| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 85.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1763 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "softly" | | 1 | "suddenly" | | 2 | "very" | | 3 | "lightly" | | 4 | "slightly" |
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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) | |
| 40.44% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1763 | | totalAiIsms | 21 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | word | "down her spine" | | count | 1 |
| | 12 | | | 13 | | | 14 | |
| | highlights | | 0 | "unreadable" | | 1 | "familiar" | | 2 | "vibrated" | | 3 | "reminder" | | 4 | "pulse" | | 5 | "predator" | | 6 | "silence" | | 7 | "fractured" | | 8 | "trembled" | | 9 | "tension" | | 10 | "unravel" | | 11 | "down her spine" | | 12 | "traced" | | 13 | "fleeting" | | 14 | "warmth" |
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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 | 173 | | matches | (empty) | |
| 60.28% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 10 | | hedgeCount | 0 | | narrationSentences | 173 | | filterMatches | | 0 | "look" | | 1 | "think" | | 2 | "know" | | 3 | "look see" | | 4 | "see" |
| | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 173 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1763 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 13 | | matches | | 0 | "You look exhausted, he said." | | 1 | "Eva is in Cardiff for the week, Rory said, closing the door and locking it out of habit." | | 2 | "I left money for the window, he said quietly." | | 3 | "I am sorry, he said." | | 4 | "You do not get to do this, she said." | | 5 | "You terrify me too, she admitted." | | 6 | "I am not good at staying, he murmured." | | 7 | "You do not get to call yourself fractured and expect me to agree, she said." | | 8 | "Then help me, he said." | | 9 | "Take off your shoes, she said." | | 10 | "When they broke apart, breathing hard, foreheads resting together, he whispered something in French against her mouth." | | 11 | "You are still terrible at knocking, she murmured." | | 12 | "I will practice, he said." |
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| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 52 | | wordCount | 1763 | | uniqueNames | 17 | | maxNameDensity | 1.02 | | worstName | "You" | | maxWindowNameDensity | 4 | | worstWindowName | "You" | | discoveredNames | | Moreau | 1 | | French-accented | 1 | | English | 1 | | Lucien | 7 | | Eva | 4 | | Cardiff | 1 | | Rory | 4 | | Brick | 2 | | Lane | 2 | | Tuesday | 1 | | French | 3 | | Aurora | 1 | | Shoreditch | 1 | | Evan | 1 | | London | 1 | | You | 18 | | Ptolemy | 3 |
| | persons | | 0 | "Moreau" | | 1 | "Lucien" | | 2 | "Eva" | | 3 | "Rory" | | 4 | "Evan" | | 5 | "You" | | 6 | "Ptolemy" |
| | places | | 0 | "Cardiff" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "Shoreditch" | | 4 | "London" |
| | globalScore | 0.99 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 114 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like a ghost she had spent half a" | | 1 | "felt like stepping off a ledge" |
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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 | 1763 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 173 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 44.08 | | std | 25.15 | | cv | 0.571 | | sampleLengths | | 0 | 42 | | 1 | 98 | | 2 | 20 | | 3 | 26 | | 4 | 77 | | 5 | 19 | | 6 | 35 | | 7 | 88 | | 8 | 28 | | 9 | 38 | | 10 | 68 | | 11 | 19 | | 12 | 60 | | 13 | 27 | | 14 | 65 | | 15 | 23 | | 16 | 40 | | 17 | 43 | | 18 | 59 | | 19 | 10 | | 20 | 71 | | 21 | 49 | | 22 | 56 | | 23 | 78 | | 24 | 95 | | 25 | 30 | | 26 | 73 | | 27 | 23 | | 28 | 57 | | 29 | 27 | | 30 | 20 | | 31 | 24 | | 32 | 26 | | 33 | 47 | | 34 | 81 | | 35 | 62 | | 36 | 8 | | 37 | 12 | | 38 | 32 | | 39 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 173 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 329 | | matches | | 0 | "was still buttoning" | | 1 | "was keeping" | | 2 | "was only keeping" | | 3 | "was trying" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 173 | | ratio | 0.006 | | matches | | 0 | "The amber eye caught the lamplight; the black one swallowed it." |
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| 90.44% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1770 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 78 | | adverbRatio | 0.04406779661016949 | | lyAdverbCount | 23 | | lyAdverbRatio | 0.012994350282485875 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 173 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 173 | | mean | 10.19 | | std | 7.84 | | cv | 0.769 | | sampleLengths | | 0 | 10 | | 1 | 32 | | 2 | 5 | | 3 | 25 | | 4 | 19 | | 5 | 15 | | 6 | 18 | | 7 | 16 | | 8 | 5 | | 9 | 15 | | 10 | 20 | | 11 | 6 | | 12 | 5 | | 13 | 27 | | 14 | 33 | | 15 | 4 | | 16 | 8 | | 17 | 4 | | 18 | 2 | | 19 | 3 | | 20 | 10 | | 21 | 4 | | 22 | 27 | | 23 | 4 | | 24 | 21 | | 25 | 11 | | 26 | 32 | | 27 | 24 | | 28 | 18 | | 29 | 6 | | 30 | 4 | | 31 | 6 | | 32 | 18 | | 33 | 10 | | 34 | 4 | | 35 | 8 | | 36 | 13 | | 37 | 8 | | 38 | 19 | | 39 | 20 | | 40 | 3 | | 41 | 3 | | 42 | 4 | | 43 | 3 | | 44 | 2 | | 45 | 4 | | 46 | 4 | | 47 | 11 | | 48 | 16 | | 49 | 7 |
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| 37.86% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 21 | | diversityRatio | 0.2832369942196532 | | totalSentences | 173 | | uniqueOpeners | 49 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 164 | | matches | | 0 | "Instead, she stepped aside." | | 1 | "Just enough to shrink the" | | 2 | "Then his knuckles brushed her" | | 3 | "Even like this." | | 4 | "Somewhere downstairs, a door slammed" | | 5 | "Then help me, he said." | | 6 | "Then go lock the door," |
| | ratio | 0.043 | |
| 12.68% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 85 | | totalSentences | 164 | | matches | | 0 | "He wore a charcoal suit" | | 1 | "You look exhausted, he said." | | 2 | "His voice was a low" | | 3 | "He did not answer immediately." | | 4 | "His gaze dropped to her" | | 5 | "It is raining." | | 6 | "She should say no." | | 7 | "She should shut the door," | | 8 | "He moved past her with" | | 9 | "He took in the flat" | | 10 | "I am just watching the" | | 11 | "I did not come for" | | 12 | "I came for you." | | 13 | "You have a strange way" | | 14 | "His mouth twitched." | | 15 | "I tried calling." | | 16 | "You changed your number." | | 17 | "She heard the edge in" | | 18 | "She prided herself on keeping" | | 19 | "You made your position clear," |
| | ratio | 0.518 | |
| 81.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 124 | | totalSentences | 164 | | matches | | 0 | "The third deadbolt slid back" | | 1 | "Rory pulled the door open," | | 2 | "Lucien Moreau filled the doorway." | | 3 | "The dim hallway light caught" | | 4 | "He wore a charcoal suit" | | 5 | "Tonight, he just looked like" | | 6 | "You look exhausted, he said." | | 7 | "His voice was a low" | | 8 | "He did not answer immediately." | | 9 | "His gaze dropped to her" | | 10 | "The curry house downstairs vented" | | 11 | "It is raining." | | 12 | "She should say no." | | 13 | "She should shut the door," | | 14 | "He moved past her with" | | 15 | "The ferrule of his cane" | | 16 | "He took in the flat" | | 17 | "Ptolemy, Eva’s overweight tabby, emerged" | | 18 | "Eva is in Cardiff for" | | 19 | "I am just watching the" |
| | ratio | 0.756 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 6 | | totalSentences | 164 | | matches | | 0 | "Because I wanted peace." | | 1 | "Because I heard about the" | | 2 | "Because I know what runs" | | 3 | "Because the thought of you" | | 4 | "Because I keep letting you" | | 5 | "If you will have me." |
| | ratio | 0.037 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 71 | | technicalSentenceCount | 3 | | matches | | 0 | "His voice was a low scrape of French-accented English that vibrated straight through her ribs." | | 1 | "I see the woman who outthinks predators and outruns her past and still stops to feed stray cats in the rain." | | 2 | "His thumb traced her lower lip, slow, reverent, as if she were something fragile and fiercely defended." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |