| 88.78% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 3 | | adverbTags | | 0 | "Eva said softly [softly]" | | 1 | "Eva’s eyes drifted back [back]" | | 2 | "She walked back [back]" |
| | dialogueSentences | 49 | | tagDensity | 0.469 | | leniency | 0.939 | | rawRatio | 0.13 | | effectiveRatio | 0.122 | |
| 86.60% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1493 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "gently" | | 1 | "softly" | | 2 | "quickly" |
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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) | |
| 49.77% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1493 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "weight" | | 1 | "stark" | | 2 | "dancing" | | 3 | "glinting" | | 4 | "echoed" | | 5 | "perfect" | | 6 | "unreadable" | | 7 | "familiar" | | 8 | "standard" | | 9 | "magnetic" | | 10 | "resolve" | | 11 | "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 | 82 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 82 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1486 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 916 | | uniqueNames | 13 | | maxNameDensity | 2.07 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Detective | 1 | | Harlow | 2 | | Quinn | 19 | | Medical | 1 | | Examiner | 1 | | Kowalski | 1 | | Eva | 15 | | Morris | 2 | | Metropolitan | 1 | | Police | 1 | | Alistair | 1 | | Finch | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" | | 4 | "Morris" | | 5 | "Alistair" | | 6 | "Finch" |
| | places | | | globalScore | 0.463 | | windowScore | 0.333 | |
| 25.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like the robes of a minor academic" | | 1 | "as if steeling herself" | | 2 | "smelled like the unexplainable silence aft" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.673 | | wordCount | 1486 | | matches | | 0 | "not guilt, but a deep, weary knowledge" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 107 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 37.15 | | std | 25.81 | | cv | 0.695 | | sampleLengths | | 0 | 88 | | 1 | 75 | | 2 | 43 | | 3 | 54 | | 4 | 56 | | 5 | 24 | | 6 | 2 | | 7 | 67 | | 8 | 23 | | 9 | 37 | | 10 | 15 | | 11 | 37 | | 12 | 14 | | 13 | 12 | | 14 | 55 | | 15 | 44 | | 16 | 1 | | 17 | 27 | | 18 | 54 | | 19 | 26 | | 20 | 50 | | 21 | 23 | | 22 | 21 | | 23 | 19 | | 24 | 60 | | 25 | 44 | | 26 | 3 | | 27 | 61 | | 28 | 66 | | 29 | 26 | | 30 | 13 | | 31 | 70 | | 32 | 2 | | 33 | 43 | | 34 | 90 | | 35 | 10 | | 36 | 14 | | 37 | 15 | | 38 | 9 | | 39 | 93 |
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| 71.03% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 8 | | totalSentences | 82 | | matches | | 0 | "was sprawled" | | 1 | "was muffled" | | 2 | "was curled" | | 3 | "being bagged" | | 4 | "been obsessed" | | 5 | "was swallowed" | | 6 | "was strangled" | | 7 | "was hidden" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 144 | | matches | | 0 | "was looking" | | 1 | "was not pointing" | | 2 | "was quivering" | | 3 | "was arranging" | | 4 | "were spinning" |
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| 89.45% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 107 | | ratio | 0.019 | | matches | | 0 | "The casing was old, worn to a patina of verdigris, the glass face scratched but the etchings beneath still visible—odd, angular sigils that made her eyes want to slide away." | | 1 | "“The killer took the token. The bone token. That’s the only thing missing that makes sense. Without it, you can’t find the next market. You can’t ask questions there. The killer isn’t just covering their tracks; they’re cutting off the avenue of inquiry at the source.” She looked at Eva." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 920 | | adjectiveStacks | 2 | | stackExamples | | 0 | "visible—odd, angular sigils" | | 1 | "strange, sigil-marked tiles" |
| | adverbCount | 29 | | adverbRatio | 0.03152173913043478 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.017391304347826087 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 13.89 | | std | 9.02 | | cv | 0.65 | | sampleLengths | | 0 | 22 | | 1 | 27 | | 2 | 20 | | 3 | 19 | | 4 | 18 | | 5 | 20 | | 6 | 15 | | 7 | 22 | | 8 | 26 | | 9 | 17 | | 10 | 3 | | 11 | 9 | | 12 | 22 | | 13 | 11 | | 14 | 9 | | 15 | 8 | | 16 | 30 | | 17 | 6 | | 18 | 12 | | 19 | 7 | | 20 | 17 | | 21 | 2 | | 22 | 13 | | 23 | 15 | | 24 | 11 | | 25 | 28 | | 26 | 8 | | 27 | 15 | | 28 | 26 | | 29 | 11 | | 30 | 12 | | 31 | 3 | | 32 | 23 | | 33 | 14 | | 34 | 11 | | 35 | 3 | | 36 | 5 | | 37 | 7 | | 38 | 7 | | 39 | 3 | | 40 | 20 | | 41 | 10 | | 42 | 15 | | 43 | 26 | | 44 | 18 | | 45 | 1 | | 46 | 16 | | 47 | 11 | | 48 | 15 | | 49 | 7 |
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| 59.50% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.42990654205607476 | | totalSentences | 107 | | uniqueOpeners | 46 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 79 | | matches | | 0 | "Her boot heels echoed with" | | 1 | "Her left wrist, where the" | | 2 | "She was looking at the" | | 3 | "It was curled into a" | | 4 | "She knelt, the concrete cold" | | 5 | "It was quivering, pointing directly" | | 6 | "she said, her voice flat" | | 7 | "Her round glasses reflected the" | | 8 | "Her freckled complexion looked pale" | | 9 | "She pushed the memory down," | | 10 | "He was strangled from behind," | | 11 | "She walked back to the" | | 12 | "She looked at his face," | | 13 | "She stood, her movements crisp." | | 14 | "She looked at Eva" | | 15 | "Her own instincts, honed over" | | 16 | "She looked at Eva." | | 17 | "She took one last look" | | 18 | "It added up to a" |
| | ratio | 0.241 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 79 | | matches | | 0 | "The air in the abandoned" | | 1 | "The single forensic lamp, powered" | | 2 | "The beam of Detective Harlow" | | 3 | "Her boot heels echoed with" | | 4 | "The body was sprawled at" | | 5 | "A man, mid-forties, dressed in" | | 6 | "Quinn circled him, her face" | | 7 | "Her left wrist, where the" | | 8 | "Quinn didn’t answer." | | 9 | "She was looking at the" | | 10 | "It was curled into a" | | 11 | "She knelt, the concrete cold" | | 12 | "A small brass compass lay" | | 13 | "The casing was old, worn" | | 14 | "The needle was not pointing" | | 15 | "It was quivering, pointing directly" | | 16 | "she said, her voice flat" | | 17 | "The voice came from the" | | 18 | "Eva Kowalski stood there, clutching" | | 19 | "Her round glasses reflected the" |
| | ratio | 0.924 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 5 | | matches | | 0 | "Her boot heels echoed with military precision, a sound that felt out of place in this swallowed, silent space." | | 1 | "The casing was old, worn to a patina of verdigris, the glass face scratched but the etchings beneath still visible—odd, angular sigils that made her eyes want t…" | | 2 | "The evidence was arranging itself in her mind, but the picture it formed refused to resolve into anything that belonged in a Metropolitan Police case file." | | 3 | "Something that smelled like the unexplainable silence after the gunshot that killed Morris, the empty alley where the evidence should have been." | | 4 | "She took one last look at Alistair Finch, a man killed for knowledge in a place that didn’t exist, holding a compass that didn’t point north." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 6 | | matches | | 0 | "she said, her voice flat" | | 1 | "Quinn corrected, her tone leaving no room for mythology" | | 2 | "Eva took, as if steeling herself" | | 3 | "Eva offered, her voice tentative" | | 4 | "Eva finished, a mix of dread and scholarly fascination in her tone" | | 5 | "Quinn asked, her voice dropping, becoming dangerously quiet" |
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| 88.78% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 3 | | fancyTags | | 0 | "Quinn corrected (correct)" | | 1 | "Eva suggested (suggest)" | | 2 | "Quinn interrupted (interrupt)" |
| | dialogueSentences | 49 | | tagDensity | 0.224 | | leniency | 0.449 | | rawRatio | 0.273 | | effectiveRatio | 0.122 | |