| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 26 | | tagDensity | 0.269 | | leniency | 0.538 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 774 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 80.62% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 774 | | totalAiIsms | 3 | | found | | | highlights | | |
| 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 | 51 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 51 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 70 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 774 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 14 | | wordCount | 619 | | uniqueNames | 8 | | maxNameDensity | 0.48 | | worstName | "Lucien" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Eva" | | discoveredNames | | Ptolemy | 2 | | Rory | 2 | | Thursday | 1 | | Lucien | 3 | | Moreau | 1 | | Soho | 1 | | Eva | 3 | | Cheapside | 1 |
| | persons | | 0 | "Ptolemy" | | 1 | "Rory" | | 2 | "Lucien" | | 3 | "Moreau" | | 4 | "Eva" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 29 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a small invasion, something p" | | 1 | "not quite sitting, occupying the space in that particular way of his, like a man who'd decided every room was a negotiation he'd already won" |
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| 70.80% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.292 | | wordCount | 774 | | matches | | 0 | "Not an invitation, exactly, but the door swung wide enough" |
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| 71.43% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 70 | | matches | | 0 | "used that name" | | 1 | "meant that it" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 20.92 | | std | 20.86 | | cv | 0.997 | | sampleLengths | | 0 | 37 | | 1 | 1 | | 2 | 6 | | 3 | 22 | | 4 | 9 | | 5 | 1 | | 6 | 1 | | 7 | 56 | | 8 | 13 | | 9 | 47 | | 10 | 76 | | 11 | 7 | | 12 | 4 | | 13 | 28 | | 14 | 25 | | 15 | 5 | | 16 | 7 | | 17 | 45 | | 18 | 33 | | 19 | 23 | | 20 | 7 | | 21 | 25 | | 22 | 56 | | 23 | 9 | | 24 | 1 | | 25 | 2 | | 26 | 50 | | 27 | 23 | | 28 | 2 | | 29 | 34 | | 30 | 22 | | 31 | 5 | | 32 | 1 | | 33 | 5 | | 34 | 71 | | 35 | 2 | | 36 | 13 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 51 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 114 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 70 | | ratio | 0 | | matches | (empty) | |
| 94.53% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 627 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.046251993620414676 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.011164274322169059 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 70 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 70 | | mean | 11.06 | | std | 9.32 | | cv | 0.843 | | sampleLengths | | 0 | 37 | | 1 | 1 | | 2 | 6 | | 3 | 5 | | 4 | 17 | | 5 | 9 | | 6 | 1 | | 7 | 1 | | 8 | 4 | | 9 | 15 | | 10 | 25 | | 11 | 7 | | 12 | 5 | | 13 | 3 | | 14 | 10 | | 15 | 22 | | 16 | 23 | | 17 | 2 | | 18 | 9 | | 19 | 22 | | 20 | 28 | | 21 | 7 | | 22 | 4 | | 23 | 6 | | 24 | 7 | | 25 | 4 | | 26 | 3 | | 27 | 25 | | 28 | 6 | | 29 | 19 | | 30 | 5 | | 31 | 7 | | 32 | 3 | | 33 | 7 | | 34 | 19 | | 35 | 16 | | 36 | 33 | | 37 | 8 | | 38 | 15 | | 39 | 7 | | 40 | 21 | | 41 | 4 | | 42 | 19 | | 43 | 7 | | 44 | 25 | | 45 | 5 | | 46 | 9 | | 47 | 1 | | 48 | 2 | | 49 | 4 |
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| 82.86% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5142857142857142 | | totalSentences | 70 | | uniqueOpeners | 36 | |
| 75.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 44 | | matches | | 0 | "Once, in a basement off" |
| | ratio | 0.023 | |
| 10.91% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 44 | | matches | | 0 | "She moved to close it." | | 1 | "His ivory-handled cane caught the" | | 2 | "She'd told him once, late" | | 3 | "He'd filed it away like" | | 4 | "She stepped back." | | 5 | "He moved through it like" | | 6 | "He didn't react." | | 7 | "He set his cane against" | | 8 | "She didn't answer." | | 9 | "He knew the difference between" | | 10 | "She'd watched him learn them" | | 11 | "He settled on the arm" | | 12 | "His voice stayed level, pleasant" | | 13 | "She pushed off the bookshelf" | | 14 | "She filled it anyway, keeping" | | 15 | "She heard him stand." | | 16 | "He stopped close enough that" | | 17 | "His expression hadn't changed, which" | | 18 | "she said, careful and precise," | | 19 | "She'd used that name once." |
| | ratio | 0.523 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 41 | | totalSentences | 44 | | matches | | 0 | "The third deadbolt clicked open" | | 1 | "She moved to close it." | | 2 | "His ivory-handled cane caught the" | | 3 | "Nobody called her that." | | 4 | "The word in his mouth" | | 5 | "She'd told him once, late" | | 6 | "He'd filed it away like" | | 7 | "The man collected useful things." | | 8 | "She stepped back." | | 9 | "He moved through it like" | | 10 | "Ptolemy materialised from behind Eva's" | | 11 | "Rory crossed her arms and" | | 12 | "The flat felt smaller with" | | 13 | "Eva's research covered every surface," | | 14 | "Lucien's eyes moved over all" | | 15 | "The amber one catalogued." | | 16 | "The black one gave nothing" | | 17 | "He didn't react." | | 18 | "He set his cane against" | | 19 | "She didn't answer." |
| | ratio | 0.932 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 44 | | matches | (empty) | | ratio | 0 | |
| 6.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 4 | | matches | | 0 | "He set his cane against the wall, peeled off his coat, and draped it over Eva's armchair with a precision that made her teeth ache." | | 1 | "He settled on the arm of the sofa, not quite sitting, occupying the space in that particular way of his, like a man who'd decided every room was a negotiation h…" | | 2 | "Heard that particular quality of silence that preceded his movement, the near-soundlessness of a man too controlled to be entirely human." | | 3 | "He stopped close enough that the cedar-and-cold-stone scent of him registered as its own specific kind of ache, the kind that lived below the ribs." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 26 | | tagDensity | 0.192 | | leniency | 0.385 | | rawRatio | 0.2 | | effectiveRatio | 0.077 | |