| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 19 | | tagDensity | 0.316 | | leniency | 0.632 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.19% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1265 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "suddenly" | | 1 | "very" | | 2 | "slightly" |
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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) | |
| 32.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1265 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "measured" | | 1 | "electric" | | 2 | "flicked" | | 3 | "gloom" | | 4 | "footsteps" | | 5 | "echoed" | | 6 | "velvet" | | 7 | "pulsed" | | 8 | "scanning" | | 9 | "maw" | | 10 | "flickered" | | 11 | "glistening" | | 12 | "glinting" |
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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 | 104 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 104 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 116 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 11 | | markdownWords | 11 | | totalWords | 1245 | | ratio | 0.009 | | matches | | 0 | "runner" | | 1 | "definitely" | | 2 | "are" | | 3 | "plan" | | 4 | "him" | | 5 | "like" | | 6 | "thunk" | | 7 | "had" | | 8 | "“Help.”" | | 9 | "clicked" | | 10 | "her" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1149 | | uniqueNames | 10 | | maxNameDensity | 1.65 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | Quinn | 1 | | Greek | 1 | | Street | 1 | | Soho | 1 | | Morris | 1 | | Veil | 1 | | Market | 1 | | Harlow | 19 | | Rat | 1 | | Maw | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Harlow" | | 3 | "Rat" |
| | places | | 0 | "Greek" | | 1 | "Street" | | 2 | "Soho" | | 3 | "Market" |
| | globalScore | 0.673 | | windowScore | 0.667 | |
| 45.83% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 3 | | matches | | 0 | "something like it in his notebook the week b" | | 1 | "tasted like copper" | | 2 | "blades that seemed to drink the light" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.803 | | wordCount | 1245 | | matches | | 0 | "Not the sickly yellow of streetlamps, but a shifting, flickering glow" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 116 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 27.67 | | std | 22.92 | | cv | 0.828 | | sampleLengths | | 0 | 66 | | 1 | 2 | | 2 | 93 | | 3 | 46 | | 4 | 2 | | 5 | 54 | | 6 | 5 | | 7 | 51 | | 8 | 52 | | 9 | 4 | | 10 | 15 | | 11 | 52 | | 12 | 1 | | 13 | 40 | | 14 | 49 | | 15 | 13 | | 16 | 2 | | 17 | 34 | | 18 | 11 | | 19 | 19 | | 20 | 9 | | 21 | 30 | | 22 | 31 | | 23 | 9 | | 24 | 26 | | 25 | 70 | | 26 | 17 | | 27 | 9 | | 28 | 45 | | 29 | 8 | | 30 | 10 | | 31 | 10 | | 32 | 67 | | 33 | 55 | | 34 | 47 | | 35 | 7 | | 36 | 38 | | 37 | 45 | | 38 | 5 | | 39 | 43 | | 40 | 12 | | 41 | 13 | | 42 | 9 | | 43 | 8 | | 44 | 11 |
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| 95.14% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 104 | | matches | | 0 | "were lined" | | 1 | "was gone" | | 2 | "were raised" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 194 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 17 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 116 | | ratio | 0.095 | | matches | | 0 | "The suspect—tall, lanky, dressed in a hooded jacket that flapped like a crow’s wings—ducked left, disappearing into the maze of Soho’s back alleys." | | 1 | "He glanced back once—just a flash of pale face under the hood—and his boot caught a loose cobblestone." | | 2 | "She reached for the handle—cold, slick—and yanked." | | 3 | "The walls were lined with graffiti—symbols, not tags." | | 4 | "A sound snapped her focus back—the suspect, cursing under his breath as he fumbled with something at the far end of the tunnel." | | 5 | "Not the sickly yellow of streetlamps, but a shifting, flickering glow—lanterns, dozens of them, hanging from chains bolted into the ceiling." | | 6 | "The suspect—no, not just a suspect, a *runner*—ducked behind a stall draped in black velvet, its shelves lined with jars of things that pulsed faintly, like hearts in brine." | | 7 | "“No?” The woman tilted her head, the lantern light catching the irises of her eyes—vertical pupils, black as oil slicks." | | 8 | "The gap—the Rat’s Maw—was barely wide enough for her shoulders, the walls lined with more of those sigils, their paint fresh, wet." | | 9 | "Harlow’s torchlight flickered over it—a mass of glistening black, chitinous, its body a writhing knot of segmented parts." | | 10 | "Its head—if it *had* a head—was a cluster of eyes, wet and reflecting, and a mouth that split open vertically, rows of needle teeth glinting." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1169 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 41 | | adverbRatio | 0.03507271171941831 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.00855431993156544 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 116 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 116 | | mean | 10.73 | | std | 7.21 | | cv | 0.672 | | sampleLengths | | 0 | 16 | | 1 | 4 | | 2 | 23 | | 3 | 23 | | 4 | 2 | | 5 | 15 | | 6 | 12 | | 7 | 13 | | 8 | 2 | | 9 | 16 | | 10 | 18 | | 11 | 17 | | 12 | 3 | | 13 | 11 | | 14 | 14 | | 15 | 8 | | 16 | 7 | | 17 | 3 | | 18 | 2 | | 19 | 19 | | 20 | 14 | | 21 | 21 | | 22 | 5 | | 23 | 10 | | 24 | 21 | | 25 | 13 | | 26 | 7 | | 27 | 13 | | 28 | 8 | | 29 | 14 | | 30 | 17 | | 31 | 4 | | 32 | 15 | | 33 | 23 | | 34 | 9 | | 35 | 20 | | 36 | 1 | | 37 | 21 | | 38 | 16 | | 39 | 3 | | 40 | 29 | | 41 | 8 | | 42 | 3 | | 43 | 1 | | 44 | 8 | | 45 | 13 | | 46 | 2 | | 47 | 2 | | 48 | 25 | | 49 | 3 |
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| 47.99% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3448275862068966 | | totalSentences | 116 | | uniqueOpeners | 40 | |
| 34.72% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 96 | | matches | | 0 | "Then, like a held breath" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 96 | | matches | | 0 | "Her breath came steady, measured," | | 1 | "He glanced back once—just a" | | 2 | "He stumbled, recovered, then veered" | | 3 | "She took the turn at" | | 4 | "She reached for the handle—cold," | | 5 | "It didn’t budge." | | 6 | "She exhaled through her nose," | | 7 | "She descended, one hand on" | | 8 | "She knew that mark." | | 9 | "Their flames burned blue, green," | | 10 | "She looked down." | | 11 | "She gestured to the bones" | | 12 | "She could chase him deeper," | | 13 | "She met the woman’s gaze." | | 14 | "She reached into her cloak" | | 15 | "She jerked her chin toward" | | 16 | "She leaned in, her breath" | | 17 | "She stepped over the bones," | | 18 | "She slid through, the velvet" | | 19 | "Her boots stuck slightly with" |
| | ratio | 0.25 | |
| 27.71% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 83 | | totalSentences | 96 | | matches | | 0 | "Harlow Quinn didn’t flinch." | | 1 | "Her breath came steady, measured," | | 2 | "The suspect—tall, lanky, dressed in" | | 3 | "The alley reeked of damp" | | 4 | "A fire escape groaned overhead," | | 5 | "Harlow’s fingers brushed the grip" | | 6 | "The suspect was fast, but" | | 7 | "He glanced back once—just a" | | 8 | "He stumbled, recovered, then veered" | | 9 | "Harlow didn’t hesitate." | | 10 | "She took the turn at" | | 11 | "The passage dead-ended at a" | | 12 | "The suspect wrenched it open" | | 13 | "She reached for the handle—cold," | | 14 | "It didn’t budge." | | 15 | "She exhaled through her nose," | | 16 | "The metal screamed, the lock" | | 17 | "Darkness yawned beyond it, the" | | 18 | "A staircase descended into black." | | 19 | "Harlow pulled her torch from" |
| | ratio | 0.865 | |
| 52.08% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 96 | | matches | | 0 | "Because the runner wasn’t just" |
| | ratio | 0.01 | |
| 86.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 4 | | matches | | 0 | "The suspect—tall, lanky, dressed in a hooded jacket that flapped like a crow’s wings—ducked left, disappearing into the maze of Soho’s back alleys." | | 1 | "Their flames burned blue, green, violet, casting long shadows over the stalls that cluttered the space." | | 2 | "The walls wept something darker, something that glistened like oil in her torchlight." | | 3 | "She drew her weapon, the slide clicking back with a sound that seemed too loud in the suffocating quiet." |
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| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 1 | | matches | | 0 | "She leaned in, her breath hot against Harlow’s ear" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |