| 27.59% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 26 | | adverbTagCount | 5 | | adverbTags | | 0 | "she headed back [back]" | | 1 | "The name felt like [like]" | | 2 | "He looked around [around]" | | 3 | "He sounded almost [almost]" | | 4 | "he said softly [softly]" |
| | dialogueSentences | 58 | | tagDensity | 0.448 | | leniency | 0.897 | | rawRatio | 0.192 | | effectiveRatio | 0.172 | |
| 90.37% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1557 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "really" | | 2 | "softly" |
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| 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) | |
| 64.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1557 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "scanned" | | 1 | "echo" | | 2 | "scanning" | | 3 | "warmth" | | 4 | "familiar" | | 5 | "pang" | | 6 | "silence" | | 7 | "measured" |
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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 | 128 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 128 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 158 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 55 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1539 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 1238 | | uniqueNames | 15 | | maxNameDensity | 0.65 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Nathan" | | discoveredNames | | Aurora | 7 | | Carter | 1 | | Raven | 2 | | Nest | 2 | | London | 1 | | Blackwood | 1 | | Nathan | 6 | | Fraser | 1 | | Cardiff | 1 | | University | 1 | | Silas | 8 | | Starling | 1 | | Evan | 2 | | Golden | 1 | | Empress | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Carter" | | 2 | "Raven" | | 3 | "Blackwood" | | 4 | "Nathan" | | 5 | "Fraser" | | 6 | "University" | | 7 | "Silas" | | 8 | "Evan" | | 9 | "Empress" |
| | places | | 0 | "London" | | 1 | "Cardiff" | | 2 | "Starling" | | 3 | "Golden" |
| | globalScore | 1 | | windowScore | 1 | |
| 32.35% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 85 | | glossingSentenceCount | 4 | | matches | | 0 | "seemed ridiculous" | | 1 | "as though weighing the words she hadn’t yet spoken" | | 2 | "as if searching for a ghost" | | 3 | "felt like a handshake half-remembered" |
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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 | 1539 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 158 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 32.74 | | std | 22.08 | | cv | 0.674 | | sampleLengths | | 0 | 103 | | 1 | 77 | | 2 | 6 | | 3 | 25 | | 4 | 50 | | 5 | 15 | | 6 | 57 | | 7 | 48 | | 8 | 33 | | 9 | 46 | | 10 | 48 | | 11 | 53 | | 12 | 10 | | 13 | 17 | | 14 | 63 | | 15 | 14 | | 16 | 14 | | 17 | 17 | | 18 | 39 | | 19 | 35 | | 20 | 14 | | 21 | 25 | | 22 | 34 | | 23 | 21 | | 24 | 11 | | 25 | 51 | | 26 | 34 | | 27 | 14 | | 28 | 43 | | 29 | 47 | | 30 | 8 | | 31 | 20 | | 32 | 20 | | 33 | 25 | | 34 | 37 | | 35 | 18 | | 36 | 16 | | 37 | 39 | | 38 | 26 | | 39 | 80 | | 40 | 32 | | 41 | 8 | | 42 | 47 | | 43 | 8 | | 44 | 4 | | 45 | 12 | | 46 | 75 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 128 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 245 | | matches | | 0 | "was waiting" | | 1 | "was talking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 16 | | semicolonCount | 4 | | flaggedSentences | 12 | | totalSentences | 158 | | ratio | 0.076 | | matches | | 0 | "Maps—ancient, yellowed—lined one wall in faded frames; black-and-white photographs of London streets and weathered faces covered the other." | | 1 | "He wore a well-worn blazer over a button-down shirt, and on his right hand gleamed the silver signet ring she remembered from childhood visits—though “childhood” felt alien now, like another life." | | 2 | "“Rory.” He used the old nickname—something she hadn’t heard in years." | | 3 | "It was early—just after six—but half the tables held regulars nursing their first rounds." | | 4 | "He looked rougher than she remembered—fewer freckles, a sharper jaw, shoulders that carried something heavier than books or late-night assignments." | | 5 | "The man—Nathan Fraser—launched himself forward, scanning the room as if searching for a ghost." | | 6 | "With each step, the years between them—six, to be precise—pressed heavier against her ribs." | | 7 | "Now his hair was cropped close; his suit fit with exacting precision." | | 8 | "She had understood—so deeply it had hurt—years ago, when she watched him drift out of her life without a trace." | | 9 | "She saw him as he must have wanted to be—brimming with ambition in Starling’s lecture hall, notes scribbled in the margins." | | 10 | "“I’ve had to be.” She thought of Evan—the ex she’d fled." | | 11 | "She hesitated, then let her story spill out in measured sentences: the early mornings at the Golden Empress, shifting through steaming trays of dumplings and noodles; the evenings at Silas’s bar, reading case law or brooding over pages she couldn’t concentrate on; the nights she stayed up planning the next day’s escape—which never came." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 474 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 13 | | adverbRatio | 0.027426160337552744 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.002109704641350211 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 158 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 158 | | mean | 9.74 | | std | 7.24 | | cv | 0.743 | | sampleLengths | | 0 | 25 | | 1 | 17 | | 2 | 22 | | 3 | 18 | | 4 | 18 | | 5 | 3 | | 6 | 13 | | 7 | 12 | | 8 | 31 | | 9 | 14 | | 10 | 7 | | 11 | 4 | | 12 | 2 | | 13 | 7 | | 14 | 11 | | 15 | 5 | | 16 | 2 | | 17 | 2 | | 18 | 25 | | 19 | 8 | | 20 | 15 | | 21 | 6 | | 22 | 9 | | 23 | 20 | | 24 | 23 | | 25 | 6 | | 26 | 8 | | 27 | 9 | | 28 | 4 | | 29 | 19 | | 30 | 16 | | 31 | 7 | | 32 | 4 | | 33 | 14 | | 34 | 5 | | 35 | 3 | | 36 | 7 | | 37 | 6 | | 38 | 20 | | 39 | 13 | | 40 | 7 | | 41 | 14 | | 42 | 14 | | 43 | 13 | | 44 | 5 | | 45 | 7 | | 46 | 8 | | 47 | 19 | | 48 | 14 | | 49 | 9 |
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| 43.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.310126582278481 | | totalSentences | 158 | | uniqueOpeners | 49 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 116 | | matches | | 0 | "Then he turned away, limping" | | 1 | "Then he walked across the" | | 2 | "Then Nathan exhaled and shook" | | 3 | "Then he stood, reached into" |
| | ratio | 0.034 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 74 | | totalSentences | 116 | | matches | | 0 | "She pulled her scarf tighter" | | 1 | "She’d climbed the narrow stairs" | | 2 | "His grey-streaked auburn hair fell" | | 3 | "He wore a well-worn blazer" | | 4 | "He glanced up as she" | | 5 | "He lifted a brow but" | | 6 | "He nodded once, setting the" | | 7 | "He used the old nickname—something" | | 8 | "It twisted in her chest." | | 9 | "she said, voice catching" | | 10 | "He gave her a patient" | | 11 | "She drifted to a corner" | | 12 | "She remembered when she’d gotten" | | 13 | "He set it down." | | 14 | "He held her gaze for" | | 15 | "She scanned the room." | | 16 | "It was early—just after six—but" | | 17 | "She wasn’t here for them." | | 18 | "She was waiting." | | 19 | "He looked rougher than she" |
| | ratio | 0.638 | |
| 33.28% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 99 | | totalSentences | 116 | | matches | | 0 | "The bell above the door" | | 1 | "She pulled her scarf tighter" | | 2 | "The bar smelled of oiled" | | 3 | "Maps—ancient, yellowed—lined one wall in" | | 4 | "She’d climbed the narrow stairs" | | 5 | "Tonight felt different." | | 6 | "Silas Blackwood stood behind the" | | 7 | "His grey-streaked auburn hair fell" | | 8 | "He wore a well-worn blazer" | | 9 | "He glanced up as she" | | 10 | "He lifted a brow but" | | 11 | "Aurora forced a smile." | | 12 | "He nodded once, setting the" | | 13 | "He used the old nickname—something" | | 14 | "It twisted in her chest." | | 15 | "The was a half-pint of" | | 16 | "she said, voice catching" | | 17 | "He gave her a patient" | | 18 | "She drifted to a corner" | | 19 | "She remembered when she’d gotten" |
| | ratio | 0.853 | |
| 86.21% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 116 | | matches | | 0 | "Now his hair was cropped" | | 1 | "Now ambition had turned concrete" |
| | ratio | 0.017 | |
| 59.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 5 | | matches | | 0 | "She drifted to a corner table, her fingers brushing the small crescent-shaped scar on her left wrist without realizing it." | | 1 | "He held her gaze for a beat longer than necessary, as though weighing the words she hadn’t yet spoken." | | 2 | "He looked rougher than she remembered—fewer freckles, a sharper jaw, shoulders that carried something heavier than books or late-night assignments." | | 3 | "The man—Nathan Fraser—launched himself forward, scanning the room as if searching for a ghost." | | 4 | "She hesitated, then let her story spill out in measured sentences: the early mornings at the Golden Empress, shifting through steaming trays of dumplings and no…" |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 26 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, voice catching," | | 1 | "He paused, as though ashamed" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 58 | | tagDensity | 0.121 | | leniency | 0.241 | | rawRatio | 0.143 | | effectiveRatio | 0.034 | |