| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.17 | | leniency | 0.34 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1265 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 60.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1265 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "shattered" | | 1 | "pristine" | | 2 | "weight" | | 3 | "stark" | | 4 | "navigate" | | 5 | "calculated" | | 6 | "familiar" | | 7 | "flickered" | | 8 | "stomach" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 77 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 77 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 116 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1265 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 60 | | wordCount | 908 | | uniqueNames | 21 | | maxNameDensity | 1.87 | | worstName | "Julian" | | maxWindowNameDensity | 4 | | worstWindowName | "Julian" | | discoveredNames | | Soho | 3 | | Golden | 1 | | Empress | 1 | | London | 1 | | Cardiff | 2 | | Raven | 1 | | Nest | 2 | | Julian | 17 | | Oxfords | 1 | | Wales | 1 | | Silas | 7 | | Savile | 1 | | Row | 1 | | Berlin | 1 | | Thames | 1 | | Rory | 14 | | Casio | 1 | | Evan | 1 | | Central | 1 | | Paddington | 1 | | Tuesday | 1 |
| | persons | | 0 | "Raven" | | 1 | "Julian" | | 2 | "Oxfords" | | 3 | "Silas" | | 4 | "Rory" | | 5 | "Evan" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Cardiff" | | 3 | "Wales" | | 4 | "Savile" | | 5 | "Berlin" | | 6 | "Thames" |
| | globalScore | 0.564 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.791 | | wordCount | 1265 | | matches | | 0 | "not at the burn, but at Rory's red nylon jacket" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 116 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 63 | | mean | 20.08 | | std | 20.08 | | cv | 1 | | sampleLengths | | 0 | 29 | | 1 | 6 | | 2 | 23 | | 3 | 10 | | 4 | 22 | | 5 | 42 | | 6 | 18 | | 7 | 1 | | 8 | 44 | | 9 | 69 | | 10 | 1 | | 11 | 43 | | 12 | 19 | | 13 | 2 | | 14 | 2 | | 15 | 8 | | 16 | 4 | | 17 | 40 | | 18 | 5 | | 19 | 88 | | 20 | 28 | | 21 | 27 | | 22 | 1 | | 23 | 3 | | 24 | 5 | | 25 | 11 | | 26 | 12 | | 27 | 8 | | 28 | 36 | | 29 | 4 | | 30 | 4 | | 31 | 8 | | 32 | 12 | | 33 | 11 | | 34 | 3 | | 35 | 16 | | 36 | 7 | | 37 | 36 | | 38 | 7 | | 39 | 5 | | 40 | 13 | | 41 | 78 | | 42 | 8 | | 43 | 5 | | 44 | 22 | | 45 | 33 | | 46 | 4 | | 47 | 40 | | 48 | 12 | | 49 | 69 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 77 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 149 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 116 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 919 | | adjectiveStacks | 2 | | stackExamples | | 0 | "small crescent-shaped scar" | | 1 | "sharp, familiar black ink." |
| | adverbCount | 21 | | adverbRatio | 0.022850924918389554 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.00544069640914037 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 116 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 116 | | mean | 10.91 | | std | 7.85 | | cv | 0.72 | | sampleLengths | | 0 | 7 | | 1 | 22 | | 2 | 6 | | 3 | 10 | | 4 | 13 | | 5 | 10 | | 6 | 21 | | 7 | 1 | | 8 | 18 | | 9 | 17 | | 10 | 7 | | 11 | 2 | | 12 | 16 | | 13 | 1 | | 14 | 4 | | 15 | 7 | | 16 | 33 | | 17 | 11 | | 18 | 3 | | 19 | 21 | | 20 | 14 | | 21 | 20 | | 22 | 1 | | 23 | 17 | | 24 | 14 | | 25 | 12 | | 26 | 6 | | 27 | 13 | | 28 | 2 | | 29 | 2 | | 30 | 8 | | 31 | 4 | | 32 | 20 | | 33 | 20 | | 34 | 5 | | 35 | 9 | | 36 | 7 | | 37 | 10 | | 38 | 23 | | 39 | 20 | | 40 | 19 | | 41 | 6 | | 42 | 6 | | 43 | 16 | | 44 | 16 | | 45 | 11 | | 46 | 1 | | 47 | 3 | | 48 | 5 | | 49 | 11 |
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| 85.34% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5172413793103449 | | totalSentences | 116 | | uniqueOpeners | 60 | |
| 98.04% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 68 | | matches | | 0 | "Instead, he laid a thick" | | 1 | "Just her real name written" |
| | ratio | 0.029 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 68 | | matches | | 0 | "His silver signet ring clicked" | | 1 | "He froze halfway through unbuttoning" | | 2 | "Her father had used that" | | 3 | "He looked expensive." | | 4 | "His hair was shorn close," | | 5 | "He walked past the drunk" | | 6 | "He claimed the stool beside" | | 7 | "He didn't walk away, choosing" | | 8 | "His eyes tracked the faded" | | 9 | "His eyes, once warm and" | | 10 | "She remembered waiting at Cardiff" | | 11 | "He had already been on" | | 12 | "He downed the rest of" | | 13 | "Her bright blue eyes locked" | | 14 | "She looked past Julian toward" |
| | ratio | 0.221 | |
| 48.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 68 | | matches | | 0 | "Glass shattered against the mahogany" | | 1 | "Rory didn't flinch, just plucked" | | 2 | "Silas didn't look up from" | | 3 | "His silver signet ring clicked" | | 4 | "Rory rubbed the small crescent-shaped" | | 5 | "The heavy oak door swung" | | 6 | "A man shook out a" | | 7 | "He froze halfway through unbuttoning" | | 8 | "The scent of sweet ginger" | | 9 | "Nobody called her that." | | 10 | "Her father had used that" | | 11 | "Julian stepped into the dim" | | 12 | "He looked expensive." | | 13 | "A tailored charcoal wool suit" | | 14 | "His hair was shorn close," | | 15 | "He walked past the drunk" | | 16 | "Years ago, Julian would have" | | 17 | "Tonight, his polished leather Oxfords" | | 18 | "He claimed the stool beside" | | 19 | "Julian signalled Silas with two" |
| | ratio | 0.824 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 2 | | matches | | 0 | "Gone were the frayed jumpers, the ink-stained fingers, and the crooked smile that used to get them out of library fines." | | 1 | "His hair was shorn close, mercilessly neat, and deep grooves bracketed a mouth that had forgotten how to curve upward." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 2 | | matches | | 0 | "Rory rubbed, her thumb catching on the raised skin" | | 1 | "Julian said, his voice dropping an octave" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.085 | | leniency | 0.17 | | rawRatio | 0 | | effectiveRatio | 0 | |