| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 91.70% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1808 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "carefully" | | 1 | "gently" | | 2 | "perfectly" |
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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) | |
| 66.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1808 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "silence" | | 1 | "scanning" | | 2 | "standard" | | 3 | "trembled" | | 4 | "perfect" | | 5 | "unreadable" | | 6 | "echoed" | | 7 | "weight" | | 8 | "traced" | | 9 | "quickened" | | 10 | "tracing" | | 11 | "unwavering" |
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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 | 259 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 259 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 259 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1808 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1808 | | uniqueNames | 11 | | maxNameDensity | 0.77 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 3 | | Quinn | 14 | | Camden | 3 | | Miller | 7 | | Kowalski | 1 | | Town | 1 | | British | 1 | | Museum | 2 | | Eva | 4 | | You | 10 | | One | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Miller" | | 3 | "Kowalski" | | 4 | "Museum" | | 5 | "Eva" | | 6 | "You" | | 7 | "One" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 142 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1808 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 259 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 43.05 | | std | 27.8 | | cv | 0.646 | | sampleLengths | | 0 | 111 | | 1 | 42 | | 2 | 6 | | 3 | 90 | | 4 | 13 | | 5 | 96 | | 6 | 27 | | 7 | 34 | | 8 | 71 | | 9 | 8 | | 10 | 44 | | 11 | 29 | | 12 | 19 | | 13 | 71 | | 14 | 9 | | 15 | 92 | | 16 | 51 | | 17 | 20 | | 18 | 24 | | 19 | 15 | | 20 | 58 | | 21 | 34 | | 22 | 31 | | 23 | 22 | | 24 | 70 | | 25 | 21 | | 26 | 54 | | 27 | 46 | | 28 | 55 | | 29 | 50 | | 30 | 51 | | 31 | 29 | | 32 | 30 | | 33 | 30 | | 34 | 26 | | 35 | 31 | | 36 | 30 | | 37 | 51 | | 38 | 31 | | 39 | 57 | | 40 | 8 | | 41 | 121 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 259 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 341 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 259 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1815 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.017079889807162536 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.005509641873278237 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 259 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 259 | | mean | 6.98 | | std | 4.36 | | cv | 0.624 | | sampleLengths | | 0 | 18 | | 1 | 19 | | 2 | 15 | | 3 | 17 | | 4 | 8 | | 5 | 11 | | 6 | 4 | | 7 | 15 | | 8 | 2 | | 9 | 2 | | 10 | 14 | | 11 | 11 | | 12 | 17 | | 13 | 6 | | 14 | 9 | | 15 | 6 | | 16 | 8 | | 17 | 5 | | 18 | 15 | | 19 | 20 | | 20 | 4 | | 21 | 4 | | 22 | 7 | | 23 | 3 | | 24 | 9 | | 25 | 10 | | 26 | 3 | | 27 | 12 | | 28 | 10 | | 29 | 10 | | 30 | 7 | | 31 | 12 | | 32 | 5 | | 33 | 3 | | 34 | 4 | | 35 | 9 | | 36 | 14 | | 37 | 10 | | 38 | 9 | | 39 | 3 | | 40 | 4 | | 41 | 11 | | 42 | 10 | | 43 | 12 | | 44 | 8 | | 45 | 4 | | 46 | 7 | | 47 | 17 | | 48 | 13 | | 49 | 6 |
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| 34.94% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 39 | | diversityRatio | 0.28957528957528955 | | totalSentences | 259 | | uniqueOpeners | 75 | |
| 44.25% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 226 | | matches | | 0 | "Just a drunk who wandered" | | 1 | "Just ran a thumb over" | | 2 | "Just a man who bought" |
| | ratio | 0.013 | |
| 74.87% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 82 | | totalSentences | 226 | | matches | | 0 | "She stepped onto the abandoned" | | 1 | "She glanced at the worn" | | 2 | "He wore a thin jacket" | | 3 | "You brought the wrong forensics" | | 4 | "She stopped ten feet from" | | 5 | "He tripped on a loose" | | 6 | "She unbuttoned her coat, revealing" | | 7 | "Her sharp jaw tightened as" | | 8 | "She hooked a gloved finger" | | 9 | "She set it carefully on" | | 10 | "He gestured toward the far" | | 11 | "She walked the circumference of" | | 12 | "His shoes bore fresh tread" | | 13 | "You're reading too much into" | | 14 | "She turned, letting the work" | | 15 | "Her brown eyes stayed flat," | | 16 | "She reached into her pocket" | | 17 | "You checked his pockets." | | 18 | "You didn't check his teeth." | | 19 | "He stepped closer, squinting at" |
| | ratio | 0.363 | |
| 39.65% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 190 | | totalSentences | 226 | | matches | | 0 | "The steel door groaned as" | | 1 | "She stepped onto the abandoned" | | 2 | "The fluorescent work lights strung" | | 3 | "Dust clung to the air" | | 4 | "She glanced at the worn" | | 5 | "The precinct had flagged the" | | 6 | "A blue tarp hung slack" | | 7 | "DC Miller stood beside it," | | 8 | "He wore a thin jacket" | | 9 | "You brought the wrong forensics" | | 10 | "Quinn moved past him, her" | | 11 | "The tiles showed decades of" | | 12 | "Water stains mapped the pillars" | | 13 | "Graffiti faded into black mold." | | 14 | "She stopped ten feet from" | | 15 | "The tarp covered a male" | | 16 | "Dust coated his jacket." | | 17 | "Grime caked his shoes." | | 18 | "The platform floor bore no" | | 19 | "He tripped on a loose" |
| | ratio | 0.841 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 226 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 64 | | technicalSentenceCount | 1 | | matches | | 0 | "The steel door groaned as Harlow Quinn forced it open, her boots clicking against the rusted track plating." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |