| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said quietly [quietly]" |
| | dialogueSentences | 56 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.071 | | effectiveRatio | 0.036 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 987 | | 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) | |
| 64.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 987 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "silence" | | 1 | "disrupting" | | 2 | "traced" | | 3 | "charged" | | 4 | "pulse" | | 5 | "familiar" | | 6 | "shattered" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "clenched jaw/fists" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "clenched into fists" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 76 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 76 | | filterMatches | (empty) | | hedgeMatches | | |
| 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 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 982 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 52.60% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 616 | | uniqueNames | 5 | | maxNameDensity | 1.95 | | worstName | "Lucien" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Lucien | 12 | | Ptolemy | 3 | | Eva | 1 | | Rory | 11 | | London | 1 |
| | persons | | 0 | "Lucien" | | 1 | "Ptolemy" | | 2 | "Eva" | | 3 | "Rory" |
| | places | | | globalScore | 0.526 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 982 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 116 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 18.88 | | std | 13.18 | | cv | 0.698 | | sampleLengths | | 0 | 38 | | 1 | 13 | | 2 | 20 | | 3 | 12 | | 4 | 31 | | 5 | 45 | | 6 | 10 | | 7 | 13 | | 8 | 26 | | 9 | 14 | | 10 | 22 | | 11 | 31 | | 12 | 12 | | 13 | 9 | | 14 | 22 | | 15 | 45 | | 16 | 5 | | 17 | 52 | | 18 | 5 | | 19 | 6 | | 20 | 16 | | 21 | 17 | | 22 | 14 | | 23 | 9 | | 24 | 9 | | 25 | 35 | | 26 | 7 | | 27 | 7 | | 28 | 16 | | 29 | 31 | | 30 | 18 | | 31 | 30 | | 32 | 20 | | 33 | 6 | | 34 | 6 | | 35 | 39 | | 36 | 9 | | 37 | 13 | | 38 | 45 | | 39 | 38 | | 40 | 29 | | 41 | 8 | | 42 | 6 | | 43 | 3 | | 44 | 9 | | 45 | 47 | | 46 | 9 | | 47 | 13 | | 48 | 10 | | 49 | 11 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 76 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 118 | | matches | (empty) | |
| 68.97% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 116 | | ratio | 0.026 | | matches | | 0 | "The deadbolts on the door behind her gleamed under the dim hallway light—three of them, all engaged." | | 1 | "\"Reasons you couldn't share? Not even a note?\" She stepped closer, close enough that he caught the faint scent of her shampoo—something citrusy." | | 2 | "The taste of her was familiar—mint and something sweet, like honey." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 621 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 11 | | adverbRatio | 0.017713365539452495 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.00322061191626409 | |
| 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 | 8.47 | | std | 5.99 | | cv | 0.707 | | sampleLengths | | 0 | 11 | | 1 | 17 | | 2 | 10 | | 3 | 6 | | 4 | 7 | | 5 | 11 | | 6 | 9 | | 7 | 5 | | 8 | 7 | | 9 | 10 | | 10 | 4 | | 11 | 17 | | 12 | 7 | | 13 | 9 | | 14 | 14 | | 15 | 15 | | 16 | 7 | | 17 | 3 | | 18 | 8 | | 19 | 5 | | 20 | 19 | | 21 | 7 | | 22 | 6 | | 23 | 8 | | 24 | 13 | | 25 | 5 | | 26 | 4 | | 27 | 23 | | 28 | 8 | | 29 | 3 | | 30 | 9 | | 31 | 9 | | 32 | 10 | | 33 | 5 | | 34 | 7 | | 35 | 12 | | 36 | 33 | | 37 | 3 | | 38 | 2 | | 39 | 36 | | 40 | 16 | | 41 | 2 | | 42 | 3 | | 43 | 6 | | 44 | 5 | | 45 | 11 | | 46 | 11 | | 47 | 6 | | 48 | 4 | | 49 | 8 |
| |
| 58.05% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.35344827586206895 | | totalSentences | 116 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 70 | | matches | (empty) | | ratio | 0 | |
| 20.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 70 | | matches | | 0 | "Her bright blue eyes narrowed" | | 1 | "She crossed her arms" | | 2 | "She didn't look down." | | 3 | "He tapped his cane against" | | 4 | "Her fingers twitched at her" | | 5 | "She stepped closer, close enough" | | 6 | "His jaw tightened." | | 7 | "Her gaze remained locked on" | | 8 | "He set his cane against" | | 9 | "Her lips parted." | | 10 | "He ran a hand through" | | 11 | "Her hands clenched into fists." | | 12 | "He stepped forward, closing the" | | 13 | "Her chin lifted, defiance flashing" | | 14 | "His voice dropped, low and" | | 15 | "Her voice cracked" | | 16 | "He reached for her, his" | | 17 | "She flinched but didn't pull" | | 18 | "he said quietly" | | 19 | "Her eyes searched his face," |
| | ratio | 0.5 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 70 | | matches | | 0 | "The door swung open before" | | 1 | "Rory stood there, her black" | | 2 | "The scent of ginger and" | | 3 | "Her bright blue eyes narrowed" | | 4 | "Lucien adjusted his grip on" | | 5 | "She crossed her arms" | | 6 | "Ptolemy, Eva's tabby cat, wound" | | 7 | "She didn't look down." | | 8 | "The deadbolts on the door" | | 9 | "Lucien stepped forward, forcing her" | | 10 | "The flat smelled of old" | | 11 | "Books teetered in stacks on" | | 12 | "A map of London's underground" | | 13 | "Rory tossed the dish towel" | | 14 | "He tapped his cane against" | | 15 | "Her fingers twitched at her" | | 16 | "Silence stretched between them, thick" | | 17 | "Lucien exhaled through his nose." | | 18 | "She stepped closer, close enough" | | 19 | "His jaw tightened." |
| | ratio | 0.986 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 70 | | matches | (empty) | | ratio | 0 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 2 | | matches | | 0 | "Rory stiffened for a heartbeat before melting into him, her hands fisting in the lapels of his suit." | | 1 | "Lucien groaned against her mouth, his free hand sliding down to grip her hip, pulling her flush against him." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "he corrected (correct)" |
| | dialogueSentences | 56 | | tagDensity | 0.054 | | leniency | 0.107 | | rawRatio | 0.333 | | effectiveRatio | 0.036 | |