| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 70 | | tagDensity | 0.214 | | leniency | 0.429 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 83.95% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1246 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "really" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 55.86% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1246 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "familiar" | | 1 | "warmth" | | 2 | "tracing" | | 3 | "flickered" | | 4 | "silence" | | 5 | "unspoken" | | 6 | "fluttered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 77 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 77 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 132 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1236 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 27 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 726 | | uniqueNames | 8 | | maxNameDensity | 0.83 | | worstName | "Aurora" | | maxWindowNameDensity | 1 | | worstWindowName | "Aurora" | | discoveredNames | | Carter | 1 | | Golden | 1 | | Empress | 1 | | Bloomsbury | 1 | | Raven | 1 | | Nest | 1 | | Aurora | 6 | | London | 1 |
| | persons | | 0 | "Carter" | | 1 | "Empress" | | 2 | "Aurora" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.809 | | wordCount | 1236 | | matches | | 0 | "Not on the stool beside her, but across from her, close enough to see the small crescent-shap" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 132 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 93 | | mean | 13.29 | | std | 15.15 | | cv | 1.14 | | sampleLengths | | 0 | 101 | | 1 | 40 | | 2 | 66 | | 3 | 6 | | 4 | 33 | | 5 | 1 | | 6 | 32 | | 7 | 13 | | 8 | 8 | | 9 | 4 | | 10 | 35 | | 11 | 5 | | 12 | 3 | | 13 | 47 | | 14 | 10 | | 15 | 8 | | 16 | 17 | | 17 | 39 | | 18 | 9 | | 19 | 2 | | 20 | 30 | | 21 | 35 | | 22 | 10 | | 23 | 6 | | 24 | 15 | | 25 | 9 | | 26 | 4 | | 27 | 8 | | 28 | 2 | | 29 | 17 | | 30 | 2 | | 31 | 8 | | 32 | 7 | | 33 | 24 | | 34 | 6 | | 35 | 13 | | 36 | 3 | | 37 | 10 | | 38 | 28 | | 39 | 7 | | 40 | 5 | | 41 | 6 | | 42 | 8 | | 43 | 5 | | 44 | 2 | | 45 | 10 | | 46 | 25 | | 47 | 3 | | 48 | 17 | | 49 | 19 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 77 | | matches | | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 144 | | matches | | 0 | "was always running" | | 1 | "was tracing" | | 2 | "was standing" | | 3 | "was measuring" | | 4 | "was always listening" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 132 | | ratio | 0.068 | | matches | | 0 | "She’d been working late—Golden Empress closed at nine, and the last delivery to a flat in Bloomsbury had taken longer than expected." | | 1 | "He nodded once—polite, routine." | | 2 | "She was measuring the distance between them—the years, the silence, the unspoken things." | | 3 | "Not new lines—old ones, just more of them." | | 4 | "More than that—stripped down." | | 5 | "The man who had once been her mentor, her confidant, the man who had taught her how to read people, how to disappear, how to survive—was now a stranger wearing familiar clothes and an old face." | | 6 | "Her name was scrawled in handwriting she almost didn’t recognize—familiar, but older, rougher." | | 7 | "She looked at him then, really looked, searching his face for the boy she’d once known—the one who’d stayed over at her place after university, who’d helped her pack when she fled London, who’d promised he’d always be there." | | 8 | "She closed her eyes, fighting back something tight in her chest—anger?" |
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| 82.70% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 737 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 39 | | adverbRatio | 0.052917232021709636 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.008141112618724558 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 132 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 132 | | mean | 9.36 | | std | 7.83 | | cv | 0.836 | | sampleLengths | | 0 | 27 | | 1 | 15 | | 2 | 22 | | 3 | 37 | | 4 | 18 | | 5 | 4 | | 6 | 18 | | 7 | 3 | | 8 | 18 | | 9 | 4 | | 10 | 16 | | 11 | 25 | | 12 | 6 | | 13 | 16 | | 14 | 12 | | 15 | 5 | | 16 | 1 | | 17 | 5 | | 18 | 13 | | 19 | 14 | | 20 | 9 | | 21 | 2 | | 22 | 2 | | 23 | 8 | | 24 | 4 | | 25 | 8 | | 26 | 15 | | 27 | 8 | | 28 | 2 | | 29 | 2 | | 30 | 5 | | 31 | 3 | | 32 | 7 | | 33 | 4 | | 34 | 34 | | 35 | 2 | | 36 | 5 | | 37 | 5 | | 38 | 8 | | 39 | 10 | | 40 | 7 | | 41 | 3 | | 42 | 36 | | 43 | 9 | | 44 | 2 | | 45 | 17 | | 46 | 13 | | 47 | 5 | | 48 | 8 | | 49 | 22 |
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| 53.28% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.3560606060606061 | | totalSentences | 132 | | uniqueOpeners | 47 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 59 | | matches | | 0 | "More than that—stripped down." | | 1 | "Instead, he pulled out a" | | 2 | "Then at him." |
| | ratio | 0.051 | |
| 9.83% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 59 | | matches | | 0 | "She’d been working late—Golden Empress" | | 1 | "He nodded once—polite, routine." | | 2 | "She ordered a whiskey on" | | 3 | "She liked this hour." | | 4 | "She perched on a stool" | | 5 | "He was standing by the" | | 6 | "She didn’t answer right away." | | 7 | "She was measuring the distance" | | 8 | "He crossed the bar without" | | 9 | "he said, voice low" | | 10 | "He stopped just in front" | | 11 | "She could see it in" | | 12 | "He laughed, but it didn’t" | | 13 | "She exhaled, sharp and bitter" | | 14 | "He didn’t answer right away." | | 15 | "She looked down at her" | | 16 | "she said, voice rising just" | | 17 | "He flinched like she’d struck" | | 18 | "She stood up slowly, leaning" | | 19 | "He reached into his jacket" |
| | ratio | 0.525 | |
| 44.75% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 59 | | matches | | 0 | "The amber glow of the" | | 1 | "Aurora Carter paused mid-step, her" | | 2 | "She’d been working late—Golden Empress" | | 3 | "The streets were slick from" | | 4 | "Silas looked up from the" | | 5 | "He nodded once—polite, routine." | | 6 | "Aurora kept moving." | | 7 | "She ordered a whiskey on" | | 8 | "She liked this hour." | | 9 | "The place was nearly empty," | | 10 | "She perched on a stool" | | 11 | "That’s when she saw him" | | 12 | "He was standing by the" | | 13 | "Aurora felt her throat tighten." | | 14 | "She didn’t answer right away." | | 15 | "She was measuring the distance" | | 16 | "He crossed the bar without" | | 17 | "he said, voice low" | | 18 | "He stopped just in front" | | 19 | "Rainwater had darkened his hairline," |
| | ratio | 0.831 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 59 | | matches | (empty) | | ratio | 0 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 2 | | matches | | 0 | "The man who had once been her mentor, her confidant, the man who had taught her how to read people, how to disappear, how to survive—was now a stranger wearing …" | | 1 | "She looked at him then, really looked, searching his face for the boy she’d once known—the one who’d stayed over at her place after university, who’d helped her…" |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 3 | | matches | | 0 | "he said, voice low" | | 1 | "she said, voice rising just a fraction" | | 2 | "she asked, not turning" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 70 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0.071 | | effectiveRatio | 0.029 | |