| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1540 | | 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) | |
| 22.08% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1540 | | totalAiIsms | 24 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | |
| | highlights | | 0 | "electric" | | 1 | "rhythmic" | | 2 | "maw" | | 3 | "flicked" | | 4 | "warmth" | | 5 | "pulsed" | | 6 | "dancing" | | 7 | "velvet" | | 8 | "echoing" | | 9 | "silk" | | 10 | "cacophony" | | 11 | "shimmered" | | 12 | "whisper" | | 13 | "echoes" | | 14 | "marble" | | 15 | "weight" | | 16 | "footfall" | | 17 | "could feel" | | 18 | "shattered" | | 19 | "kaleidoscope" | | 20 | "lurch" | | 21 | "flickered" |
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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 | 114 | | matches | (empty) | |
| 92.73% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 114 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 134 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1527 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 1270 | | uniqueNames | 15 | | maxNameDensity | 1.57 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 20 | | Quinn | 3 | | Pratt | 1 | | Street | 1 | | Camden | 1 | | Tube | 1 | | London | 1 | | Static | 1 | | Veil | 1 | | Market | 3 | | Crow-man | 2 | | Saint | 1 | | Christopher | 1 | | Tomás | 4 | | Herrera | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Static" | | 3 | "Market" | | 4 | "Crow-man" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Tomás" | | 8 | "Herrera" |
| | places | | 0 | "Pratt" | | 1 | "Street" | | 2 | "Camden" | | 3 | "London" |
| | globalScore | 0.713 | | windowScore | 0.667 | |
| 63.79% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | glossingSentenceCount | 3 | | matches | | 0 | "quite people—tall, spindly things in silk suits and bent figures carrying jars of glowing liquid" | | 1 | "meat that seemed to twitch under the lamplight" | | 2 | "looked like weathered marble" |
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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 | 1527 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 134 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 27.27 | | std | 17.78 | | cv | 0.652 | | sampleLengths | | 0 | 28 | | 1 | 71 | | 2 | 58 | | 3 | 20 | | 4 | 53 | | 5 | 32 | | 6 | 2 | | 7 | 48 | | 8 | 53 | | 9 | 15 | | 10 | 12 | | 11 | 11 | | 12 | 3 | | 13 | 55 | | 14 | 23 | | 15 | 9 | | 16 | 60 | | 17 | 27 | | 18 | 1 | | 19 | 26 | | 20 | 21 | | 21 | 23 | | 22 | 41 | | 23 | 45 | | 24 | 20 | | 25 | 53 | | 26 | 5 | | 27 | 33 | | 28 | 19 | | 29 | 41 | | 30 | 12 | | 31 | 45 | | 32 | 18 | | 33 | 38 | | 34 | 17 | | 35 | 40 | | 36 | 19 | | 37 | 3 | | 38 | 58 | | 39 | 27 | | 40 | 36 | | 41 | 5 | | 42 | 36 | | 43 | 16 | | 44 | 9 | | 45 | 21 | | 46 | 33 | | 47 | 22 | | 48 | 3 | | 49 | 11 |
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| 99.11% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 114 | | matches | | 0 | "been sealed" | | 1 | "been snapped" |
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| 7.69% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 208 | | matches | | 0 | "was weaving" | | 1 | "was heading" | | 2 | "was standing" | | 3 | "was talking" | | 4 | "wasn't fleeing" | | 5 | "was gliding" |
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| 36.25% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 1 | | flaggedSentences | 5 | | totalSentences | 134 | | ratio | 0.037 | | matches | | 0 | "The roar of London’s night traffic muffled into a low, rhythmic thrumming, replaced by the heavy scent of ozone and something metallic—like a mouth full of copper pennies." | | 1 | "Not cut—snapped, the thick steel twisted like a dry twig." | | 2 | "Her suspect was weaving through a crowd of people who weren't quite people—tall, spindly things in silk suits and bent figures carrying jars of glowing liquid." | | 3 | "Under the hood, his face was a void—no features, just a smooth, pale surface like an uncarved mask." | | 4 | "He didn't jump to the tracks; he leapt upward, grabbing a rusted light fixture and swinging himself onto a narrow maintenance catwalk twenty feet above the floor." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1282 | | adjectiveStacks | 1 | | stackExamples | | 0 | "short, curly dark hair" |
| | adverbCount | 27 | | adverbRatio | 0.02106084243369735 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.00858034321372855 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 134 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 134 | | mean | 11.4 | | std | 6.92 | | cv | 0.608 | | sampleLengths | | 0 | 28 | | 1 | 4 | | 2 | 19 | | 3 | 23 | | 4 | 3 | | 5 | 7 | | 6 | 15 | | 7 | 11 | | 8 | 18 | | 9 | 13 | | 10 | 10 | | 11 | 6 | | 12 | 12 | | 13 | 8 | | 14 | 7 | | 15 | 23 | | 16 | 3 | | 17 | 20 | | 18 | 4 | | 19 | 28 | | 20 | 2 | | 21 | 11 | | 22 | 27 | | 23 | 10 | | 24 | 7 | | 25 | 6 | | 26 | 19 | | 27 | 11 | | 28 | 10 | | 29 | 5 | | 30 | 10 | | 31 | 5 | | 32 | 7 | | 33 | 11 | | 34 | 3 | | 35 | 4 | | 36 | 13 | | 37 | 9 | | 38 | 6 | | 39 | 23 | | 40 | 15 | | 41 | 4 | | 42 | 4 | | 43 | 9 | | 44 | 7 | | 45 | 19 | | 46 | 13 | | 47 | 21 | | 48 | 10 | | 49 | 17 |
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| 41.04% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.29850746268656714 | | totalSentences | 134 | | uniqueOpeners | 40 | |
| 59.52% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 112 | | matches | | 0 | "Too fast for a man" | | 1 | "Then, he vanished into the" |
| | ratio | 0.018 | |
| 70.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 42 | | totalSentences | 112 | | matches | | 0 | "Her suspect was fast." | | 1 | "She didn't shout." | | 2 | "It turned the neon glows" | | 3 | "She checked the worn leather" | | 4 | "she grunted into the lapel" | | 5 | "He veered sharp right, skidding" | | 6 | "She hit the fence hard," | | 7 | "He turned his head, just" | | 8 | "She flicked her torch on." | | 9 | "She shoved the radio into" | | 10 | "It wasn't the humid heat" | | 11 | "She didn't need it." | | 12 | "It was a fever dream" | | 13 | "She stood on the edge" | | 14 | "Her suspect was weaving through" | | 15 | "He was heading for a" | | 16 | "She reached into her pocket." | | 17 | "Her fingers brushed a small," | | 18 | "She’d kept it as evidence," | | 19 | "She dropped the bone into" |
| | ratio | 0.375 | |
| 18.04% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 99 | | totalSentences | 112 | | matches | | 0 | "The heavy industrial plastic of" | | 1 | "Her suspect was fast." | | 2 | "She didn't shout." | | 3 | "Shouting was for uniformed officers" | | 4 | "Harlow just tightened her grip" | | 5 | "The rain didn't fall so" | | 6 | "It turned the neon glows" | | 7 | "Harlow’s salt-and-pepper hair, usually cropped" | | 8 | "She checked the worn leather" | | 9 | "she grunted into the lapel" | | 10 | "The figure didn't head for" | | 11 | "He veered sharp right, skidding" | | 12 | "Harlow didn't hesitate." | | 13 | "She hit the fence hard," | | 14 | "The air changed instantly." | | 15 | "The roar of London’s night" | | 16 | "The man paused at the" | | 17 | "He turned his head, just" | | 18 | "Harlow reached the edge of" | | 19 | "This wasn't on the official" |
| | ratio | 0.884 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 112 | | matches | (empty) | | ratio | 0 | |
| 47.62% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 8 | | matches | | 0 | "Ahead, the hooded figure vaulted a stack of wooden pallets with a fluid, predatory grace that made the hair on Harlow’s neck prickle." | | 1 | "He veered sharp right, skidding through a gap in a chain-link fence that led toward the skeletal remains of a long-abandoned Tube entrance." | | 2 | "It wasn't the humid heat of a summer night, but a dry, stifling warmth that smelled of incense, old parchment, and charred meat." | | 3 | "This was the legendary underground market, the place where the things that shouldn't exist traded in things that shouldn't be bought." | | 4 | "Her suspect was weaving through a crowd of people who weren't quite people—tall, spindly things in silk suits and bent figures carrying jars of glowing liquid." | | 5 | "Next to it, a butcher’s stall displayed cuts of meat that seemed to twitch under the lamplight." | | 6 | "He had warm brown eyes and short, curly dark hair that shimmered under the amber lanterns." | | 7 | "It was a narrow, terrifying strip of perforated steel that shuddered with every footfall." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn said, her sharp jaw tightening" | | 1 | "Tomás stepped, his voice dropping to a whisper" |
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| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 4 | | fancyTags | | 0 | "she grunted (grunt)" | | 1 | "the Crow-man hissed (hiss)" | | 2 | "Harlow yelled (yell)" | | 3 | "the thing hissed (hiss)" |
| | dialogueSentences | 28 | | tagDensity | 0.214 | | leniency | 0.429 | | rawRatio | 0.667 | | effectiveRatio | 0.286 | |