| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 23 | | tagDensity | 0.348 | | leniency | 0.696 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 83.39% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 903 | | totalAiIsmAdverbs | 3 | | found | | 0 | | | 1 | | | 2 | | adverb | "barely above a whisper" | | count | 1 |
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| | highlights | | 0 | "tightly" | | 1 | "slightly" | | 2 | "barely above a whisper" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 903 | | totalAiIsms | 22 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "structure" | | 1 | "loomed" | | 2 | "glinting" | | 3 | "etching" | | 4 | "pulse" | | 5 | "quickened" | | 6 | "flicked" | | 7 | "echoed" | | 8 | "velvet" | | 9 | "etched" | | 10 | "weight" | | 11 | "almost alive" | | 12 | "whisper" | | 13 | "trembled" | | 14 | "unspoken" | | 15 | "racing" | | 16 | "pulsed" | | 17 | "resolve" | | 18 | "silence" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 68 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 68 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 81 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 10 | | totalWords | 898 | | ratio | 0.011 | | matches | | 0 | "become" | | 1 | "“The truth lies where the river forgets its name.”" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 51.82% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 713 | | uniqueNames | 7 | | maxNameDensity | 1.96 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 14 | | Quinn | 1 | | Camden | 2 | | Tube | 1 | | Eva | 8 | | Kowalski | 1 | | Thames | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Camden" | | 3 | "Eva" | | 4 | "Kowalski" |
| | places | | | globalScore | 0.518 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 898 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 81 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 22 | | mean | 40.82 | | std | 22.83 | | cv | 0.559 | | sampleLengths | | 0 | 88 | | 1 | 73 | | 2 | 47 | | 3 | 30 | | 4 | 59 | | 5 | 4 | | 6 | 62 | | 7 | 34 | | 8 | 29 | | 9 | 76 | | 10 | 12 | | 11 | 60 | | 12 | 12 | | 13 | 37 | | 14 | 35 | | 15 | 51 | | 16 | 14 | | 17 | 37 | | 18 | 50 | | 19 | 9 | | 20 | 24 | | 21 | 55 |
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| 89.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 68 | | matches | | 0 | "were lined" | | 1 | "was lined" | | 2 | "was broken" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 129 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 1 | | flaggedSentences | 5 | | totalSentences | 81 | | ratio | 0.062 | | matches | | 0 | "She inhaled deeply, letting the scent of damp soil and something sweeter—perhaps decay—fill her lungs." | | 1 | "It wasn’t just any token; the etching along its edge resembled sigils she’d seen only in the most obscure grimoires." | | 2 | "The walls were lined with graffiti—scrawls in multiple languages, some resembling the sigil, others jagged and frantic." | | 3 | "Beneath them, a locket—tarnished, its surface etched with the same sigil." | | 4 | "As she lifted it, a fragment of paper fell into her palm—a note, written in a shaky hand." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 720 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.02638888888888889 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.0125 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 81 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 81 | | mean | 11.09 | | std | 6.73 | | cv | 0.607 | | sampleLengths | | 0 | 19 | | 1 | 15 | | 2 | 21 | | 3 | 18 | | 4 | 15 | | 5 | 10 | | 6 | 20 | | 7 | 13 | | 8 | 7 | | 9 | 20 | | 10 | 3 | | 11 | 7 | | 12 | 19 | | 13 | 15 | | 14 | 6 | | 15 | 8 | | 16 | 10 | | 17 | 12 | | 18 | 7 | | 19 | 25 | | 20 | 27 | | 21 | 3 | | 22 | 1 | | 23 | 10 | | 24 | 40 | | 25 | 12 | | 26 | 15 | | 27 | 13 | | 28 | 6 | | 29 | 20 | | 30 | 9 | | 31 | 8 | | 32 | 15 | | 33 | 17 | | 34 | 14 | | 35 | 11 | | 36 | 11 | | 37 | 7 | | 38 | 5 | | 39 | 4 | | 40 | 13 | | 41 | 17 | | 42 | 11 | | 43 | 9 | | 44 | 6 | | 45 | 12 | | 46 | 9 | | 47 | 21 | | 48 | 7 | | 49 | 8 |
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| 56.79% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.37037037037037035 | | totalSentences | 81 | | uniqueOpeners | 30 | |
| 52.08% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 64 | | matches | | 0 | "Instead, they raised a hand," |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 64 | | matches | | 0 | "Her leather watch glinted dully" | | 1 | "She inhaled deeply, letting the" | | 2 | "It wasn’t just any token;" | | 3 | "Her pulse quickened." | | 4 | "Her round glasses slid down" | | 5 | "Her gaze swept the entrance" | | 6 | "She produced a worn leather" | | 7 | "She tapped a page marked" | | 8 | "she asked, her voice barely" | | 9 | "Her eyes met Harlow’s, wide" | | 10 | "she demanded, her voice steady" | | 11 | "She bent to retrieve it," | | 12 | "She glanced at Eva, whose" | | 13 | "It was a threshold." |
| | ratio | 0.219 | |
| 30.31% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 64 | | matches | | 0 | "Detective Harlow Quinn stepped off" | | 1 | "The air carried a metallic" | | 2 | "Her leather watch glinted dully" | | 3 | "The ground beneath her boots" | | 4 | "She inhaled deeply, letting the" | | 5 | "A skeletal structure loomed ahead," | | 6 | "The abandoned Tube station, its" | | 7 | "A bone token lay on" | | 8 | "Harlow knelt, fingers brushing the" | | 9 | "It wasn’t just any token;" | | 10 | "Her pulse quickened." | | 11 | "Eva Kowalski leaned against a" | | 12 | "Her round glasses slid down" | | 13 | "Harlow stood, brushing dirt from" | | 14 | "Her gaze swept the entrance" | | 15 | "Eva pushed off the pillar," | | 16 | "She produced a worn leather" | | 17 | "Harlow’s eyes narrowed." | | 18 | "Eva said, her voice low" | | 19 | "She tapped a page marked" |
| | ratio | 0.859 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 64 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 1 | | matches | | 0 | "Detective Harlow Quinn stepped off the rickety tram that had deposited her at the edge of Camden’s forgotten district." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 3 | | matches | | 0 | "Eva said, her voice low" | | 1 | "she asked, her voice barely above a whisper" | | 2 | "she demanded, her voice steady despite the adrenaline surging through her veins" |
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| 63.04% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "she murmured (murmur)" | | 1 | "she demanded (demand)" |
| | dialogueSentences | 23 | | tagDensity | 0.174 | | leniency | 0.348 | | rawRatio | 0.5 | | effectiveRatio | 0.174 | |