| 36.73% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 4 | | adverbTags | | 0 | "Eva said quietly [quietly]" | | 1 | "Eva said quietly [quietly]" | | 2 | "Eva said carefully [carefully]" | | 3 | "she said slowly [slowly]" |
| | dialogueSentences | 49 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0.19 | | effectiveRatio | 0.163 | |
| 81.13% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1855 | | totalAiIsmAdverbs | 7 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | adverb | "barely above a whisper" | | count | 1 |
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| | highlights | | 0 | "carefully" | | 1 | "very" | | 2 | "slowly" | | 3 | "sharply" | | 4 | "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) | |
| 81.13% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1855 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "implication" | | 1 | "familiar" | | 2 | "systematic" | | 3 | "etched" | | 4 | "weight" | | 5 | "whisper" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 97 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 97 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 125 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1851 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 64 | | wordCount | 1379 | | uniqueNames | 14 | | maxNameDensity | 2.25 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 31 | | Victorian | 2 | | Camden | 1 | | Town | 1 | | North | 1 | | Transport | 1 | | London | 1 | | Morris | 2 | | Italian | 1 | | Eva | 19 | | Kowalski | 1 | | Whitechapel | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Eva" | | 4 | "Kowalski" |
| | places | | 0 | "Camden" | | 1 | "Town" | | 2 | "North" | | 3 | "Transport" | | 4 | "London" | | 5 | "Italian" |
| | globalScore | 0.376 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.54 | | wordCount | 1851 | | matches | | 0 | "not to the body itself but to the platform around it" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 125 | | matches | | 0 | "lights that forensics" | | 1 | "seen that look" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 61 | | mean | 30.34 | | std | 20.81 | | cv | 0.686 | | sampleLengths | | 0 | 52 | | 1 | 25 | | 2 | 52 | | 3 | 24 | | 4 | 55 | | 5 | 13 | | 6 | 56 | | 7 | 2 | | 8 | 66 | | 9 | 32 | | 10 | 49 | | 11 | 51 | | 12 | 28 | | 13 | 19 | | 14 | 83 | | 15 | 15 | | 16 | 2 | | 17 | 43 | | 18 | 32 | | 19 | 58 | | 20 | 62 | | 21 | 58 | | 22 | 2 | | 23 | 9 | | 24 | 6 | | 25 | 25 | | 26 | 5 | | 27 | 3 | | 28 | 64 | | 29 | 32 | | 30 | 36 | | 31 | 29 | | 32 | 5 | | 33 | 57 | | 34 | 35 | | 35 | 6 | | 36 | 3 | | 37 | 41 | | 38 | 25 | | 39 | 19 | | 40 | 13 | | 41 | 40 | | 42 | 4 | | 43 | 60 | | 44 | 78 | | 45 | 23 | | 46 | 17 | | 47 | 28 | | 48 | 19 | | 49 | 6 |
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| 98.03% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 97 | | matches | | 0 | "been disturbed" | | 1 | "been collected" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 239 | | matches | | 0 | "was looking" | | 1 | "was taking" |
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| 51.43% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 125 | | ratio | 0.032 | | matches | | 0 | "Eva tucked a strand of hair behind her left ear—a nervous habit Quinn had catalogued during their first meeting, six months ago, when the museum's restricted archives had become relevant to a case involving stolen antiquities." | | 1 | "Three nights was enough for a body to reach the state of rigor she'd observed, assuming ambient temperature in the tunnel—she'd need the medical examiner's report to confirm, but the preliminary picture was taking shape." | | 2 | "Unofficially, Quinn had spent three years following threads that led nowhere—or rather, that led to places like this." | | 3 | "Eva met her eyes, and Quinn saw something there that might have been relief—the unburdening of someone who had carried secrets alone for too long." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1385 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 54 | | adverbRatio | 0.03898916967509025 | | lyAdverbCount | 24 | | lyAdverbRatio | 0.017328519855595668 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 125 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 125 | | mean | 14.81 | | std | 9.73 | | cv | 0.657 | | sampleLengths | | 0 | 24 | | 1 | 28 | | 2 | 25 | | 3 | 4 | | 4 | 28 | | 5 | 20 | | 6 | 8 | | 7 | 9 | | 8 | 7 | | 9 | 27 | | 10 | 23 | | 11 | 2 | | 12 | 2 | | 13 | 1 | | 14 | 13 | | 15 | 21 | | 16 | 7 | | 17 | 28 | | 18 | 2 | | 19 | 32 | | 20 | 34 | | 21 | 23 | | 22 | 9 | | 23 | 36 | | 24 | 13 | | 25 | 12 | | 26 | 18 | | 27 | 6 | | 28 | 15 | | 29 | 20 | | 30 | 8 | | 31 | 13 | | 32 | 6 | | 33 | 15 | | 34 | 23 | | 35 | 45 | | 36 | 7 | | 37 | 8 | | 38 | 2 | | 39 | 4 | | 40 | 23 | | 41 | 16 | | 42 | 22 | | 43 | 10 | | 44 | 19 | | 45 | 39 | | 46 | 12 | | 47 | 25 | | 48 | 25 | | 49 | 10 |
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| 68.80% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.432 | | totalSentences | 125 | | uniqueOpeners | 54 | |
| 73.26% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 91 | | matches | | 0 | "Officially, it remained unsolved." | | 1 | "Unofficially, Quinn had spent three" |
| | ratio | 0.022 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 91 | | matches | | 0 | "She ducked under the police" | | 1 | "Her attention had already fixed" | | 2 | "She'd checked twice on the" | | 3 | "His eyes were open, fixed" | | 4 | "She'd seen that look once" | | 5 | "She looked up to find" | | 6 | "She crouched where Quinn had" | | 7 | "She pulled a small notebook" | | 8 | "She turned away from Eva" | | 9 | "She tucked her hair behind" | | 10 | "She stopped herself" | | 11 | "She stood, turning to face" | | 12 | "she said, thinking aloud" | | 13 | "She trailed off, her face" | | 14 | "She thought of Morris again." | | 15 | "she said, turning to the" | | 16 | "He held up another evidence" | | 17 | "She took the bag and" | | 18 | "she asked Eva" | | 19 | "she said slowly" |
| | ratio | 0.242 | |
| 31.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 91 | | matches | | 0 | "The abandoned platform stretched before" | | 1 | "She ducked under the police" | | 2 | "the uniformed constable said, though" | | 3 | "Quinn didn't acknowledge him." | | 4 | "Her attention had already fixed" | | 5 | "The letters had long since" | | 6 | "She'd checked twice on the" | | 7 | "The victim was a white" | | 8 | "His eyes were open, fixed" | | 9 | "She'd seen that look once" | | 10 | "Quinn pushed the memory aside" | | 11 | "The cause of death wasn't" | | 12 | "She looked up to find" | | 13 | "The young woman's round glasses" | | 14 | "Quinn rose to her full" | | 15 | "Eva tucked a strand of" | | 16 | "Quinn let the name hang" | | 17 | "The detective inspector had been" | | 18 | "Quinn didn't care for the" | | 19 | "Eva's voice steadied as she" |
| | ratio | 0.857 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 91 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 10 | | matches | | 0 | "The victim was a white male, mid-thirties, dressed in clothes that looked expensive but carried the subtle shabbiness of garments worn too often and cleaned too…" | | 1 | "The detective inspector had been increasingly willing to bring in outside expertise on cases that defied conventional explanation." | | 2 | "Quinn watched her trace a circle in the air, following a pattern that became visible only when you knew to look for it: a series of symbols scratched into the t…" | | 3 | "She pulled a small notebook from her satchel, flipping through pages covered in cramped handwriting until she found what she was looking for." | | 4 | "Quinn felt the familiar itch at the base of her skull that told her she was missing something important." | | 5 | "She turned away from Eva and began a slow circuit of the crime scene, cataloguing details with the systematic precision that had earned her three commendations …" | | 6 | "Candle stubs had been collected as evidence, but Quinn could see the wax drippings that marked their positions: another circle, smaller, nested within the first…" | | 7 | "A compass, its casing covered in a patina of verdigris that spoke of age, its face etched with markings that matched nothing in any navigational tradition she r…" | | 8 | "The researcher's face had gone pale beneath her freckles, and Quinn recognized the expression: someone who had just realized they knew more than they wanted to …" | | 9 | "Eva met her eyes, and Quinn saw something there that might have been relief—the unburdening of someone who had carried secrets alone for too long." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 1 | | matches | | 0 | "She trailed, her face going paler still" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 49 | | tagDensity | 0.184 | | leniency | 0.367 | | rawRatio | 0 | | effectiveRatio | 0 | |