| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 45 | | tagDensity | 0.289 | | leniency | 0.578 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 85.67% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1744 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "sharply" | | 1 | "perfectly" | | 2 | "gently" | | 3 | "slowly" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 74.20% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1744 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "shattered" | | 1 | "footsteps" | | 2 | "echoing" | | 3 | "chill" | | 4 | "perfect" | | 5 | "weight" | | 6 | "crystalline" | | 7 | "furrowed" |
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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 | 122 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 122 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 154 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 69 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 5 | | totalWords | 1731 | | ratio | 0.003 | | matches | | 0 | "—genesis" | | 1 | "They’re watching the station." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 80.80% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1156 | | uniqueNames | 10 | | maxNameDensity | 1.38 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 16 | | Quinn | 2 | | Northern | 1 | | Line | 1 | | Victorian | 1 | | Samir | 1 | | Patel | 14 | | Wapping | 1 | | Okonkwo | 1 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Samir" | | 3 | "Patel" | | 4 | "Okonkwo" | | 5 | "Morris" |
| | places | (empty) | | globalScore | 0.808 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.578 | | wordCount | 1731 | | matches | | 0 | "not the usual cardinal directions, but something older" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 154 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 71 | | mean | 24.38 | | std | 17.81 | | cv | 0.73 | | sampleLengths | | 0 | 48 | | 1 | 42 | | 2 | 46 | | 3 | 19 | | 4 | 16 | | 5 | 52 | | 6 | 17 | | 7 | 18 | | 8 | 3 | | 9 | 54 | | 10 | 47 | | 11 | 51 | | 12 | 23 | | 13 | 3 | | 14 | 35 | | 15 | 11 | | 16 | 69 | | 17 | 52 | | 18 | 17 | | 19 | 46 | | 20 | 27 | | 21 | 13 | | 22 | 11 | | 23 | 23 | | 24 | 15 | | 25 | 58 | | 26 | 1 | | 27 | 6 | | 28 | 4 | | 29 | 11 | | 30 | 34 | | 31 | 43 | | 32 | 6 | | 33 | 19 | | 34 | 53 | | 35 | 4 | | 36 | 17 | | 37 | 20 | | 38 | 6 | | 39 | 52 | | 40 | 22 | | 41 | 42 | | 42 | 4 | | 43 | 42 | | 44 | 5 | | 45 | 20 | | 46 | 28 | | 47 | 6 | | 48 | 45 | | 49 | 5 |
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| 99.51% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 122 | | matches | | 0 | "were coated" | | 1 | "been disturbed" | | 2 | "was clenched" |
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| 94.74% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 190 | | matches | | 0 | "was bleeding" | | 1 | "wasn’t pointing" | | 2 | "was pointing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 154 | | ratio | 0.065 | | matches | | 0 | "The air hit her first—damp cement and the copper tang of blood, undercut by something sharper." | | 1 | "She’d worked murders in stranger places—a disused meatpacking plant in Wapping came to mind—but something about this platform gnawed at her." | | 2 | "Not the ambient chill of a subterranean room—this was the kind of cold that seeped into bone." | | 3 | "The smell hit her again—that ozone charge." | | 4 | "The glass was thin, delicate—laboratory grade." | | 5 | "A faded label clung to one edge, the ink smeared but still legible enough to make out a partial word: *—genesis*." | | 6 | "The signal levers were coated in decades of grime, but several of them had been disturbed—clean streaks where hands had gripped the metal." | | 7 | "But the floor—the floor was marked with a trail of dark droplets that led away from the signal room." | | 8 | "She studied the man’s face—pale, unshaven, with deep shadows under the eyes." | | 9 | "Strange symbols she didn’t recognize covered the face—not the usual cardinal directions, but something older." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1168 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.026541095890410957 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.0059931506849315065 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 154 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 154 | | mean | 11.24 | | std | 9.29 | | cv | 0.827 | | sampleLengths | | 0 | 19 | | 1 | 16 | | 2 | 2 | | 3 | 11 | | 4 | 7 | | 5 | 20 | | 6 | 5 | | 7 | 10 | | 8 | 25 | | 9 | 21 | | 10 | 19 | | 11 | 9 | | 12 | 7 | | 13 | 17 | | 14 | 3 | | 15 | 21 | | 16 | 4 | | 17 | 7 | | 18 | 11 | | 19 | 6 | | 20 | 8 | | 21 | 10 | | 22 | 3 | | 23 | 15 | | 24 | 39 | | 25 | 4 | | 26 | 16 | | 27 | 17 | | 28 | 10 | | 29 | 28 | | 30 | 23 | | 31 | 9 | | 32 | 7 | | 33 | 5 | | 34 | 2 | | 35 | 3 | | 36 | 24 | | 37 | 11 | | 38 | 4 | | 39 | 7 | | 40 | 69 | | 41 | 4 | | 42 | 10 | | 43 | 14 | | 44 | 24 | | 45 | 11 | | 46 | 1 | | 47 | 5 | | 48 | 22 | | 49 | 15 |
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| 64.50% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.4025974025974026 | | totalSentences | 154 | | uniqueOpeners | 62 | |
| 90.09% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 111 | | matches | | 0 | "Almost body temperature." | | 1 | "Just a body in an" | | 2 | "Somewhere in the distance, metal" |
| | ratio | 0.027 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 111 | | matches | | 0 | "She swept her torch across" | | 1 | "His usual easy demeanor had" | | 2 | "She’d worked murders in stranger" | | 3 | "She crossed the platform, her" | | 4 | "She stepped through the signal" | | 5 | "She shifted her weight and" | | 6 | "She angled her torch downward." | | 7 | "She picked up the largest" | | 8 | "She held the fragment up" | | 9 | "He stepped away to answer" | | 10 | "She swept her torch in" | | 11 | "She followed the line of" | | 12 | "He looked up from his" | | 13 | "She shone her torch inside." | | 14 | "She crouched and aimed her" | | 15 | "She pulled out her phone" | | 16 | "She gestured at the blood" | | 17 | "She studied the man’s face—pale," | | 18 | "His clothes were unremarkable: dark" | | 19 | "It was a small brass" |
| | ratio | 0.297 | |
| 45.59% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 92 | | totalSentences | 111 | | matches | | 0 | "Detective Harlow Quinn ducked under" | | 1 | "The air hit her first—damp" | | 2 | "The kind of charge in" | | 3 | "She swept her torch across" | | 4 | "The beam caught the old" | | 5 | "Ticket machines rusted to husks." | | 6 | "A skeletal information booth with" | | 7 | "DC Samir Patel emerged from" | | 8 | "His usual easy demeanor had" | | 9 | "Patel gestured toward the far" | | 10 | "Harlow followed his line of" | | 11 | "The signal room." | | 12 | "She’d worked murders in stranger" | | 13 | "The walls were wrong." | | 14 | "The shadows sat at angles" | | 15 | "She crossed the platform, her" | | 16 | "Patel’s torch beam danced alongside" | | 17 | "Patel shook his head" | | 18 | "Harlow filed that away." | | 19 | "She stepped through the signal" |
| | ratio | 0.829 | |
| 90.09% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 111 | | matches | | 0 | "As if they had fallen" | | 1 | "As if whatever was bleeding" |
| | ratio | 0.018 | |
| 84.55% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 4 | | matches | | 0 | "His usual easy demeanor had evaporated, replaced by the tight-jawed look of a man who had seen something he couldn’t explain." | | 1 | "The body lay crumpled against a bank of ancient signal levers, arms outflung as if the man had been trying to push himself backward in his final moment." | | 2 | "But the lips of the wound were sealed shut in a dark seam, as if someone had taken a soldering iron to exposed meat." | | 3 | "A scatter of broken vials lay near the body, their contents dried to a crystalline residue that glittered amber under the light." |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "She slipped, but the needle continued to track her movement even through the plastic" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 45 | | tagDensity | 0.067 | | leniency | 0.133 | | rawRatio | 0 | | effectiveRatio | 0 | |