| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 24 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.84% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1226 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 42.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1226 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "scanning" | | 1 | "pulse" | | 2 | "quickened" | | 3 | "standard" | | 4 | "charm" | | 5 | "etched" | | 6 | "perfect" | | 7 | "silk" | | 8 | "vibrated" | | 9 | "profound" | | 10 | "racing" | | 11 | "pulsed" |
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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 | 80 | | matches | (empty) | |
| 53.57% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 4 | | narrationSentences | 80 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "began to" | | 2 | "tried to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 92 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1221 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 975 | | uniqueNames | 9 | | maxNameDensity | 1.74 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 2 | | Camden | 1 | | Harlow | 1 | | Quinn | 17 | | Miller | 6 | | Morris | 1 | | Veil | 1 | | Market | 1 | | Eva | 1 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Miller" | | 4 | "Morris" | | 5 | "Eva" |
| | places | (empty) | | globalScore | 0.628 | | windowScore | 0.333 | |
| 63.79% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 2 | | matches | | 0 | "shadows that seemed to move independently of the people casting them" | | 1 | "sigils that seemed to shift when she tilted the device" |
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| 36.20% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.638 | | wordCount | 1221 | | matches | | 0 | "Not leading toward the exit, but leading deeper into the tunnels, toward a bricked-up archway" | | 1 | "not a wall, but a doorway" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 92 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 32.13 | | std | 21.68 | | cv | 0.675 | | sampleLengths | | 0 | 74 | | 1 | 70 | | 2 | 59 | | 3 | 2 | | 4 | 35 | | 5 | 32 | | 6 | 59 | | 7 | 41 | | 8 | 17 | | 9 | 14 | | 10 | 70 | | 11 | 11 | | 12 | 65 | | 13 | 30 | | 14 | 7 | | 15 | 11 | | 16 | 21 | | 17 | 5 | | 18 | 48 | | 19 | 55 | | 20 | 20 | | 21 | 14 | | 22 | 66 | | 23 | 5 | | 24 | 56 | | 25 | 23 | | 26 | 16 | | 27 | 25 | | 28 | 38 | | 29 | 19 | | 30 | 43 | | 31 | 55 | | 32 | 44 | | 33 | 14 | | 34 | 21 | | 35 | 9 | | 36 | 13 | | 37 | 14 |
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| 74.56% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 80 | | matches | | 0 | "been scrubbed" | | 1 | "was clamped" | | 2 | "were coated" | | 3 | "been wiped" | | 4 | "been opened" | | 5 | "was etched" | | 6 | "been summoned" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 7 | | totalVerbs | 170 | | matches | | 0 | "was, standing" | | 1 | "was hovering" | | 2 | "was crumbling" | | 3 | "wasn't pointing" | | 4 | "was spinning" | | 5 | "was operating" | | 6 | "was racing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 4 | | flaggedSentences | 8 | | totalSentences | 92 | | ratio | 0.087 | | matches | | 0 | "The flickering overhead lights—somehow still drawing power from a grid that should have been dead for decades—cast long, twitching shadows that seemed to move independently of the people casting them." | | 1 | "She didn't look at the man's face; she looked at his hands." | | 2 | "She remembered the file on DS Morris—the partner she had lost three years ago." | | 3 | "Its face wasn't marked with cardinal directions; instead, it was etched with a series of interlocking sigils that seemed to shift when she tilted the device." | | 4 | "It didn't just point; it vibrated." | | 5 | "She remembered the rumors she'd been chasing for months—whispers of a place called the Veil Market, a black market for things that shouldn't exist, tucked away in the folds of the city." | | 6 | "The man hadn't wandered here; he had been summoned, or perhaps he had tried to buy something he couldn't afford." | | 7 | "For a split second, the iridescent film pulsed, and she saw it—not a wall, but a doorway." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 986 | | adjectiveStacks | 1 | | stackExamples | | 0 | "bustling, neon-lit bazaar" |
| | adverbCount | 29 | | adverbRatio | 0.029411764705882353 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.013184584178498986 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 92 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 92 | | mean | 13.27 | | std | 8.5 | | cv | 0.641 | | sampleLengths | | 0 | 28 | | 1 | 16 | | 2 | 30 | | 3 | 17 | | 4 | 16 | | 5 | 6 | | 6 | 31 | | 7 | 9 | | 8 | 20 | | 9 | 4 | | 10 | 4 | | 11 | 22 | | 12 | 2 | | 13 | 2 | | 14 | 17 | | 15 | 16 | | 16 | 17 | | 17 | 11 | | 18 | 4 | | 19 | 11 | | 20 | 48 | | 21 | 3 | | 22 | 8 | | 23 | 12 | | 24 | 10 | | 25 | 8 | | 26 | 17 | | 27 | 4 | | 28 | 10 | | 29 | 13 | | 30 | 14 | | 31 | 25 | | 32 | 18 | | 33 | 7 | | 34 | 4 | | 35 | 17 | | 36 | 17 | | 37 | 8 | | 38 | 4 | | 39 | 19 | | 40 | 4 | | 41 | 26 | | 42 | 7 | | 43 | 4 | | 44 | 7 | | 45 | 21 | | 46 | 5 | | 47 | 3 | | 48 | 8 | | 49 | 19 |
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| 63.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.41304347826086957 | | totalSentences | 92 | | uniqueOpeners | 38 | |
| 88.89% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 75 | | matches | | 0 | "Just a man who looked" | | 1 | "Then, the image vanished, leaving" |
| | ratio | 0.027 | |
| 81.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 75 | | matches | | 0 | "She stepped over a rusted" | | 1 | "Her sharp jaw was set," | | 2 | "He was a middle-aged man" | | 3 | "He was hovering a few" | | 4 | "She glanced at the worn" | | 5 | "It was 3:14 AM." | | 6 | "She stepped closer to the" | | 7 | "She didn't look at the" | | 8 | "She reached out, gently prying" | | 9 | "She remembered the file on" | | 10 | "They had shown symbols etched" | | 11 | "She stood up and began" | | 12 | "They formed a trail." | | 13 | "She followed the rings to" | | 14 | "She reached into the victim's" | | 15 | "She unwrapped it slowly." | | 16 | "Its face wasn't marked with" | | 17 | "It was spinning in a" | | 18 | "It didn't just point; it" | | 19 | "She remembered the rumors she'd" |
| | ratio | 0.347 | |
| 60.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 75 | | matches | | 0 | "The air in the abandoned" | | 1 | "She stepped over a rusted" | | 2 | "The flickering overhead lights—somehow still" | | 3 | "Detective Quinn stopped at the" | | 4 | "Her sharp jaw was set," | | 5 | "This wasn't a standard crime" | | 6 | "The station had been scrubbed" | | 7 | "He was a middle-aged man" | | 8 | "He was hovering a few" | | 9 | "Quinn replied, her voice a" | | 10 | "She glanced at the worn" | | 11 | "It was 3:14 AM." | | 12 | "Miller continued, oblivious to her" | | 13 | "Quinn didn't answer." | | 14 | "She stepped closer to the" | | 15 | "She didn't look at the" | | 16 | "The man’s right hand was" | | 17 | "She reached out, gently prying" | | 18 | "Quinn felt a cold prickle" | | 19 | "She remembered the file on" |
| | ratio | 0.8 | |
| 66.67% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 75 | | matches | | 0 | "Now, she held the key." |
| | ratio | 0.013 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 8 | | matches | | 0 | "The air in the abandoned Tube station beneath Camden tasted of ozone and wet concrete, a thick, cloying dampness that clung to the back of Harlow Quinn’s throat…" | | 1 | "The flickering overhead lights—somehow still drawing power from a grid that should have been dead for decades—cast long, twitching shadows that seemed to move i…" | | 2 | "Not leading toward the exit, but leading deeper into the tunnels, toward a bricked-up archway that looked as though it hadn't been opened in a century." | | 3 | "Its face wasn't marked with cardinal directions; instead, it was etched with a series of interlocking sigils that seemed to shift when she tilted the device." | | 4 | "She remembered the rumors she'd been chasing for months—whispers of a place called the Veil Market, a black market for things that shouldn't exist, tucked away …" | | 5 | "It was a woman, small and slight, wearing a worn leather satchel that looked heavy enough to tip her over." | | 6 | "She had a crown of curly red hair and round glasses that caught the flickering light." | | 7 | "A glimpse of a bustling, neon-lit bazaar filled with creatures that defied anatomy and stalls selling jars of shimmering smoke." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 6 | | matches | | 0 | "Quinn replied, her voice a low, clipped rasp" | | 1 | "Quinn shouted, her voice booming through the station with military authority" | | 2 | "the woman called back, her voice trembling but clear" | | 3 | "Quinn snapped, though her mind was racing" | | 4 | "Quinn ordered, her voice cold" | | 5 | "Quinn said, her eyes narrowing," |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 7 | | fancyTags | | 0 | "Miller continued (continue)" | | 1 | "Quinn murmured (murmur)" | | 2 | "Miller noted (note)" | | 3 | "Quinn shouted (shout)" | | 4 | "the woman called back (call back)" | | 5 | "Quinn snapped (snap)" | | 6 | "Quinn ordered (order)" |
| | dialogueSentences | 24 | | tagDensity | 0.417 | | leniency | 0.833 | | rawRatio | 0.7 | | effectiveRatio | 0.583 | |