| 78.79% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 4 | | adverbTags | | 0 | "She turned around [around]" | | 1 | "Lucien leaned back [back]" | | 2 | "His voice cracked just [just]" | | 3 | "Lucien said smoothly [smoothly]" |
| | dialogueSentences | 66 | | tagDensity | 0.288 | | leniency | 0.576 | | rawRatio | 0.211 | | effectiveRatio | 0.121 | |
| 93.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1598 | | totalAiIsmAdverbs | 2 | | 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) | |
| 62.45% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1598 | | totalAiIsms | 12 | | found | | 0 | | | 1 | | word | "down her spine" | | count | 1 |
| | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | |
| | highlights | | 0 | "velvet" | | 1 | "down her spine" | | 2 | "rhythmic" | | 3 | "intensity" | | 4 | "weight" | | 5 | "charm" | | 6 | "chill" | | 7 | "silence" | | 8 | "predator" | | 9 | "vibrated" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "sent a shiver through" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 120 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 120 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 166 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 3 | | totalWords | 1586 | | ratio | 0.002 | | matches | | 0 | "clink" | | 1 | "tick-tock" | | 2 | "clunk" |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 1027 | | uniqueNames | 10 | | maxNameDensity | 1.75 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | French | 1 | | Eva | 2 | | Moreau | 1 | | Brick | 1 | | Lane | 1 | | Lucien | 11 | | Rory | 18 | | London | 1 | | Thames | 1 | | Evan | 1 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Lucien" | | 3 | "Rory" | | 4 | "Evan" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "London" | | 3 | "Thames" |
| | globalScore | 0.624 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 79 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a physical weight" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.631 | | wordCount | 1586 | | matches | | 0 | "Not running, but gliding" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 166 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 78 | | mean | 20.33 | | std | 15.55 | | cv | 0.765 | | sampleLengths | | 0 | 16 | | 1 | 28 | | 2 | 1 | | 3 | 31 | | 4 | 26 | | 5 | 20 | | 6 | 5 | | 7 | 30 | | 8 | 55 | | 9 | 4 | | 10 | 17 | | 11 | 38 | | 12 | 28 | | 13 | 8 | | 14 | 17 | | 15 | 2 | | 16 | 62 | | 17 | 38 | | 18 | 17 | | 19 | 17 | | 20 | 7 | | 21 | 3 | | 22 | 32 | | 23 | 21 | | 24 | 9 | | 25 | 26 | | 26 | 40 | | 27 | 6 | | 28 | 28 | | 29 | 23 | | 30 | 9 | | 31 | 49 | | 32 | 3 | | 33 | 40 | | 34 | 17 | | 35 | 5 | | 36 | 15 | | 37 | 7 | | 38 | 40 | | 39 | 18 | | 40 | 41 | | 41 | 8 | | 42 | 16 | | 43 | 7 | | 44 | 42 | | 45 | 1 | | 46 | 7 | | 47 | 24 | | 48 | 5 | | 49 | 4 |
| |
| 99.42% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 120 | | matches | | 0 | "been secured" | | 1 | "was slicked" |
| |
| 10.61% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 176 | | matches | | 0 | "wasn't coming" | | 1 | "wasn't lying" | | 2 | "was trying" | | 3 | "was ticking" | | 4 | "wasn't holding" |
| |
| 56.80% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 166 | | ratio | 0.03 | | matches | | 0 | "The chain rattled—a sharp, metallic staccato against the heavy timber of the doorframe." | | 1 | "Ptolemy, her tabby cat, slid into the gap between her and the intruder, hissing—a low, guttural sound that stopped the door from opening any further." | | 2 | "\"Who is it?\" Eva’s voice drifted up from the floor below—a casual question about returning a book." | | 3 | "Instead, he hovered his fingers near her ear, inches away from the fresh bruise blossoming on her jawline—a souvenir from her ex, Evan." | | 4 | "His eyes—the heterochromatic set—were terrifyingly honest." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1036 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 39 | | adverbRatio | 0.037644787644787646 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.008687258687258687 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 166 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 166 | | mean | 9.55 | | std | 6.86 | | cv | 0.718 | | sampleLengths | | 0 | 3 | | 1 | 13 | | 2 | 7 | | 3 | 21 | | 4 | 1 | | 5 | 6 | | 6 | 14 | | 7 | 11 | | 8 | 17 | | 9 | 9 | | 10 | 4 | | 11 | 16 | | 12 | 5 | | 13 | 4 | | 14 | 16 | | 15 | 3 | | 16 | 7 | | 17 | 13 | | 18 | 17 | | 19 | 25 | | 20 | 4 | | 21 | 17 | | 22 | 8 | | 23 | 4 | | 24 | 3 | | 25 | 23 | | 26 | 10 | | 27 | 10 | | 28 | 3 | | 29 | 1 | | 30 | 4 | | 31 | 8 | | 32 | 8 | | 33 | 9 | | 34 | 2 | | 35 | 19 | | 36 | 26 | | 37 | 17 | | 38 | 12 | | 39 | 8 | | 40 | 18 | | 41 | 17 | | 42 | 4 | | 43 | 7 | | 44 | 6 | | 45 | 2 | | 46 | 5 | | 47 | 3 | | 48 | 5 | | 49 | 6 |
| |
| 44.58% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.2710843373493976 | | totalSentences | 166 | | uniqueOpeners | 45 | |
| 30.86% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 108 | | matches | | 0 | "Instead, he hovered his fingers" |
| | ratio | 0.009 | |
| 42.22% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 108 | | matches | | 0 | "She stood just a crack" | | 1 | "She didn't say his last" | | 2 | "She tightened her grip." | | 3 | "He didn't knock again." | | 4 | "His knuckles grazed the wood," | | 5 | "It hadn't been secured from" | | 6 | "Her apartment was twenty steps" | | 7 | "She knew better." | | 8 | "She turned her back on" | | 9 | "It was small." | | 10 | "She looked at the door," | | 11 | "He stood there like he" | | 12 | "His tailored charcoal suit was" | | 13 | "He held an ivory-handled cane" | | 14 | "His platinum blond hair was" | | 15 | "He just kept his eyes" | | 16 | "He took a step forward." | | 17 | "It wasn't coming from the" | | 18 | "she said, her voice steadier" | | 19 | "She rubbed her left wrist," |
| | ratio | 0.444 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 100 | | totalSentences | 108 | | matches | | 0 | "The deadbolt clicked." | | 1 | "The chain rattled—a sharp, metallic" | | 2 | "Rory didn't open it all" | | 3 | "She stood just a crack" | | 4 | "She didn't say his last" | | 5 | "Sandalwood and old dust, mixed" | | 6 | "The accent was still a" | | 7 | "She tightened her grip." | | 8 | "He didn't knock again." | | 9 | "His knuckles grazed the wood," | | 10 | "The deadbolt jiggled." | | 11 | "It hadn't been secured from" | | 12 | "Rory stepped back, her sneaker" | | 13 | "Her apartment was twenty steps" | | 14 | "Ptolemy, her tabby cat, slid" | | 15 | "The chain pulled taut with" | | 16 | "Rory didn't fight it." | | 17 | "She knew better." | | 18 | "She turned her back on" | | 19 | "The flat smelled of stale" |
| | ratio | 0.926 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 108 | | matches | (empty) | | ratio | 0 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 4 | | matches | | 0 | "His knuckles grazed the wood, a deliberate, slow movement that sent a shiver down her spine." | | 1 | "Ptolemy, her tabby cat, slid into the gap between her and the intruder, hissing—a low, guttural sound that stopped the door from opening any further." | | 2 | "One amber eye, the other deep black, watched her with an intensity that felt like a physical weight." | | 3 | "The menace evaporated, replaced by a hungry intensity that made her knees weak." |
| |
| 46.05% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 3 | | matches | | 0 | "she said, her voice steadier than she felt" | | 1 | "Rory snapped, the words tumbling out before she could stop them" | | 2 | "He reached out, his fingers brushing against her cheek" |
| |
| 74.24% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 5 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "he murmured (murmur)" | | 2 | "Rory snapped (snap)" | | 3 | "Rory laughed (laugh)" | | 4 | "he murmured (murmur)" |
| | dialogueSentences | 66 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0.455 | | effectiveRatio | 0.152 | |