| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 1 | | adverbTags | | 0 | "He simply said [simply]" |
| | dialogueSentences | 35 | | tagDensity | 0.029 | | leniency | 0.057 | | rawRatio | 1 | | effectiveRatio | 0.057 | |
| 89.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 951 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 52.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 951 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "pulse" | | 1 | "scanned" | | 2 | "tension" | | 3 | "intensity" | | 4 | "unspoken" | | 5 | "stomach" | | 6 | "unreadable" | | 7 | "weight" |
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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 | 59 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 59 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 93 | | 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 | 2 | | markdownWords | 2 | | totalWords | 942 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 755 | | uniqueNames | 8 | | maxNameDensity | 1.46 | | worstName | "Silas" | | maxWindowNameDensity | 4 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Carter | 1 | | Rory | 2 | | Blackwood | 1 | | Aurora | 2 | | London | 1 | | Silas | 11 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Rory" | | 4 | "Blackwood" | | 5 | "Aurora" | | 6 | "Silas" |
| | places | | | globalScore | 0.772 | | windowScore | 0.333 | |
| 95.65% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 1 | | matches | | 0 | "something like tension" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 942 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 93 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 24.15 | | std | 21.93 | | cv | 0.908 | | sampleLengths | | 0 | 78 | | 1 | 104 | | 2 | 78 | | 3 | 18 | | 4 | 4 | | 5 | 39 | | 6 | 13 | | 7 | 9 | | 8 | 46 | | 9 | 29 | | 10 | 8 | | 11 | 5 | | 12 | 23 | | 13 | 26 | | 14 | 12 | | 15 | 15 | | 16 | 17 | | 17 | 21 | | 18 | 14 | | 19 | 13 | | 20 | 5 | | 21 | 8 | | 22 | 7 | | 23 | 15 | | 24 | 17 | | 25 | 13 | | 26 | 29 | | 27 | 40 | | 28 | 14 | | 29 | 26 | | 30 | 10 | | 31 | 10 | | 32 | 24 | | 33 | 9 | | 34 | 23 | | 35 | 10 | | 36 | 21 | | 37 | 26 | | 38 | 63 |
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| 87.42% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 59 | | matches | | 0 | "were lined" | | 1 | "was pulled" | | 2 | "was streaked" |
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| 34.71% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 121 | | matches | | 0 | "was wearing" | | 1 | "was running" | | 2 | "was running" |
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| 50.69% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 93 | | ratio | 0.032 | | matches | | 0 | "The neon sign above the door—green, jagged, and unmistakable—flashed once, then settled into a steady pulse, casting a sickly glow over the dimly lit room." | | 1 | "Aurora Carter—Rory, to those who knew her—stood at the bar, her fingers brushing the rim of a glass before she set it down with a sharp *clink*." | | 2 | "The photographs on the wall—old maps of foreign cities, snapshots of men in suits and women in evening gowns—seemed to watch her, their faces frozen in time." |
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| 84.54% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 763 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 44 | | adverbRatio | 0.057667103538663174 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.010484927916120577 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 93 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 93 | | mean | 10.13 | | std | 8.41 | | cv | 0.831 | | sampleLengths | | 0 | 24 | | 1 | 25 | | 2 | 29 | | 3 | 27 | | 4 | 42 | | 5 | 35 | | 6 | 7 | | 7 | 16 | | 8 | 22 | | 9 | 33 | | 10 | 17 | | 11 | 1 | | 12 | 3 | | 13 | 1 | | 14 | 9 | | 15 | 27 | | 16 | 3 | | 17 | 8 | | 18 | 5 | | 19 | 3 | | 20 | 6 | | 21 | 12 | | 22 | 27 | | 23 | 7 | | 24 | 5 | | 25 | 18 | | 26 | 6 | | 27 | 5 | | 28 | 3 | | 29 | 5 | | 30 | 7 | | 31 | 9 | | 32 | 7 | | 33 | 23 | | 34 | 3 | | 35 | 2 | | 36 | 10 | | 37 | 9 | | 38 | 6 | | 39 | 7 | | 40 | 10 | | 41 | 16 | | 42 | 5 | | 43 | 8 | | 44 | 6 | | 45 | 3 | | 46 | 10 | | 47 | 3 | | 48 | 2 | | 49 | 8 |
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| 45.70% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.21505376344086022 | | totalSentences | 93 | | uniqueOpeners | 20 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 58 | | matches | | 0 | "Then she saw the signet" | | 1 | "Then, slowly, he turned back" | | 2 | "Instead, she stepped back, her" |
| | ratio | 0.052 | |
| 13.10% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 58 | | matches | | 0 | "She was wearing a dark" | | 1 | "Her black hair was pulled" | | 2 | "She didn’t recognize the man" | | 3 | "He was taller than she" | | 4 | "His hair was streaked with" | | 5 | "She didn’t move." | | 6 | "He stepped closer, the bar" | | 7 | "She exhaled through her nose," | | 8 | "He didn’t flinch." | | 9 | "She turned away, her fingers" | | 10 | "He poured himself another drink," | | 11 | "She didn’t look at him." | | 12 | "She turned back to face" | | 13 | "He studied her for a" | | 14 | "She scoffed, though her voice" | | 15 | "He reached across the bar," | | 16 | "She pulled her hand away," | | 17 | "He simply said," | | 18 | "She nodded, her throat tight." | | 19 | "She exhaled, the breath coming" |
| | ratio | 0.517 | |
| 3.10% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 53 | | totalSentences | 58 | | matches | | 0 | "The Raven’s Nest hummed with" | | 1 | "The neon sign above the" | | 2 | "The walls were lined with" | | 3 | "Aurora Carter—Rory, to those who" | | 4 | "She was wearing a dark" | | 5 | "Her black hair was pulled" | | 6 | "She didn’t recognize the man" | | 7 | "He was taller than she" | | 8 | "His hair was streaked with" | | 9 | "Silas Blackwood turned, his voice" | | 10 | "She didn’t move." | | 11 | "The word hung between them," | | 12 | "He stepped closer, the bar" | | 13 | "She exhaled through her nose," | | 14 | "He didn’t flinch." | | 15 | "She turned away, her fingers" | | 16 | "The photographs on the wall—old" | | 17 | "Silas didn’t answer right away." | | 18 | "He poured himself another drink," | | 19 | "She didn’t look at him." |
| | ratio | 0.914 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 58 | | matches | (empty) | | ratio | 0 | |
| 37.04% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 4 | | matches | | 0 | "She was wearing a dark green sweater that hugged her shoulders, the sleeves rolled up just enough to show the faint outline of her wrist, where a small crescent…" | | 1 | "Her black hair was pulled back into a loose braid, the ends escaping in loose waves, and her bright blue eyes scanned the room with the kind of sharp focus that…" | | 2 | "His hair was streaked with gray, his beard neatly trimmed, and his hazel eyes held a quiet intensity that made her pause." | | 3 | "He reached across the bar, his fingers brushing hers for just a second before pulling back." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.029 | | leniency | 0.057 | | rawRatio | 0 | | effectiveRatio | 0 | |