| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 32 | | tagDensity | 0.313 | | leniency | 0.625 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 83.39% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 903 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "really" | | 1 | "carefully" | | 2 | "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) | |
| 55.70% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 903 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "scanning" | | 1 | "traced" | | 2 | "weight" | | 3 | "glint" | | 4 | "etched" | | 5 | "echoed" | | 6 | "stomach" |
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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 | 86 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 86 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 109 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 4 | | totalWords | 895 | | ratio | 0.004 | | matches | | 0 | "E. Kowalski" | | 1 | "Aurora Voss" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 611 | | uniqueNames | 7 | | maxNameDensity | 1.96 | | worstName | "Davies" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Davies" | | discoveredNames | | Tube | 1 | | Davies | 12 | | Patek | 1 | | Philippe | 1 | | Eva | 1 | | Camden | 1 | | Morris | 1 |
| | persons | | 0 | "Davies" | | 1 | "Patek" | | 2 | "Philippe" | | 3 | "Eva" | | 4 | "Morris" |
| | places | | | globalScore | 0.518 | | windowScore | 0.5 | |
| 91.86% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like ivory but wasn’t" |
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| 88.27% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.117 | | wordCount | 895 | | matches | | 0 | "Not one I recognised, but it had the weight of something old, something" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 109 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 22.95 | | std | 17.76 | | cv | 0.774 | | sampleLengths | | 0 | 79 | | 1 | 10 | | 2 | 29 | | 3 | 5 | | 4 | 31 | | 5 | 62 | | 6 | 6 | | 7 | 29 | | 8 | 11 | | 9 | 38 | | 10 | 4 | | 11 | 8 | | 12 | 41 | | 13 | 21 | | 14 | 54 | | 15 | 3 | | 16 | 45 | | 17 | 10 | | 18 | 15 | | 19 | 16 | | 20 | 35 | | 21 | 19 | | 22 | 27 | | 23 | 6 | | 24 | 29 | | 25 | 28 | | 26 | 51 | | 27 | 3 | | 28 | 11 | | 29 | 5 | | 30 | 17 | | 31 | 6 | | 32 | 24 | | 33 | 10 | | 34 | 13 | | 35 | 25 | | 36 | 37 | | 37 | 27 | | 38 | 5 |
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| 93.02% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 86 | | matches | | 0 | "been dropped" | | 1 | "was ruined" | | 2 | "been handled" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 119 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 109 | | ratio | 0.064 | | matches | | 0 | "His suit was expensive—tailored wool, the kind that didn’t wrinkle—but it was ruined now, stained dark at the collar and sleeves." | | 1 | "My fingers brushed against something hard beneath his sleeve—a watch." | | 2 | "The tiles were grimy, the paint peeling, but there was something else—subtle, almost imperceptible." | | 3 | "Then I saw it—a glint of metal near the third rail." | | 4 | "There was a symbol etched into it—a crescent moon cradling a star." | | 5 | "There was a second name beneath Eva’s—*Aurora Voss*." | | 6 | "He knew me well enough to recognise the look in my eyes—the same one I’d had three years ago, when Morris died." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 535 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.028037383177570093 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.003738317757009346 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 8.21 | | std | 5.97 | | cv | 0.727 | | sampleLengths | | 0 | 20 | | 1 | 20 | | 2 | 18 | | 3 | 21 | | 4 | 8 | | 5 | 2 | | 6 | 10 | | 7 | 8 | | 8 | 4 | | 9 | 3 | | 10 | 1 | | 11 | 1 | | 12 | 2 | | 13 | 5 | | 14 | 13 | | 15 | 18 | | 16 | 12 | | 17 | 7 | | 18 | 11 | | 19 | 10 | | 20 | 9 | | 21 | 13 | | 22 | 6 | | 23 | 5 | | 24 | 24 | | 25 | 2 | | 26 | 9 | | 27 | 5 | | 28 | 14 | | 29 | 5 | | 30 | 2 | | 31 | 2 | | 32 | 1 | | 33 | 1 | | 34 | 8 | | 35 | 4 | | 36 | 2 | | 37 | 6 | | 38 | 14 | | 39 | 2 | | 40 | 21 | | 41 | 4 | | 42 | 4 | | 43 | 17 | | 44 | 11 | | 45 | 10 | | 46 | 7 | | 47 | 5 | | 48 | 11 | | 49 | 10 |
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| 60.86% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.3761467889908257 | | totalSentences | 109 | | uniqueOpeners | 41 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 68 | | matches | | 0 | "Then I saw it—a glint" | | 1 | "Instead, I unfolded the receipt" | | 2 | "Somewhere down there, beneath the" |
| | ratio | 0.044 | |
| 61.18% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 68 | | matches | | 0 | "I crouched beside the body," | | 1 | "His suit was expensive—tailored wool," | | 2 | "I ignored him, my gaze" | | 3 | "His eyes were open, glassy," | | 4 | "I reached for the man’s" | | 5 | "His skin was cold, but" | | 6 | "My fingers brushed against something" | | 7 | "I stood, scanning the platform." | | 8 | "I pulled a pen from" | | 9 | "I ignored him, moving closer" | | 10 | "I stepped carefully, avoiding the" | | 11 | "I picked it up, turning" | | 12 | "I pocketed the token." | | 13 | "I stood, brushing the dust" | | 14 | "He knew I was right." | | 15 | "He just didn’t want to" | | 16 | "I held up the token" | | 17 | "I said it quietly, but" | | 18 | "I turned back to the" | | 19 | "I reached into his jacket" |
| | ratio | 0.397 | |
| 92.35% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 50 | | totalSentences | 68 | | matches | | 0 | "The air smelled of damp" | | 1 | "I crouched beside the body," | | 2 | "The victim lay sprawled on" | | 3 | "His suit was expensive—tailored wool," | | 4 | "Davies didn’t look up from" | | 5 | "I ignored him, my gaze" | | 6 | "His eyes were open, glassy," | | 7 | "Davies snapped his notebook shut" | | 8 | "I reached for the man’s" | | 9 | "His skin was cold, but" | | 10 | "The kind of cold that" | | 11 | "My fingers brushed against something" | | 12 | "This was a Patek Philippe," | | 13 | "Davies exhaled through his nose." | | 14 | "I stood, scanning the platform." | | 15 | "The tiles were grimy, the" | | 16 | "A pattern in the dust." | | 17 | "I pulled a pen from" | | 18 | "Davies crossed his arms." | | 19 | "I ignored him, moving closer" |
| | ratio | 0.735 | |
| 73.53% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 68 | | matches | | | ratio | 0.015 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 2 | | matches | | 0 | "The air smelled of damp stone and something older, something that clung to the back of my throat like copper." | | 1 | "Not one I recognised, but it had the weight of something old, something that didn’t belong in a place like this." |
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| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | 0 | "I said, but the words echoed in the hollow space" |
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| 87.50% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "Davies snapped (snap)" | | 1 | "I muttered (mutter)" |
| | dialogueSentences | 32 | | tagDensity | 0.156 | | leniency | 0.313 | | rawRatio | 0.4 | | effectiveRatio | 0.125 | |