| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said quietly [quietly]" |
| | dialogueSentences | 39 | | tagDensity | 0.436 | | leniency | 0.872 | | rawRatio | 0.059 | | effectiveRatio | 0.051 | |
| 95.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1165 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 78.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1165 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "perfect" | | 1 | "flickered" | | 2 | "warmth" | | 3 | "stomach" | | 4 | "silence" |
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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 | 58 | | matches | (empty) | |
| 93.60% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 58 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 79 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 74 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 15 | | totalWords | 1174 | | ratio | 0.013 | | matches | | 0 | "I am not keeping you. You are not staying." | | 1 | "trust no one with this." | | 2 | "know." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 865 | | uniqueNames | 10 | | maxNameDensity | 0.46 | | worstName | "Lucien" | | maxWindowNameDensity | 1 | | worstWindowName | "Eva" | | discoveredNames | | Aurora | 2 | | Eva | 3 | | Mr | 1 | | Moreau | 1 | | Ptolemy | 2 | | Tagus | 1 | | Brick | 1 | | Lane | 1 | | Lucien | 4 | | Lisbon | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Eva" | | 2 | "Mr" | | 3 | "Moreau" | | 4 | "Ptolemy" | | 5 | "Lucien" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 78.57% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 35 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.852 | | wordCount | 1174 | | matches | | 0 | "not by size, though he had a few inches on her, but by sheer composure, as if the building itself had rearranged" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 79 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 36 | | mean | 32.61 | | std | 30.32 | | cv | 0.93 | | sampleLengths | | 0 | 71 | | 1 | 15 | | 2 | 105 | | 3 | 3 | | 4 | 22 | | 5 | 3 | | 6 | 6 | | 7 | 10 | | 8 | 45 | | 9 | 13 | | 10 | 3 | | 11 | 83 | | 12 | 11 | | 13 | 20 | | 14 | 46 | | 15 | 92 | | 16 | 22 | | 17 | 13 | | 18 | 107 | | 19 | 43 | | 20 | 2 | | 21 | 19 | | 22 | 86 | | 23 | 33 | | 24 | 14 | | 25 | 52 | | 26 | 15 | | 27 | 45 | | 28 | 3 | | 29 | 17 | | 30 | 56 | | 31 | 19 | | 32 | 10 | | 33 | 2 | | 34 | 27 | | 35 | 41 |
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| 93.16% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 58 | | matches | | 0 | "been trained" | | 1 | "was slicked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 143 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 1 | | flaggedSentences | 9 | | totalSentences | 79 | | ratio | 0.114 | | matches | | 0 | "That was the mistake she'd been trained out of, the one Eva nagged her about — but it was nearly midnight, and she'd been expecting the curry house downstairs to send up the last of the day's unsold naan, the way they sometimes did when Mr." | | 1 | "Lucien Moreau filled the narrow landing the way he filled any space — not by size, though he had a few inches on her, but by sheer composure, as if the building itself had rearranged to make room." | | 2 | "A faint curve at the corner of his mouth — not quite a smile." | | 3 | "For all his polish, she'd learned to catch those flickers — they were the only honest thing about him." | | 4 | "He had to angle his shoulders to avoid a tower of Eva's research — leather-bound volumes stacked waist-high, scrolls jutting like the bones of some half-buried thing, sticky notes in three colors of ink crawling up the wall." | | 5 | "\"It's not meant to be one.\" He set the cane against the cluttered table, deliberate, and the small surrender of it — putting down the only weapon he carried openly — undid something in her chest." | | 6 | "The amber eye held hers; the black one, depthless, gave nothing." | | 7 | "Ptolemy hopped down from the sofa and wound between Lucien's polished shoes, utterly unbothered, and Aurora found she couldn't look away from the man's face — from the loose strand of hair, the rain still beading at his collar, the careful stillness of someone braced for her to throw him out." | | 8 | "For the first time, Lucien smiled — the real one, the rare one, the one she'd been stupid enough to fall for over a stolen bottle of wine." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 861 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.03832752613240418 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.009291521486643438 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 79 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 79 | | mean | 14.86 | | std | 13.51 | | cv | 0.909 | | sampleLengths | | 0 | 20 | | 1 | 46 | | 2 | 5 | | 3 | 15 | | 4 | 38 | | 5 | 30 | | 6 | 14 | | 7 | 23 | | 8 | 3 | | 9 | 18 | | 10 | 4 | | 11 | 3 | | 12 | 6 | | 13 | 10 | | 14 | 14 | | 15 | 31 | | 16 | 11 | | 17 | 2 | | 18 | 3 | | 19 | 6 | | 20 | 4 | | 21 | 43 | | 22 | 30 | | 23 | 4 | | 24 | 7 | | 25 | 12 | | 26 | 8 | | 27 | 11 | | 28 | 19 | | 29 | 9 | | 30 | 7 | | 31 | 6 | | 32 | 24 | | 33 | 38 | | 34 | 17 | | 35 | 7 | | 36 | 9 | | 37 | 4 | | 38 | 5 | | 39 | 4 | | 40 | 5 | | 41 | 8 | | 42 | 7 | | 43 | 72 | | 44 | 28 | | 45 | 4 | | 46 | 16 | | 47 | 23 | | 48 | 2 | | 49 | 10 |
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| 66.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.46835443037974683 | | totalSentences | 79 | | uniqueOpeners | 37 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 50 | | matches | | 0 | "Instead she stepped back, and" | | 1 | "Then morning, and the empty" |
| | ratio | 0.04 | |
| 20.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 50 | | matches | | 0 | "She opened the door on" | | 1 | "His charcoal suit was immaculate" | | 2 | "His platinum hair was slicked" | | 3 | "She gripped the door." | | 4 | "She'd rehearsed this moment a" | | 5 | "She laughed, and it came" | | 6 | "he said quietly" | | 7 | "She should have shut the" | | 8 | "He had to angle his" | | 9 | "He glanced at it all," | | 10 | "She watched him decide not" | | 11 | "She closed the door but" | | 12 | "*I am not keeping you." | | 13 | "You are not staying.*" | | 14 | "He turned to face her" | | 15 | "She pressed her lips together" | | 16 | "He set the cane against" | | 17 | "she said, unsteady" | | 18 | "He took a half step" | | 19 | "His jaw tightened." |
| | ratio | 0.5 | |
| 40.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 50 | | matches | | 0 | "The three deadbolts gave one" | | 1 | "That was the mistake she'd" | | 2 | "Rahman took pity on her." | | 3 | "She opened the door on" | | 4 | "Lucien Moreau filled the narrow" | | 5 | "His charcoal suit was immaculate" | | 6 | "His platinum hair was slicked" | | 7 | "The accent did what it" | | 8 | "She gripped the door." | | 9 | "A faint curve at the" | | 10 | "That was the trouble." | | 11 | "She'd rehearsed this moment a" | | 12 | "She laughed, and it came" | | 13 | "Something flickered across his face" | | 14 | "he said quietly" | | 15 | "She should have shut the" | | 16 | "He had to angle his" | | 17 | "He glanced at it all," | | 18 | "She watched him decide not" | | 19 | "She closed the door but" |
| | ratio | 0.84 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 50 | | matches | (empty) | | ratio | 0 | |
| 57.14% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 3 | | matches | | 0 | "Lucien Moreau filled the narrow landing the way he filled any space — not by size, though he had a few inches on her, but by sheer composure, as if the building…" | | 1 | "His charcoal suit was immaculate despite the rain that had started an hour ago, the shoulders dark with damp, the ivory handle of his cane catching the bare bul…" | | 2 | "Behind her, Ptolemy slunk along the back of the sofa, tail flicking, taking in the visitor with the indifferent suspicion of a cat who had seen worse come throu…" |
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| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 1 | | matches | | |
| 98.72% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 2 | | fancyTags | | 0 | "She laughed (laugh)" | | 1 | "She pressed (press)" |
| | dialogueSentences | 39 | | tagDensity | 0.308 | | leniency | 0.615 | | rawRatio | 0.167 | | effectiveRatio | 0.103 | |