| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1146 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 43.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1146 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "pulse" | | 2 | "gleaming" | | 3 | "echoed" | | 4 | "weight" | | 5 | "maw" | | 6 | "standard" | | 7 | "silence" | | 8 | "velvet" | | 9 | "trembled" | | 10 | "navigating" | | 11 | "hulking" |
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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 | 76 | | matches | (empty) | |
| 86.47% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 76 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 82 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1142 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 89.70% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1078 | | uniqueNames | 22 | | maxNameDensity | 1.21 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Detective | 1 | | Harlow | 13 | | Quinn | 1 | | Dean | 1 | | Street | 1 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Spanish | 1 | | London | 1 | | Tomás | 11 | | Victorian | 2 | | Morris | 2 | | Tube | 1 | | Camden | 1 | | Veil | 1 | | Market | 1 | | Metropolitan | 1 | | Police | 1 | | Department | 1 |
| | persons | | 0 | "Raven" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Tomás" | | 7 | "Morris" | | 8 | "Camden" | | 9 | "Police" | | 10 | "Department" |
| | places | | 0 | "Dean" | | 1 | "Street" | | 2 | "London" |
| | globalScore | 0.897 | | windowScore | 1 | |
| 70.63% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 2 | | matches | | 0 | "cloaks that seemed to drink the meager light" | | 1 | "felt like a toy" |
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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 | 1142 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 82 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 33.59 | | std | 22.61 | | cv | 0.673 | | sampleLengths | | 0 | 56 | | 1 | 36 | | 2 | 4 | | 3 | 78 | | 4 | 25 | | 5 | 32 | | 6 | 10 | | 7 | 36 | | 8 | 63 | | 9 | 79 | | 10 | 5 | | 11 | 55 | | 12 | 20 | | 13 | 11 | | 14 | 84 | | 15 | 3 | | 16 | 49 | | 17 | 54 | | 18 | 14 | | 19 | 37 | | 20 | 64 | | 21 | 44 | | 22 | 4 | | 23 | 8 | | 24 | 36 | | 25 | 27 | | 26 | 11 | | 27 | 37 | | 28 | 18 | | 29 | 44 | | 30 | 18 | | 31 | 24 | | 32 | 34 | | 33 | 22 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 76 | | matches | (empty) | |
| 87.01% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 177 | | matches | | 0 | "was navigating" | | 1 | "was bartering" | | 2 | "was slipping" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 1 | | flaggedSentences | 5 | | totalSentences | 82 | | ratio | 0.061 | | matches | | 0 | "This wasn't standard operating procedure; no backup, no radio signal penetrating three feet of reinforced Victorian concrete, no clear grid coordinates." | | 1 | "The smell hit her first—a suffocating mix of dried lavender, copper, roasting spices, and unwashed wool." | | 2 | "She broke through a narrow archway into an vaulted tunnel—an abandoned Tube platform beneath Camden, swallowed whole by something impossible." | | 3 | "He clutched his forearm, wincing as his jacket brushed against a passerby—the long scar from his paramedic days clearly aching." | | 4 | "She adopted her standard patrol posture—shoulders back, chin firm, absolute authority radiating from every line of her frame despite the cold terror coiling in her gut." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1094 | | adjectiveStacks | 2 | | stackExamples | | 0 | "polished, ivory-white bone" | | 1 | "faceless, cloth-wrapped head" |
| | adverbCount | 16 | | adverbRatio | 0.014625228519195612 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.003656307129798903 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 13.93 | | std | 7.25 | | cv | 0.52 | | sampleLengths | | 0 | 31 | | 1 | 11 | | 2 | 14 | | 3 | 14 | | 4 | 22 | | 5 | 4 | | 6 | 4 | | 7 | 20 | | 8 | 8 | | 9 | 24 | | 10 | 22 | | 11 | 16 | | 12 | 9 | | 13 | 20 | | 14 | 12 | | 15 | 10 | | 16 | 3 | | 17 | 17 | | 18 | 16 | | 19 | 9 | | 20 | 3 | | 21 | 20 | | 22 | 11 | | 23 | 20 | | 24 | 11 | | 25 | 4 | | 26 | 21 | | 27 | 36 | | 28 | 3 | | 29 | 4 | | 30 | 5 | | 31 | 17 | | 32 | 16 | | 33 | 22 | | 34 | 20 | | 35 | 11 | | 36 | 16 | | 37 | 15 | | 38 | 20 | | 39 | 17 | | 40 | 16 | | 41 | 3 | | 42 | 16 | | 43 | 9 | | 44 | 5 | | 45 | 19 | | 46 | 23 | | 47 | 20 | | 48 | 11 | | 49 | 5 |
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| 59.35% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.4146341463414634 | | totalSentences | 82 | | uniqueOpeners | 34 | |
| 43.86% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 76 | | matches | | 0 | "Instead, his warm brown eyes" |
| | ratio | 0.013 | |
| 83.16% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 76 | | matches | | 0 | "Her boots struck the slick" | | 1 | "He threw a frantic glance" | | 2 | "His short, dark curls stuck" | | 3 | "He took off down the" | | 4 | "He threw his weight against" | | 5 | "She stumbled into an abandoned" | | 6 | "She adjusted her grip on" | | 7 | "Her sharp jaw tightened." | | 8 | "Her mind flashed to the" | | 9 | "He had been there." | | 10 | "She broke through a narrow" | | 11 | "She saw a merchant with" | | 12 | "Her hand trembled against the" | | 13 | "He clutched his forearm, wincing" | | 14 | "He glanced back toward the" | | 15 | "He didn't belong here either." | | 16 | "He was navigating it out" | | 17 | "Her badge was a useless" | | 18 | "He pulled out a polished," | | 19 | "she whispered under her breath" |
| | ratio | 0.342 | |
| 25.79% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 76 | | matches | | 0 | "Sheets of freezing rain slammed" | | 1 | "Her boots struck the slick" | | 2 | "Harlow gripped the butt of" | | 3 | "The figure didn't flinch." | | 4 | "Tomás Herrera surged out from" | | 5 | "He threw a frantic glance" | | 6 | "His short, dark curls stuck" | | 7 | "He took off down the" | | 8 | "Harlow shoved past a rusted" | | 9 | "Tomás’s voice echoed off the" | | 10 | "Tomás didn't answer." | | 11 | "He threw his weight against" | | 12 | "The latch groaned, snapped, and" | | 13 | "Harlow hit the iron door" | | 14 | "The metal shrieked." | | 15 | "She stumbled into an abandoned" | | 16 | "Rain thrummed against the roof" | | 17 | "She adjusted her grip on" | | 18 | "Her sharp jaw tightened." | | 19 | "This wasn't standard operating procedure;" |
| | ratio | 0.868 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 76 | | matches | | 0 | "If she stepped out from" | | 1 | "If she vanished into these" |
| | ratio | 0.026 | |
| 26.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 8 | | matches | | 0 | "He took off down the alley, vaulting over a collapsed wooden pallet with an agility that made Harlow growl through clamped teeth." | | 1 | "Ahead, a heavy flashlight beam cut through swirling dust, bouncing down a concrete staircase that plummeted deep into the earth." | | 2 | "Down here, the silence of the abandoned underground vanished, replaced by a low, vibrating hum that rattled the fillings in her teeth." | | 3 | "This was something that tore through her clean, logical view of reality and left it bleeding on the floor." | | 4 | "He clutched his forearm, wincing as his jacket brushed against a passerby—the long scar from his paramedic days clearly aching." | | 5 | "He pulled out a polished, ivory-white bone token and handed it to a hulking figure guarding an archway that led deeper into the subterranean maze." | | 6 | "She reached for her belt, unclipping her handcuffs and shoving them into her pocket." | | 7 | "Harlow raised her weapon, leveling it straight at Tomás's chest, stepping fully over the threshold into the dark core of the market." |
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| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 1 | | matches | | 0 | "he gasped, his voice carrying over the hum of the market" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 4 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "she snapped (snap)" | | 2 | "he gasped (gasp)" | | 3 | "Harlow shouted (shout)" |
| | dialogueSentences | 12 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 1 | | effectiveRatio | 0.667 | |