| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 3 | | adverbTags | | 0 | "Rory’s fingers tightened around [around]" | | 1 | "Rory said quietly [quietly]" | | 2 | "So she just said [just]" |
| | dialogueSentences | 108 | | tagDensity | 0.093 | | leniency | 0.185 | | rawRatio | 0.3 | | effectiveRatio | 0.056 | |
| 90.65% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1604 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | |
| 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) | |
| 31.42% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1604 | | totalAiIsms | 22 | | found | | | highlights | | 0 | "flicked" | | 1 | "familiar" | | 2 | "stomach" | | 3 | "pulse" | | 4 | "silence" | | 5 | "tension" | | 6 | "gleaming" | | 7 | "unreadable" | | 8 | "unravel" | | 9 | "weight" |
| |
| 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 | "stomach dropped/sank" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "stomach dropped" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 145 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 145 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 233 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 13 | | totalWords | 1597 | | ratio | 0.008 | | matches | | 0 | "him" | | 1 | "You’re not going back to him. Not ever." | | 2 | "I" | | 3 | "cared" | | 4 | "he" | | 5 | "her" |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 131 | | wordCount | 1015 | | uniqueNames | 8 | | maxNameDensity | 5.22 | | worstName | "Rory" | | maxWindowNameDensity | 9 | | worstWindowName | "Eva" | | discoveredNames | | Rory | 53 | | London | 2 | | Eva | 50 | | Ptolemy | 3 | | Evan | 2 | | Silence | 1 | | Moreau | 1 | | Lucien | 19 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Ptolemy" | | 3 | "Evan" | | 4 | "Silence" | | 5 | "Moreau" | | 6 | "Lucien" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 1 | | matches | | 0 | "as if sensing the tension" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1597 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 233 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 119 | | mean | 13.42 | | std | 11.01 | | cv | 0.821 | | sampleLengths | | 0 | 67 | | 1 | 19 | | 2 | 16 | | 3 | 19 | | 4 | 16 | | 5 | 59 | | 6 | 30 | | 7 | 8 | | 8 | 15 | | 9 | 9 | | 10 | 5 | | 11 | 34 | | 12 | 6 | | 13 | 17 | | 14 | 62 | | 15 | 11 | | 16 | 27 | | 17 | 7 | | 18 | 16 | | 19 | 4 | | 20 | 10 | | 21 | 24 | | 22 | 10 | | 23 | 25 | | 24 | 3 | | 25 | 24 | | 26 | 8 | | 27 | 21 | | 28 | 11 | | 29 | 14 | | 30 | 22 | | 31 | 4 | | 32 | 6 | | 33 | 5 | | 34 | 17 | | 35 | 14 | | 36 | 8 | | 37 | 4 | | 38 | 21 | | 39 | 7 | | 40 | 16 | | 41 | 5 | | 42 | 15 | | 43 | 22 | | 44 | 6 | | 45 | 12 | | 46 | 9 | | 47 | 3 | | 48 | 7 | | 49 | 4 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 145 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 214 | | matches | | 0 | "were moving" | | 1 | "was coming" |
| |
| 93.81% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 233 | | ratio | 0.017 | | matches | | 0 | "The flat was exactly as Rory remembered—cluttered, lived-in, the kind of chaos that only made sense to Eva." | | 1 | "Rory could still see it—the way Eva’s hands had shaken when she pulled her from Evan’s flat, the way her voice had broken when she said, *You’re not going back to him." | | 2 | "Lucien Moreau stood on the other side, his platinum blond hair slicked back, his heterochromatic eyes—one amber, one black—gleaming in the dim hallway light." | | 3 | "She looked at him—really looked at him—and for the first time, she saw the weight in his eyes." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1026 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.03508771929824561 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005847953216374269 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 233 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 233 | | mean | 6.85 | | std | 5.74 | | cv | 0.838 | | sampleLengths | | 0 | 17 | | 1 | 33 | | 2 | 17 | | 3 | 6 | | 4 | 13 | | 5 | 8 | | 6 | 8 | | 7 | 11 | | 8 | 5 | | 9 | 3 | | 10 | 12 | | 11 | 4 | | 12 | 9 | | 13 | 18 | | 14 | 32 | | 15 | 10 | | 16 | 20 | | 17 | 4 | | 18 | 4 | | 19 | 11 | | 20 | 4 | | 21 | 4 | | 22 | 5 | | 23 | 2 | | 24 | 3 | | 25 | 17 | | 26 | 17 | | 27 | 2 | | 28 | 4 | | 29 | 9 | | 30 | 8 | | 31 | 6 | | 32 | 32 | | 33 | 24 | | 34 | 6 | | 35 | 5 | | 36 | 7 | | 37 | 18 | | 38 | 2 | | 39 | 3 | | 40 | 4 | | 41 | 3 | | 42 | 13 | | 43 | 3 | | 44 | 1 | | 45 | 6 | | 46 | 4 | | 47 | 7 | | 48 | 17 | | 49 | 2 |
| |
| 47.42% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.2575107296137339 | | totalSentences | 233 | | uniqueOpeners | 60 | |
| 25.06% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 133 | | matches | | 0 | "Then she turned away, her" |
| | ratio | 0.008 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 133 | | matches | | 0 | "She didn’t move" | | 1 | "She cut herself off, shaking" | | 2 | "She stopped, her breath hitching" | | 3 | "She could lie." | | 4 | "She could spin some half-truth," | | 5 | "She pressed her eye to" | | 6 | "He was dressed in one" | | 7 | "She just unlocked the deadbolts," | | 8 | "His amber eye locked onto" | | 9 | "His lips curved." | | 10 | "She looked at him—really looked" | | 11 | "She could walk away." | | 12 | "She could let Lucien handle" | | 13 | "She opened her eyes." | | 14 | "She looked at Eva, at" |
| | ratio | 0.113 | |
| 1.35% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 122 | | totalSentences | 133 | | matches | | 0 | "The door swung open before" | | 1 | "Eva stood there, her dark" | | 2 | "The scent of turmeric and" | | 3 | "Eva’s voice was half-laugh, half-accusation" | | 4 | "Rory exhaled, her breath fogging" | | 5 | "Eva’s gaze flicked over Rory’s" | | 6 | "She didn’t move" | | 7 | "Rory’s fingers tightened around the" | | 8 | "Eva hesitated, then stepped back," | | 9 | "The flat was exactly as" | | 10 | "Books teetered in precarious stacks" | | 11 | "Rory stepped inside, the familiar" | | 12 | "The door clicked shut behind" | | 13 | "Eva crossed her arms." | | 14 | "Rory set her bag down," | | 15 | "Eva’s eyebrows shot up." | | 16 | "Eva’s voice was sharp, but" | | 17 | "Eva turned away, running a" | | 18 | "The words hung between them," | | 19 | "Rory could still see it—the" |
| | ratio | 0.917 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 133 | | matches | (empty) | | ratio | 0 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 2 | | matches | | 0 | "Eva stood there, her dark curls wild as if she’d been running her hands through them all morning, her sharp brown eyes widening in a way that was equal parts su…" | | 1 | "The door clicked shut behind her, the three deadbolts sliding into place with a finality that made her stomach twist." |
| |
| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | 0 | "She stopped, her breath hitching" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 108 | | tagDensity | 0.037 | | leniency | 0.074 | | rawRatio | 0.25 | | effectiveRatio | 0.019 | |