| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 34 | | adverbTagCount | 3 | | adverbTags | | 0 | "Harlow’s hand moved instinctively [instinctively]" | | 1 | "The girl jumped nearly [nearly]" | | 2 | "Eva nodded quickly. [quickly]" |
| | dialogueSentences | 54 | | tagDensity | 0.63 | | leniency | 1 | | rawRatio | 0.088 | | effectiveRatio | 0.088 | |
| 88.46% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1733 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | | 2 | | | 3 | | adverb | "reluctantly" | | count | 1 |
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| | highlights | | 0 | "gently" | | 1 | "softly" | | 2 | "quickly" | | 3 | "reluctantly" |
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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) | |
| 50.95% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1733 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "shattered" | | 1 | "silence" | | 2 | "gloom" | | 3 | "echoed" | | 4 | "scanning" | | 5 | "standard" | | 6 | "perfect" | | 7 | "profound" | | 8 | "etched" | | 9 | "intricate" | | 10 | "echoing" | | 11 | "rhythmic" | | 12 | "trembled" | | 13 | "mosaic" | | 14 | "footsteps" | | 15 | "familiar" |
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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 | 108 | | matches | (empty) | |
| 63.49% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 3 | | narrationSentences | 108 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 119 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 65 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1726 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 1 | | matches | | 0 | "Reluctantly, Miller grumbled and started the long climb back up the escalator. Harlow waited until the sound of his foot…" |
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| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 73 | | wordCount | 1239 | | uniqueNames | 24 | | maxNameDensity | 2.18 | | worstName | "Harlow" | | maxWindowNameDensity | 4 | | worstWindowName | "Harlow" | | discoveredNames | | Tube | 2 | | Harlow | 27 | | Quinn | 3 | | Camden | 1 | | Friday | 1 | | Victorian | 1 | | Sergeant | 1 | | Miller | 8 | | Morris | 3 | | Yard | 1 | | Eva | 9 | | British | 1 | | Museum | 1 | | Market | 3 | | Miss | 1 | | Kowalski | 1 | | Tomorrow | 1 | | Breach-Hunter | 1 | | Veil | 1 | | Ancient | 1 | | History | 1 | | Call | 1 | | You | 2 | | Reluctantly | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Miller" | | 4 | "Morris" | | 5 | "Eva" | | 6 | "Market" | | 7 | "Miss" | | 8 | "Kowalski" | | 9 | "Veil" | | 10 | "You" |
| | places | | 0 | "Tube" | | 1 | "Yard" | | 2 | "British" | | 3 | "Ancient" |
| | globalScore | 0.41 | | windowScore | 0.333 | |
| 47.26% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like he wanted to be anywhere else" | | 1 | "liquid that seemed to shimmer even in the low light, and strangely shaped curios made of bone and scrap metal" | | 2 | "sigils that seemed to crawl if she looked at them too long" |
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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 | 1726 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 119 | | matches | (empty) | |
| 96.40% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 39.23 | | std | 19.12 | | cv | 0.487 | | sampleLengths | | 0 | 65 | | 1 | 59 | | 2 | 6 | | 3 | 50 | | 4 | 48 | | 5 | 9 | | 6 | 35 | | 7 | 64 | | 8 | 45 | | 9 | 47 | | 10 | 54 | | 11 | 82 | | 12 | 34 | | 13 | 20 | | 14 | 27 | | 15 | 47 | | 16 | 57 | | 17 | 45 | | 18 | 21 | | 19 | 66 | | 20 | 66 | | 21 | 16 | | 22 | 32 | | 23 | 3 | | 24 | 44 | | 25 | 27 | | 26 | 48 | | 27 | 34 | | 28 | 60 | | 29 | 18 | | 30 | 42 | | 31 | 18 | | 32 | 15 | | 33 | 65 | | 34 | 37 | | 35 | 5 | | 36 | 13 | | 37 | 27 | | 38 | 59 | | 39 | 42 | | 40 | 39 | | 41 | 43 | | 42 | 50 | | 43 | 42 |
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| 85.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 108 | | matches | | 0 | "was supposed" | | 1 | "been sheared" | | 2 | "was clamped" | | 3 | "was etched" | | 4 | "was supposed" | | 5 | "was undisturbed" | | 6 | "being told" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 233 | | matches | | 0 | "were screaming" | | 1 | "was holding" | | 2 | "was standing" | | 3 | "was looking" | | 4 | "was spinning" | | 5 | "was trying" | | 6 | "were glowing" | | 7 | "were still shaking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 2 | | flaggedSentences | 8 | | totalSentences | 119 | | ratio | 0.067 | | matches | | 0 | "There wasn't a mark on him—no blood, no bruising, no signs of a struggle." | | 1 | "She’d seen sketches of such things in the private journals Morris had left behind—the ones no one at the Yard was supposed to know about." | | 2 | "She was small—no more than 5'4\"—with a mass of curly red hair and round glasses that reflected the flashlight’s beam. She wore a heavy coat and carried a worn leather satchel that looked fit to burst with books." | | 3 | "The girl jumped, nearly dropping her bag. She immediately tucked a stray lock of red hair behind her left ear—a nervous flick of the wrist. “I—I’m sorry!" | | 4 | "I wasn't—I’m not with him!”" | | 5 | "Harlow stopped six feet from the girl. She recognized the look in Eva’s eyes. It was the same look Morris had the night he vanished—a mixture of awe and crippling dread. “What killed him?”" | | 6 | "Harlow looked back at the body. The coldness of the station seemed to seep into her bones. Every detail that Miller had dismissed as 'junk' or 'vandalism' was clicking into a different, darker mosaic. The silver wire wasn't just metal; it was a conductor. The herbs weren't drugs; they were incense meant to mask the scent of human presence from things that hunted by smell." | | 7 | "Harlow felt a familiar shadow stir in the back of her mind—the memory of Morris’s empty trench coat lying in a rain-slicked alley. She looked down at the compass. The sigils were glowing now, a faint, sickly violet light." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1027 | | adjectiveStacks | 1 | | stackExamples | | 0 | "humid, ozone-thick air" |
| | adverbCount | 15 | | adverbRatio | 0.014605647517039922 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004868549172346641 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 119 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 119 | | mean | 14.5 | | std | 12.63 | | cv | 0.871 | | sampleLengths | | 0 | 18 | | 1 | 20 | | 2 | 27 | | 3 | 10 | | 4 | 2 | | 5 | 24 | | 6 | 23 | | 7 | 6 | | 8 | 10 | | 9 | 6 | | 10 | 34 | | 11 | 10 | | 12 | 25 | | 13 | 13 | | 14 | 9 | | 15 | 7 | | 16 | 7 | | 17 | 21 | | 18 | 3 | | 19 | 18 | | 20 | 34 | | 21 | 9 | | 22 | 14 | | 23 | 14 | | 24 | 17 | | 25 | 6 | | 26 | 41 | | 27 | 9 | | 28 | 5 | | 29 | 20 | | 30 | 20 | | 31 | 7 | | 32 | 9 | | 33 | 6 | | 34 | 9 | | 35 | 31 | | 36 | 5 | | 37 | 15 | | 38 | 9 | | 39 | 25 | | 40 | 6 | | 41 | 14 | | 42 | 6 | | 43 | 13 | | 44 | 8 | | 45 | 13 | | 46 | 21 | | 47 | 6 | | 48 | 7 | | 49 | 6 |
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| 64.99% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.42016806722689076 | | totalSentences | 119 | | uniqueOpeners | 50 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 100 | | matches | | 0 | "Gently, Harlow pried the fingers" | | 1 | "Specifically, the artifacts that shouldn't" | | 2 | "Reluctantly, Miller grumbled and started" | | 3 | "Once you see it, you" |
| | ratio | 0.04 | |
| 76.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 100 | | matches | | 0 | "She paused at the foot" | | 1 | "She adjusted her stance, her" | | 2 | "She found Sergeant Miller standing" | | 3 | "He was a thick-necked man" | | 4 | "He gestured with his light" | | 5 | "He shone the beam onto" | | 6 | "His eyes were wide open," | | 7 | "She didn't touch anything yet." | | 8 | "She reached into her coat" | | 9 | "She pointed to the victim’s" | | 10 | "It was clamped shut around" | | 11 | "Its casing was thick with" | | 12 | "It spun in slow, erratic" | | 13 | "She’d seen sketches of such" | | 14 | "She stood up, her brown" | | 15 | "She took the flashlight from" | | 16 | "She used a pen to" | | 17 | "It was a bone token," | | 18 | "She turned her attention to" | | 19 | "She was small—no more than" |
| | ratio | 0.36 | |
| 80.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 76 | | totalSentences | 100 | | matches | | 0 | "The humid, ozone-thick air of" | | 1 | "She paused at the foot" | | 2 | "Harlow checked the worn leather" | | 3 | "She adjusted her stance, her" | | 4 | "a voice echoed" | | 5 | "Harlow moved toward the light," | | 6 | "This wasn’t a standard crime" | | 7 | "The abandoned station was supposed" | | 8 | "She found Sergeant Miller standing" | | 9 | "He was a thick-necked man" | | 10 | "He gestured with his light" | | 11 | "Harlow asked, her voice low" | | 12 | "He shone the beam onto" | | 13 | "Harlow looked down." | | 14 | "The victim was male, mid-twenties," | | 15 | "His eyes were wide open," | | 16 | "Miller grunted, folding his arms" | | 17 | "Harlow knelt beside the body," | | 18 | "She didn't touch anything yet." | | 19 | "She reached into her coat" |
| | ratio | 0.76 | |
| 50.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 100 | | matches | | | ratio | 0.01 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 9 | | matches | | 0 | "She adjusted her stance, her spine clicking into the rigid, military posture that had become her default setting over eighteen years on the force." | | 1 | "The abandoned station was supposed to be sealed behind four inches of reinforced steel, yet the lock on the street-level grate had been sheared off with a preci…" | | 2 | "He was a thick-necked man who smelled of menthol cigarettes and cheap coffee, and right now, he looked like he wanted to be anywhere else." | | 3 | "Laid out in a perfect, concentric circle were dozens of items that didn't belong in a derelict tunnel." | | 4 | "There were bundles of dried herbs tied with silver wire, small vials of iridescent liquid that seemed to shimmer even in the low light, and strangely shaped cur…" | | 5 | "The victim was male, mid-twenties, dressed in expensive tactical gear that looked brand new." | | 6 | "Its casing was thick with a green patina of verdigris, and the glass face was etched with intricate, swirling sigils that seemed to crawl if she looked at them …" | | 7 | "The thick carpet of grime that covered the platform was undisturbed everywhere except for the direct path leading to the body." | | 8 | "She was small—no more than 5'4\"—with a mass of curly red hair and round glasses that reflected the flashlight’s beam. She wore a heavy coat and carried a worn l…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 24 | | uselessAdditionCount | 6 | | matches | | 0 | "Harlow asked, her voice low and raspy" | | 1 | "Harlow whispered, the words tasting bitter" | | 2 | "Harlow said, her voice dropping an octave" | | 3 | "Eva said, her voice gaining a sliver of academic courage" | | 4 | "Harlow said, her voice softening just enough to be dangerous" | | 5 | "she snapped, the command slicing through the air like a blade" |
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| 38.89% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 6 | | fancyTags | | 0 | "Miller grunted (grunt)" | | 1 | "Harlow whispered (whisper)" | | 2 | "Harlow noted (note)" | | 3 | "Harlow barked (bark)" | | 4 | "Quinn tell (quinn tell)" | | 5 | "she snapped (snap)" |
| | dialogueSentences | 54 | | tagDensity | 0.296 | | leniency | 0.593 | | rawRatio | 0.375 | | effectiveRatio | 0.222 | |