| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 40 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 82.05% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1393 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "softly" | | 1 | "slightly" | | 2 | "sharply" |
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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) | |
| 56.93% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1393 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "shimmered" | | 1 | "gloom" | | 2 | "stark" | | 3 | "efficient" | | 4 | "etched" | | 5 | "perfect" | | 6 | "pristine" | | 7 | "silence" | | 8 | "stomach" | | 9 | "whisper" | | 10 | "glinting" | | 11 | "rhythmic" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 118 | | matches | (empty) | |
| 94.43% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 118 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 138 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1392 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1021 | | uniqueNames | 10 | | maxNameDensity | 2.74 | | worstName | "Quinn" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Harlow | 1 | | Quinn | 28 | | Tube | 1 | | Metropolitan | 1 | | Police | 1 | | Kowalski | 1 | | Eva | 14 | | Market | 1 | | Morris | 1 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Police" | | 4 | "Kowalski" | | 5 | "Eva" | | 6 | "Morris" |
| | places | (empty) | | globalScore | 0.129 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 1 | | matches | | 0 | "air that seemed to press against her skin" |
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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 | 1392 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 138 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 33.95 | | std | 20.09 | | cv | 0.592 | | sampleLengths | | 0 | 80 | | 1 | 51 | | 2 | 68 | | 3 | 49 | | 4 | 34 | | 5 | 75 | | 6 | 57 | | 7 | 53 | | 8 | 21 | | 9 | 36 | | 10 | 6 | | 11 | 20 | | 12 | 55 | | 13 | 61 | | 14 | 37 | | 15 | 18 | | 16 | 29 | | 17 | 40 | | 18 | 8 | | 19 | 17 | | 20 | 12 | | 21 | 46 | | 22 | 40 | | 23 | 16 | | 24 | 4 | | 25 | 38 | | 26 | 37 | | 27 | 11 | | 28 | 3 | | 29 | 31 | | 30 | 32 | | 31 | 42 | | 32 | 6 | | 33 | 16 | | 34 | 30 | | 35 | 36 | | 36 | 15 | | 37 | 8 | | 38 | 53 | | 39 | 54 | | 40 | 47 |
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| 96.34% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 118 | | matches | | 0 | "been scrawled" | | 1 | "was contained" | | 2 | "were gone" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 14 | | totalVerbs | 175 | | matches | | 0 | "was tucking" | | 1 | "was spinning" | | 2 | "wasn't pointing" | | 3 | "wasn't pointing" | | 4 | "was pointing" | | 5 | "wasn't spreading" | | 6 | "was pointing" | | 7 | "was beginning" | | 8 | "was still pointing" | | 9 | "was still pointing" | | 10 | "wasn't pointing" | | 11 | "was pointing" | | 12 | "was waiting" | | 13 | "was following" |
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| 80.75% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 2 | | flaggedSentences | 3 | | totalSentences | 138 | | ratio | 0.022 | | matches | | 0 | "She didn't look at the body; she looked at the space around it." | | 1 | "The memory of DS Morris flashed behind her eyes—three years ago, the same smell of ozone, the same look of confusion before he vanished." | | 2 | "The body wasn't a victim of a crime; it was a receipt." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1024 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.025390625 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.009765625 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 138 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 138 | | mean | 10.09 | | std | 6.47 | | cv | 0.642 | | sampleLengths | | 0 | 21 | | 1 | 18 | | 2 | 17 | | 3 | 4 | | 4 | 20 | | 5 | 17 | | 6 | 7 | | 7 | 20 | | 8 | 7 | | 9 | 17 | | 10 | 12 | | 11 | 10 | | 12 | 4 | | 13 | 25 | | 14 | 13 | | 15 | 22 | | 16 | 14 | | 17 | 10 | | 18 | 12 | | 19 | 12 | | 20 | 7 | | 21 | 15 | | 22 | 8 | | 23 | 13 | | 24 | 32 | | 25 | 9 | | 26 | 9 | | 27 | 19 | | 28 | 20 | | 29 | 2 | | 30 | 6 | | 31 | 12 | | 32 | 4 | | 33 | 6 | | 34 | 23 | | 35 | 21 | | 36 | 8 | | 37 | 5 | | 38 | 11 | | 39 | 7 | | 40 | 5 | | 41 | 6 | | 42 | 5 | | 43 | 15 | | 44 | 13 | | 45 | 10 | | 46 | 9 | | 47 | 8 | | 48 | 15 | | 49 | 13 |
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| 39.13% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.26811594202898553 | | totalSentences | 138 | | uniqueOpeners | 37 | |
| 31.75% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 105 | | matches | | | ratio | 0.01 | |
| 44.76% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 46 | | totalSentences | 105 | | matches | | 0 | "She adjusted the collar of" | | 1 | "He was a man in" | | 2 | "It shimmered, catching the light" | | 3 | "She looked small against the" | | 4 | "She was tucking a stray" | | 5 | "She clutched her worn leather" | | 6 | "She walked around the perimeter" | | 7 | "Her military precision kept her" | | 8 | "She didn't look at the" | | 9 | "She pulled a small brass" | | 10 | "She looked at the compass" | | 11 | "It was spinning, a frantic" | | 12 | "It wasn't pointing north." | | 13 | "It wasn't pointing at the" | | 14 | "It was pointing at the" | | 15 | "She crouched, the leather of" | | 16 | "It was contained within a" | | 17 | "She walked to the wall" | | 18 | "She reached into her pocket" | | 19 | "She snapped them on, the" |
| | ratio | 0.438 | |
| 12.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 94 | | totalSentences | 105 | | matches | | 0 | "The air beneath Camden tasted" | | 1 | "She adjusted the collar of" | | 2 | "The leather strap was worn" | | 3 | "The full moon was high," | | 4 | "Quinn stepped over a threshold" | | 5 | "The station wasn’t on any" | | 6 | "The Metropolitan Police had marked" | | 7 | "The bodies didn’t appear in" | | 8 | "He was a man in" | | 9 | "It shimmered, catching the light" | | 10 | "Eva Kowalski stood three feet" | | 11 | "She looked small against the" | | 12 | "She was tucking a stray" | | 13 | "Eva said, her voice hushed" | | 14 | "She clutched her worn leather" | | 15 | "Quinn ignored the plea in" | | 16 | "She walked around the perimeter" | | 17 | "Her military precision kept her" | | 18 | "She didn't look at the" | | 19 | "Eva insisted, stepping closer" |
| | ratio | 0.895 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 105 | | matches | (empty) | | ratio | 0 | |
| 69.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 4 | | matches | | 0 | "The air beneath Camden tasted of rust and old ozone, a metallic tang that coated the back of Harlow Quinn’s throat." | | 1 | "She was tucking a stray lock behind her left ear, her fingers trembling slightly." | | 2 | "It was pointing at the wall behind the victim, specifically at a section of graffiti that had been scrawled over decades of paint." | | 3 | "The ash was beginning to shift, swirling slightly against the wind that didn't exist." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 4 | | matches | | 0 | "Eva said, her voice hushed" | | 1 | "Quinn said, her voice low," | | 2 | "Eva said, her voice hardening" | | 3 | "Quinn said, her voice dropping to a whisper" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 40 | | tagDensity | 0.35 | | leniency | 0.7 | | rawRatio | 0.071 | | effectiveRatio | 0.05 | |