| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 53 | | tagDensity | 0.358 | | leniency | 0.717 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1163 | | 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) | |
| 14.02% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1163 | | totalAiIsms | 20 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "loomed" | | 1 | "flicked" | | 2 | "tracing" | | 3 | "pulse" | | 4 | "silence" | | 5 | "porcelain" | | 6 | "velvet" | | 7 | "predator" | | 8 | "footsteps" | | 9 | "echoed" | | 10 | "magnetic" | | 11 | "flickered" | | 12 | "tension" | | 13 | "traced" | | 14 | "silk" | | 15 | "aligned" | | 16 | "thundered" | | 17 | "delved" | | 18 | "shattered" |
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| 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 | 162 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 162 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 195 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 21 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1151 | | ratio | 0 | | matches | (empty) | |
| 89.29% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 1 | | matches | | 0 | "The blade inside hummed, she swore, faint vibration through the floorboards." |
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| 93.18% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 57 | | wordCount | 880 | | uniqueNames | 25 | | maxNameDensity | 1.14 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Eva | 5 | | Evan | 2 | | London | 1 | | Bright | 1 | | Mayfair | 1 | | French | 1 | | Voice | 3 | | Marseille | 1 | | Long | 1 | | Towered | 1 | | Poured | 1 | | Last | 1 | | Brick | 2 | | Lane | 2 | | Forced | 1 | | Parted | 1 | | Streetlamp | 1 | | Honesty | 1 | | Challenge | 2 | | Bodies | 1 | | Laughter | 1 | | Rory | 4 | | Lucien | 10 | | Ptolemy | 9 | | Black | 3 |
| | persons | | 0 | "Eva" | | 1 | "Evan" | | 2 | "Voice" | | 3 | "Poured" | | 4 | "Forced" | | 5 | "Streetlamp" | | 6 | "Challenge" | | 7 | "Bodies" | | 8 | "Laughter" | | 9 | "Rory" | | 10 | "Lucien" | | 11 | "Ptolemy" | | 12 | "Black" |
| | places | | 0 | "London" | | 1 | "French" | | 2 | "Marseille" | | 3 | "Brick" | | 4 | "Lane" |
| | globalScore | 0.932 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | 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 | 1151 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 195 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 20.55 | | std | 13.09 | | cv | 0.637 | | sampleLengths | | 0 | 10 | | 1 | 44 | | 2 | 16 | | 3 | 5 | | 4 | 13 | | 5 | 37 | | 6 | 55 | | 7 | 29 | | 8 | 10 | | 9 | 42 | | 10 | 52 | | 11 | 14 | | 12 | 1 | | 13 | 7 | | 14 | 50 | | 15 | 22 | | 16 | 19 | | 17 | 29 | | 18 | 16 | | 19 | 34 | | 20 | 28 | | 21 | 34 | | 22 | 13 | | 23 | 34 | | 24 | 16 | | 25 | 25 | | 26 | 24 | | 27 | 19 | | 28 | 28 | | 29 | 25 | | 30 | 32 | | 31 | 18 | | 32 | 12 | | 33 | 28 | | 34 | 18 | | 35 | 34 | | 36 | 16 | | 37 | 7 | | 38 | 14 | | 39 | 7 | | 40 | 34 | | 41 | 9 | | 42 | 10 | | 43 | 36 | | 44 | 15 | | 45 | 8 | | 46 | 23 | | 47 | 9 | | 48 | 7 | | 49 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 162 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 216 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 195 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 889 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 16 | | adverbRatio | 0.01799775028121485 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0022497187851518562 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 195 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 195 | | mean | 5.9 | | std | 3.8 | | cv | 0.643 | | sampleLengths | | 0 | 10 | | 1 | 15 | | 2 | 15 | | 3 | 14 | | 4 | 6 | | 5 | 10 | | 6 | 5 | | 7 | 4 | | 8 | 7 | | 9 | 2 | | 10 | 3 | | 11 | 7 | | 12 | 11 | | 13 | 10 | | 14 | 2 | | 15 | 4 | | 16 | 5 | | 17 | 14 | | 18 | 7 | | 19 | 9 | | 20 | 20 | | 21 | 2 | | 22 | 12 | | 23 | 3 | | 24 | 4 | | 25 | 2 | | 26 | 1 | | 27 | 5 | | 28 | 4 | | 29 | 6 | | 30 | 10 | | 31 | 7 | | 32 | 12 | | 33 | 13 | | 34 | 7 | | 35 | 16 | | 36 | 2 | | 37 | 5 | | 38 | 5 | | 39 | 2 | | 40 | 1 | | 41 | 2 | | 42 | 2 | | 43 | 10 | | 44 | 3 | | 45 | 7 | | 46 | 4 | | 47 | 1 | | 48 | 6 | | 49 | 1 |
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| 99.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.6256410256410256 | | totalSentences | 195 | | uniqueOpeners | 122 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 133 | | matches | | 0 | "Of course he did." | | 1 | "Bright blue eyes met his" | | 2 | "Just her, piecing together rumours" | | 3 | "Instead, fingers grazed his sleeve." |
| | ratio | 0.03 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 133 | | matches | | 0 | "His charcoal suit hugged his" | | 1 | "She gripped the edge, knuckles" | | 2 | "He didn't smile" | | 3 | "She slammed the door, twisted" | | 4 | "He turned, cane planted." | | 5 | "She crossed arms, leaned against" | | 6 | "Her black hair fell forward," | | 7 | "His gaze flicked to the" | | 8 | "His mouth on her pulse." | | 9 | "She pushed off the door," | | 10 | "Her hand froze on a" | | 11 | "She slammed the mug down." | | 12 | "He rose, fluid, crossed to" | | 13 | "She shoved his chest, suit" | | 14 | "He didn't budge." | | 15 | "His hand caught her wrist." | | 16 | "She wrenched free, stepped back." | | 17 | "She snorted, snatched the teapot" | | 18 | "He circled the table, predator" | | 19 | "Her breath hitched." |
| | ratio | 0.248 | |
| 69.02% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 104 | | totalSentences | 133 | | matches | | 0 | "Rory wrenched the door open" | | 1 | "Lucien loomed in the narrow" | | 2 | "His charcoal suit hugged his" | | 3 | "She gripped the edge, knuckles" | | 4 | "Ptolemy slunk between her ankles," | | 5 | "He didn't smile" | | 6 | "The cane tapped once against" | | 7 | "Ptolemy bolted inside." | | 8 | "Rory stepped aside, reluctant muscles" | | 9 | "Lucien glided past, cologne trailing," | | 10 | "She slammed the door, twisted" | | 11 | "Habit from Eva's warnings." | | 12 | "The flat swallowed him whole." | | 13 | "Books teetered on every surface," | | 14 | "Ptolemy leaped onto a stack," | | 15 | "Lucien paused, surveyed the chaos" | | 16 | "Dust motes danced in the" | | 17 | "Rory crashed here after the" | | 18 | "Lucien knew that." | | 19 | "He turned, cane planted." |
| | ratio | 0.782 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 133 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 98.68% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 1 | | matches | | 0 | "Lucien peeled off, deliberate" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 53 | | tagDensity | 0.057 | | leniency | 0.113 | | rawRatio | 0.333 | | effectiveRatio | 0.038 | |