| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said quietly [quietly]" |
| | dialogueSentences | 47 | | tagDensity | 0.383 | | leniency | 0.766 | | rawRatio | 0.056 | | effectiveRatio | 0.043 | |
| 85.96% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1424 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "very" | | 1 | "slightly" | | 2 | "really" |
| |
| 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) | |
| 68.40% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1424 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "measured" | | 1 | "stomach" | | 2 | "pulse" | | 3 | "flicker" | | 4 | "silence" | | 5 | "affection" | | 6 | "whisper" | | 7 | "shattered" | | 8 | "perfect" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 76 | | matches | (empty) | |
| 86.47% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 76 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 104 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1436 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 23 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 967 | | uniqueNames | 16 | | maxNameDensity | 0.62 | | worstName | "Lucien" | | maxWindowNameDensity | 1 | | worstWindowName | "Eva" | | discoveredNames | | Eva | 4 | | Moreau | 4 | | October | 1 | | Brick | 2 | | Lane | 2 | | Evan | 1 | | Cardiff | 1 | | Lucien | 6 | | Did | 1 | | Silence | 1 | | Started | 1 | | Rory | 3 | | Carter | 1 | | Barely | 1 | | July | 1 | | Ptolemy | 3 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Evan" | | 3 | "Lucien" | | 4 | "Did" | | 5 | "Rory" | | 6 | "Carter" | | 7 | "Ptolemy" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 93.18% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like the high ground, even though" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1436 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 104 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 28.72 | | std | 26.55 | | cv | 0.924 | | sampleLengths | | 0 | 33 | | 1 | 23 | | 2 | 56 | | 3 | 7 | | 4 | 46 | | 5 | 8 | | 6 | 30 | | 7 | 10 | | 8 | 16 | | 9 | 39 | | 10 | 71 | | 11 | 6 | | 12 | 28 | | 13 | 3 | | 14 | 6 | | 15 | 64 | | 16 | 10 | | 17 | 30 | | 18 | 46 | | 19 | 7 | | 20 | 4 | | 21 | 101 | | 22 | 4 | | 23 | 3 | | 24 | 6 | | 25 | 70 | | 26 | 6 | | 27 | 16 | | 28 | 36 | | 29 | 10 | | 30 | 1 | | 31 | 73 | | 32 | 16 | | 33 | 101 | | 34 | 9 | | 35 | 6 | | 36 | 61 | | 37 | 2 | | 38 | 57 | | 39 | 46 | | 40 | 6 | | 41 | 8 | | 42 | 71 | | 43 | 4 | | 44 | 47 | | 45 | 31 | | 46 | 15 | | 47 | 45 | | 48 | 10 | | 49 | 32 |
| |
| 96.03% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 76 | | matches | | 0 | "was owed" | | 1 | "been locked" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 173 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 2 | | flaggedSentences | 11 | | totalSentences | 104 | | ratio | 0.106 | | matches | | 0 | "The knock came again — three measured raps, unhurried, patient in a way that said the person on the other side knew exactly how long she'd been standing there deciding whether to answer." | | 1 | "Her hand hesitated on the third, and she hated herself for the hesitation — for the way her pulse had already betrayed her, hammering at her throat like it had been waiting three months for this exact moment." | | 2 | "The amber eye caught the hallway light; the black one swallowed it." | | 3 | "Every sensible part of her — the part that had survived Evan, the part that had packed a bag and fled Cardiff with nothing but a crescent-shaped scar and her mother's old suitcase — said no." | | 4 | "He set his cane against the arm of Eva's sagging sofa, unbuttoned his jacket, and sat — uninvited, unhurried, folding himself into the mess of the flat with the ease of a man who had never once doubted he'd be welcome anywhere." | | 5 | "\"Eva is in Edinburgh until Sunday. She told me herself.\" He glanced up, and there it was — the thing she'd been dreading, the tiredness under the polish." | | 6 | "The name from that night — the night at the docks, the thing with too many teeth, Lucien's blade sliding from his cane like a whispered secret, and after, in the alley, his hands on her face and his mouth on hers and the world gone narrow and bright and terrifying." | | 7 | "\"One you earned.\" He leaned forward, elbows on his knees, and for the first time the fixer mask slipped — just a fraction, just enough to show the man underneath, the one she'd spent ninety-one nights trying not to think about." | | 8 | "Rain made runnels of the glass; Brick Lane shone below in smears of neon and sodium." | | 9 | "\"That a woman with your future had no business tangled in mine. I very nearly believed it. And then tonight something with my father's accent started asking for you by name, and I understood—\" a fracture in the polish, raw as wire, \"—that I could live with you hating me. I could not live with the alternative.\"" | | 10 | "Rory looked at the man in the middle of her best friend's cluttered flat — rain-soaked, uninvited, offering her a door she both wanted and feared to close — and felt something in her chest that had been locked since July finally, treacherously, turn over." |
| |
| 95.54% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 887 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 40 | | adverbRatio | 0.04509582863585118 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.006764374295377677 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 104 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 104 | | mean | 13.81 | | std | 13.95 | | cv | 1.01 | | sampleLengths | | 0 | 33 | | 1 | 23 | | 2 | 32 | | 3 | 9 | | 4 | 1 | | 5 | 14 | | 6 | 7 | | 7 | 5 | | 8 | 3 | | 9 | 38 | | 10 | 4 | | 11 | 4 | | 12 | 15 | | 13 | 12 | | 14 | 3 | | 15 | 10 | | 16 | 8 | | 17 | 4 | | 18 | 4 | | 19 | 36 | | 20 | 3 | | 21 | 16 | | 22 | 47 | | 23 | 8 | | 24 | 6 | | 25 | 7 | | 26 | 4 | | 27 | 5 | | 28 | 12 | | 29 | 3 | | 30 | 6 | | 31 | 9 | | 32 | 42 | | 33 | 3 | | 34 | 10 | | 35 | 6 | | 36 | 4 | | 37 | 28 | | 38 | 2 | | 39 | 4 | | 40 | 8 | | 41 | 34 | | 42 | 7 | | 43 | 4 | | 44 | 12 | | 45 | 7 | | 46 | 5 | | 47 | 51 | | 48 | 5 | | 49 | 3 |
| |
| 67.95% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.4423076923076923 | | totalSentences | 104 | | uniqueOpeners | 46 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 66 | | matches | | 0 | "Then the second." | | 1 | "Of course he had." | | 2 | "Somewhere below, the curry house's" | | 3 | "Barely a whisper" |
| | ratio | 0.061 | |
| 56.36% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 66 | | matches | | 0 | "She opened the first deadbolt." | | 1 | "Her hand hesitated on the" | | 2 | "She opened the door." | | 3 | "His voice was lower than" | | 4 | "She stepped aside." | | 5 | "He moved past her into" | | 6 | "She shut the door" | | 7 | "He set his cane against" | | 8 | "She stayed standing." | | 9 | "He glanced up, and there" | | 10 | "She crossed her arms and" | | 11 | "he said quietly" | | 12 | "She hadn't heard it in" | | 13 | "He leaned forward, elbows on" | | 14 | "His mouth twitched." | | 15 | "He said it plainly, no" | | 16 | "He traded, he brokered, he" | | 17 | "She pressed her shoulders harder" | | 18 | "He gestured at the walls," | | 19 | "She stared at him." |
| | ratio | 0.409 | |
| 88.79% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 66 | | matches | | 0 | "The knock came again —" | | 1 | "Rory looked through the peephole," | | 2 | "Lucien Moreau stood in the" | | 3 | "A charcoal suit on Brick" | | 4 | "Ptolemy wound between her ankles," | | 5 | "She opened the first deadbolt." | | 6 | "Her hand hesitated on the" | | 7 | "The third lock turned." | | 8 | "She opened the door." | | 9 | "His voice was lower than" | | 10 | "The amber eye caught the" | | 11 | "A flicker at the corner" | | 12 | "Every sensible part of her" | | 13 | "She stepped aside." | | 14 | "He moved past her into" | | 15 | "Ptolemy immediately abandoned her to" | | 16 | "She shut the door" | | 17 | "The look he gave her" | | 18 | "He set his cane against" | | 19 | "She stayed standing." |
| | ratio | 0.742 | |
| 75.76% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 66 | | matches | | 0 | "Even distorted through the fisheye" |
| | ratio | 0.015 | |
| 28.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 4 | | matches | | 0 | "The knock came again — three measured raps, unhurried, patient in a way that said the person on the other side knew exactly how long she'd been standing there d…" | | 1 | "Every sensible part of her — the part that had survived Evan, the part that had packed a bag and fled Cardiff with nothing but a crescent-shaped scar and her mo…" | | 2 | "He set his cane against the arm of Eva's sagging sofa, unbuttoned his jacket, and sat — uninvited, unhurried, folding himself into the mess of the flat with the…" | | 3 | "Rory looked at the man in the middle of her best friend's cluttered flat — rain-soaked, uninvited, offering her a door she both wanted and feared to close — and…" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 47 | | tagDensity | 0.191 | | leniency | 0.383 | | rawRatio | 0.111 | | effectiveRatio | 0.043 | |