| 66.67% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 3 | | adverbTags | | 0 | "she said instead [instead]" | | 1 | "she asked quietly [quietly]" | | 2 | "he said softly [softly]" |
| | dialogueSentences | 45 | | tagDensity | 0.422 | | leniency | 0.844 | | rawRatio | 0.158 | | effectiveRatio | 0.133 | |
| 83.86% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2168 | | totalAiIsmAdverbs | 7 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
| | 2 | | | 3 | | | 4 | | | 5 | |
| | highlights | | 0 | "slowly" | | 1 | "deliberately" | | 2 | "carefully" | | 3 | "really" | | 4 | "softly" | | 5 | "very" |
| |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 67.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2168 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "silence" | | 1 | "scanned" | | 2 | "sense of" | | 3 | "flicked" | | 4 | "familiar" | | 5 | "perfect" | | 6 | "flicker" | | 7 | "weight" | | 8 | "tracing" | | 9 | "sanctuary" | | 10 | "flickered" |
| |
| 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 | 1 | | narrationSentences | 155 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 155 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 182 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2155 | | 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 | 40 | | wordCount | 1683 | | uniqueNames | 16 | | maxNameDensity | 0.65 | | worstName | "Evan" | | maxWindowNameDensity | 2 | | worstWindowName | "Evan" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Thursday | 1 | | Carter | 2 | | Yu-Fei | 2 | | Cantonese | 1 | | Hale | 1 | | Silas | 5 | | Aurora | 6 | | Evan | 11 | | Shoreditch | 1 | | Instagram | 1 | | Eva | 1 | | Cardiff | 1 | | London | 2 | | Thames | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Yu-Fei" | | 4 | "Hale" | | 5 | "Silas" | | 6 | "Aurora" | | 7 | "Evan" | | 8 | "Eva" |
| | places | | 0 | "Shoreditch" | | 1 | "Cardiff" | | 2 | "London" | | 3 | "Thames" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 105 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared behind the bar without a sound, his slight limp barely noticeable tonight" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.464 | | wordCount | 2155 | | matches | | 0 | "not the memory of her, but the woman she had become" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 182 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 73 | | mean | 29.52 | | std | 21.92 | | cv | 0.743 | | sampleLengths | | 0 | 80 | | 1 | 87 | | 2 | 24 | | 3 | 44 | | 4 | 1 | | 5 | 29 | | 6 | 32 | | 7 | 1 | | 8 | 70 | | 9 | 54 | | 10 | 30 | | 11 | 27 | | 12 | 85 | | 13 | 23 | | 14 | 28 | | 15 | 3 | | 16 | 27 | | 17 | 30 | | 18 | 50 | | 19 | 13 | | 20 | 24 | | 21 | 27 | | 22 | 16 | | 23 | 50 | | 24 | 12 | | 25 | 59 | | 26 | 2 | | 27 | 47 | | 28 | 8 | | 29 | 59 | | 30 | 10 | | 31 | 52 | | 32 | 8 | | 33 | 3 | | 34 | 13 | | 35 | 5 | | 36 | 69 | | 37 | 46 | | 38 | 40 | | 39 | 5 | | 40 | 20 | | 41 | 1 | | 42 | 35 | | 43 | 10 | | 44 | 15 | | 45 | 20 | | 46 | 47 | | 47 | 70 | | 48 | 6 | | 49 | 5 |
| |
| 98.47% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 155 | | matches | | 0 | "was gone" | | 1 | "was fixed" | | 2 | "was supposed" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 273 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 1 | | flaggedSentences | 12 | | totalSentences | 182 | | ratio | 0.066 | | matches | | 0 | "Work had been relentless—three late deliveries through clogged traffic, Yu-Fei’s muttered Cantonese curses still ringing in her ears." | | 1 | "She met his eyes—still the same stormy grey—and felt the old reflex twitch in her shoulders, the urge to make herself smaller." | | 2 | "But his hands—those were the same." | | 3 | "The faint scent of his cologne wrapped around her—something woody and expensive that used to make her feel safe." | | 4 | "Evan reached for her wrist—the scarred one—before she could pull away." | | 5 | "She studied him—the new lines at the corners of his eyes, the faint silver at his temples, the way his shoulders had broadened like he’d been lifting weights to fill some other emptiness." | | 6 | "Aurora caught his eye and the barest nod of acknowledgement passed between them—his way of asking if she needed an exit." | | 7 | "For the first time since he’d sat down, he seemed to actually look at her—not the memory of her, but the woman she had become." | | 8 | "Silas had retreated to the secret room behind the bookshelf; she could tell by the way the air felt lighter." | | 9 | "For a moment she saw the boy she had fallen in love with at seventeen—the one who wrote terrible poetry and brought her coffee exactly how she liked it and promised her the world." | | 10 | "The weight of time settled on his shoulders like the expensive coat he wore—beautiful, heavy, and no longer quite fitting right." | | 11 | "The girl who had received that scar had been fearless in a different way—reckless with her heart, generous with her trust." |
| |
| 91.89% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1157 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 57 | | adverbRatio | 0.049265341400172864 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.013828867761452032 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 182 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 182 | | mean | 11.84 | | std | 8.75 | | cv | 0.739 | | sampleLengths | | 0 | 24 | | 1 | 25 | | 2 | 18 | | 3 | 13 | | 4 | 27 | | 5 | 16 | | 6 | 18 | | 7 | 18 | | 8 | 8 | | 9 | 24 | | 10 | 12 | | 11 | 21 | | 12 | 11 | | 13 | 1 | | 14 | 7 | | 15 | 6 | | 16 | 2 | | 17 | 14 | | 18 | 22 | | 19 | 10 | | 20 | 1 | | 21 | 3 | | 22 | 1 | | 23 | 24 | | 24 | 16 | | 25 | 11 | | 26 | 6 | | 27 | 9 | | 28 | 30 | | 29 | 19 | | 30 | 5 | | 31 | 19 | | 32 | 11 | | 33 | 17 | | 34 | 10 | | 35 | 14 | | 36 | 24 | | 37 | 3 | | 38 | 29 | | 39 | 15 | | 40 | 6 | | 41 | 17 | | 42 | 9 | | 43 | 19 | | 44 | 3 | | 45 | 2 | | 46 | 7 | | 47 | 11 | | 48 | 7 | | 49 | 8 |
| |
| 52.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.35714285714285715 | | totalSentences | 182 | | uniqueOpeners | 65 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 134 | | matches | | 0 | "Only a handful of patrons" | | 1 | "Then his gaze landed on" | | 2 | "Instead she lifted her chin" | | 3 | "Simply placed a fresh glass" | | 4 | "Just a fraction, but she" |
| | ratio | 0.037 | |
| 73.73% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 49 | | totalSentences | 134 | | matches | | 0 | "It was just past nine" | | 1 | "She had come downstairs from" | | 2 | "She wanted noise that wasn’t" | | 3 | "She hadn’t expected the past" | | 4 | "She had buried it with" | | 5 | "She met his eyes—still the" | | 6 | "He looked different." | | 7 | "His jaw was harder, his" | | 8 | "He crossed the room without" | | 9 | "he said, a note of" | | 10 | "She took a slow sip" | | 11 | "He didn’t speak." | | 12 | "His attention was fixed on" | | 13 | "he said after a moment" | | 14 | "She hadn’t known she still" | | 15 | "he continued, lowering his voice" | | 16 | "It had happened for two" | | 17 | "she said instead" | | 18 | "His fingers were warm." | | 19 | "he murmured, thumb brushing the" |
| | ratio | 0.366 | |
| 64.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 106 | | totalSentences | 134 | | matches | | 0 | "The Raven’s Nest smelled of" | | 1 | "It was just past nine" | | 2 | "Aurora Carter sat at the" | | 3 | "The small crescent scar on" | | 4 | "She had come downstairs from" | | 5 | "Work had been relentless—three late" | | 6 | "She wanted noise that wasn’t" | | 7 | "She hadn’t expected the past" | | 8 | "Evan Hale stopped just inside" | | 9 | "The name hit her like" | | 10 | "She had buried it with" | | 11 | "She met his eyes—still the" | | 12 | "He looked different." | | 13 | "The boyish softness that had" | | 14 | "His jaw was harder, his" | | 15 | "The coat probably cost more" | | 16 | "He crossed the room without" | | 17 | "The faint scent of his" | | 18 | "he said, a note of" | | 19 | "She took a slow sip" |
| | ratio | 0.791 | |
| 74.63% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 134 | | matches | | 0 | "Now it tightened her throat." | | 1 | "Now she heard the calculation." |
| | ratio | 0.015 | |
| 92.56% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 71 | | technicalSentenceCount | 5 | | matches | | 0 | "The Raven’s Nest smelled of old wood, spilled stout, and the faint metallic tang of rain that had followed people in from the street." | | 1 | "Green neon from the sign above the door bled through the fogged front windows, painting watery ripples across the black-and-white photographs that lined the wal…" | | 2 | "He crossed the room without waiting for an invitation, sliding onto the stool beside her as though the last five years had been nothing more than a missed lunch…" | | 3 | "The girl who had received that scar had been fearless in a different way—reckless with her heart, generous with her trust." | | 4 | "Aurora Carter squared her shoulders and walked into the night, the weight of who she had been and who she had become balanced, finally, inside her chest like tw…" |
| |
| 98.68% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 1 | | matches | | 0 | "he murmured, thumb brushing the crescent scar" |
| |
| 83.33% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 3 | | fancyTags | | 0 | "he continued (continue)" | | 1 | "he murmured (murmur)" | | 2 | "he whispered (whisper)" |
| | dialogueSentences | 45 | | tagDensity | 0.311 | | leniency | 0.622 | | rawRatio | 0.214 | | effectiveRatio | 0.133 | |