| 78.79% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 25 | | adverbTagCount | 4 | | adverbTags | | 0 | "Eva nodded slowly [slowly]" | | 1 | "Eva said finally [finally]" | | 2 | "she said simply [simply]" | | 3 | "Eva said finally [finally]" |
| | dialogueSentences | 66 | | tagDensity | 0.379 | | leniency | 0.758 | | rawRatio | 0.16 | | effectiveRatio | 0.121 | |
| 76.27% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1475 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "carefully" | | 1 | "slowly" | | 2 | "really" | | 3 | "suddenly" | | 4 | "sharply" |
| |
| 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) | |
| 28.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1475 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "familiar" | | 1 | "weight" | | 2 | "throbbed" | | 3 | "methodical" | | 4 | "glint" | | 5 | "tracing" | | 6 | "whisper" | | 7 | "etched" | | 8 | "flickered" | | 9 | "unreadable" | | 10 | "silence" | | 11 | "glistening" | | 12 | "constructed" | | 13 | "unspoken" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "tears streamed down" | | count | 1 |
| | 1 | | label | "sent a shiver through" | | count | 1 |
|
| | highlights | | 0 | "tears streamed down" | | 1 | "sent a jolt through" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 67 | | matches | (empty) | |
| 78.89% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 67 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1468 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 1090 | | uniqueNames | 7 | | maxNameDensity | 1.83 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Aurora | 20 | | London | 2 | | Eva | 16 | | Silas | 2 | | Evan | 1 |
| | persons | | 0 | "Raven" | | 1 | "Aurora" | | 2 | "Eva" | | 3 | "Silas" | | 4 | "Evan" |
| | places | | | globalScore | 0.583 | | windowScore | 0.5 | |
| 16.07% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 3 | | matches | | 0 | "quite reach her bright blue eyes" | | 1 | "as if tasting it for the first time" | | 2 | "appeared beside them, his expression unreadable" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.681 | | wordCount | 1468 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 107 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 26.69 | | std | 19.95 | | cv | 0.747 | | sampleLengths | | 0 | 65 | | 1 | 64 | | 2 | 34 | | 3 | 23 | | 4 | 20 | | 5 | 29 | | 6 | 19 | | 7 | 64 | | 8 | 1 | | 9 | 79 | | 10 | 1 | | 11 | 47 | | 12 | 3 | | 13 | 35 | | 14 | 24 | | 15 | 29 | | 16 | 22 | | 17 | 37 | | 18 | 35 | | 19 | 9 | | 20 | 30 | | 21 | 32 | | 22 | 23 | | 23 | 19 | | 24 | 10 | | 25 | 56 | | 26 | 37 | | 27 | 12 | | 28 | 14 | | 29 | 24 | | 30 | 12 | | 31 | 53 | | 32 | 52 | | 33 | 4 | | 34 | 16 | | 35 | 64 | | 36 | 4 | | 37 | 19 | | 38 | 56 | | 39 | 5 | | 40 | 3 | | 41 | 52 | | 42 | 13 | | 43 | 24 | | 44 | 3 | | 45 | 8 | | 46 | 5 | | 47 | 35 | | 48 | 11 | | 49 | 15 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 67 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 181 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 107 | | ratio | 0.065 | | matches | | 0 | "Even from across the room, Aurora recognized the way she carried herself—the slight tilt of the head, the particular way she tucked a strand of hair behind her ear." | | 1 | "Time had been unkind to her childhood friend, or perhaps it had been generous—she couldn't decide which." | | 2 | "No one had called her Aurora in years—not since the accident, not since everything had changed." | | 3 | "Aurora remembered that night vividly—the way her vision had blurred, the sound of her own crying, the desperate need to escape the suffocating darkness that had settled over her life." | | 4 | "\"I thought... I thought you'd surface eventually.\" Eva's gaze met hers, and for a moment Aurora saw the reflection of their shared past in those eyes—the late-night conversations, the dreams they'd nursed together over cups of terrible university coffee, the promise they'd made to always be there for each other no matter what." | | 5 | "Aurora studied her friend's face by the light of the bar, searching for traces of the girl she'd once known—the one who'd laughed until tears streamed down her face, who'd stayed up all night talking about their futures, who'd promised that no matter where life took them, they'd always find their way back to each other." | | 6 | "Eva smiled—a real smile this time, the kind that reached her eyes and lit up her whole face." |
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| 86.69% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 326 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.05521472392638037 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.003067484662576687 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 13.72 | | std | 10.94 | | cv | 0.798 | | sampleLengths | | 0 | 32 | | 1 | 33 | | 2 | 21 | | 3 | 43 | | 4 | 18 | | 5 | 14 | | 6 | 2 | | 7 | 15 | | 8 | 8 | | 9 | 14 | | 10 | 6 | | 11 | 18 | | 12 | 11 | | 13 | 13 | | 14 | 6 | | 15 | 12 | | 16 | 23 | | 17 | 29 | | 18 | 1 | | 19 | 18 | | 20 | 7 | | 21 | 17 | | 22 | 37 | | 23 | 1 | | 24 | 14 | | 25 | 33 | | 26 | 3 | | 27 | 20 | | 28 | 13 | | 29 | 2 | | 30 | 18 | | 31 | 6 | | 32 | 23 | | 33 | 6 | | 34 | 11 | | 35 | 11 | | 36 | 13 | | 37 | 22 | | 38 | 2 | | 39 | 30 | | 40 | 5 | | 41 | 7 | | 42 | 2 | | 43 | 25 | | 44 | 5 | | 45 | 8 | | 46 | 18 | | 47 | 6 | | 48 | 17 | | 49 | 6 |
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| 68.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.4485981308411215 | | totalSentences | 107 | | uniqueOpeners | 48 | |
| 51.28% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 65 | | matches | | | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 65 | | matches | | 0 | "Her delivery bag thudded against" | | 1 | "She'd been coming here for" | | 2 | "She nodded toward the back" | | 3 | "His hazel eyes held a" | | 4 | "She hesitated, fingers unconsciously tracing" | | 5 | "They stood frozen for a" | | 6 | "She glanced around the bar," | | 7 | "She paused, choosing her words" | | 8 | "She settled onto a stool" | | 9 | "He smiled, but it didn't" | | 10 | "He poured two glasses of" | | 11 | "They fell into an awkward" | | 12 | "She'd called Eva, her lifeline," | | 13 | "she said simply" | | 14 | "They sat in contemplative silence" | | 15 | "She'd spent so long building" | | 16 | "she said after a moment" | | 17 | "They sat like that for" |
| | ratio | 0.277 | |
| 6.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 65 | | matches | | 0 | "The amber glow from the" | | 1 | "Her delivery bag thudded against" | | 2 | "She'd been coming here for" | | 3 | "Silas looked up from behind" | | 4 | "The silver signet ring on" | | 5 | "Aurora offered a tired smile," | | 6 | "She nodded toward the back" | | 7 | "His hazel eyes held a" | | 8 | "She hesitated, fingers unconsciously tracing" | | 9 | "The bell above the door" | | 10 | "A woman stood just inside," | | 11 | "The name escaped as barely" | | 12 | "The woman turned, and Aurora's" | | 13 | "Time had been unkind to" | | 14 | "Lines etched themselves around eyes" | | 15 | "They stood frozen for a" | | 16 | "The years between them stretched" | | 17 | "Eva's voice had deepened, acquired" | | 18 | "She glanced around the bar," | | 19 | "Aurora stepped forward, her delivery" |
| | ratio | 0.908 | |
| 76.92% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 65 | | matches | | 0 | "Even from across the room," |
| | ratio | 0.015 | |
| 34.63% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 5 | | matches | | 0 | "Maybe it was the way her wrist throbbed from the day's deliveries, or perhaps it was simply the weight of everything that had led her to this moment, standing i…" | | 1 | "Lines etched themselves around eyes that had once sparkled with mischief, and her dark hair, once long and flowing, was now cut short in a practical style that …" | | 2 | "Aurora remembered that night vividly—the way her vision had blurred, the sound of her own crying, the desperate need to escape the suffocating darkness that had…" | | 3 | "Aurora studied her friend's face by the light of the bar, searching for traces of the girl she'd once known—the one who'd laughed until tears streamed down her …" | | 4 | "Eva smiled—a real smile this time, the kind that reached her eyes and lit up her whole face." |
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| 85.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 25 | | uselessAdditionCount | 2 | | matches | | 0 | "Silas looked up, his weathered hands polishing a glass with methodical precision" | | 1 | "Eva took, her expression unreadable" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 66 | | tagDensity | 0.106 | | leniency | 0.212 | | rawRatio | 0.143 | | effectiveRatio | 0.03 | |