past and the present." | | 1 | "He wore a bespoke charcoal suit that cost more than her monthly rent, a far cry from the frayed tweed jackets and ink-stained fingers she remembered." | | 2 | "He'd been a philosopher then, a dreamer who argued about the ethics of artificial intelligence until the small hours in their university digs." | | 3 | "The only thing that moved was the small, crescent-shaped scar on her wrist, a pale mark against her skin that felt suddenly, acutely sensitive." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 5 | | matches | | 0 | "she said, her voice flat" | | 1 | "She held, refusing to be the first to look away" | | 2 | "He swirled, the ice clinking a soft, melancholic tune" | | 3 | "she warned, her voice dropping to a low murmur" | | 4 | "He leaned in, his voice dropping to a conspiratorial whisper" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 45 | | tagDensity | 0.156 | | leniency | 0.311 | | rawRatio | 0.143 | | effectiveRatio | 0.044 | |