| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 30 | | tagDensity | 0.267 | | leniency | 0.533 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 605 | | 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) | |
| 25.62% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 605 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoed" | | 2 | "flickered" | | 3 | "crystal" | | 4 | "scanning" | | 5 | "pulse" | | 6 | "quickened" | | 7 | "trembled" |
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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 | 1 | | narrationSentences | 76 | | matches | | |
| 86.47% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 76 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 19 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 603 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 28.59% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 453 | | uniqueNames | 15 | | maxNameDensity | 2.43 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Harlow" | | discoveredNames | | Detective | 1 | | Harlow | 11 | | Quinn | 1 | | Raven | 1 | | Nest | 1 | | Herrera | 1 | | Tomás | 11 | | Saint | 1 | | Christopher | 1 | | Distant | 1 | | Morris | 1 | | Elise | 4 | | Veil | 1 | | Market | 1 | | Rain | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Herrera" | | 4 | "Tomás" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Distant" | | 8 | "Morris" | | 9 | "Elise" | | 10 | "Market" | | 11 | "Rain" |
| | places | (empty) | | globalScore | 0.286 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 36 | | 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 | 603 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 36 | | mean | 16.75 | | std | 11.02 | | cv | 0.658 | | sampleLengths | | 0 | 50 | | 1 | 8 | | 2 | 25 | | 3 | 16 | | 4 | 11 | | 5 | 23 | | 6 | 27 | | 7 | 8 | | 8 | 31 | | 9 | 30 | | 10 | 8 | | 11 | 15 | | 12 | 49 | | 13 | 8 | | 14 | 9 | | 15 | 23 | | 16 | 11 | | 17 | 11 | | 18 | 14 | | 19 | 9 | | 20 | 27 | | 21 | 10 | | 22 | 13 | | 23 | 9 | | 24 | 19 | | 25 | 11 | | 26 | 6 | | 27 | 22 | | 28 | 2 | | 29 | 26 | | 30 | 5 | | 31 | 15 | | 32 | 17 | | 33 | 8 | | 34 | 6 | | 35 | 21 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 76 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 106 | | matches | (empty) | |
| 84.55% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 98 | | ratio | 0.02 | | matches | | 0 | "Behind her, footsteps echoed—light, hurried, deliberate." | | 1 | "A face Harlow recognized—DS Morris’s twin sister, Elise." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 455 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.017582417582417582 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.006593406593406593 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 6.15 | | std | 3.51 | | cv | 0.57 | | sampleLengths | | 0 | 8 | | 1 | 11 | | 2 | 16 | | 3 | 9 | | 4 | 6 | | 5 | 8 | | 6 | 9 | | 7 | 2 | | 8 | 11 | | 9 | 3 | | 10 | 12 | | 11 | 4 | | 12 | 7 | | 13 | 4 | | 14 | 12 | | 15 | 11 | | 16 | 12 | | 17 | 15 | | 18 | 3 | | 19 | 5 | | 20 | 3 | | 21 | 8 | | 22 | 5 | | 23 | 8 | | 24 | 7 | | 25 | 2 | | 26 | 7 | | 27 | 13 | | 28 | 8 | | 29 | 8 | | 30 | 7 | | 31 | 3 | | 32 | 5 | | 33 | 7 | | 34 | 11 | | 35 | 11 | | 36 | 9 | | 37 | 11 | | 38 | 6 | | 39 | 2 | | 40 | 6 | | 41 | 3 | | 42 | 19 | | 43 | 4 | | 44 | 6 | | 45 | 3 | | 46 | 2 | | 47 | 7 | | 48 | 4 | | 49 | 5 |
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| 72.79% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4489795918367347 | | totalSentences | 98 | | uniqueOpeners | 44 | |
| 49.02% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 68 | | matches | | 0 | "Somewhere, a clock struck midnight." |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 68 | | matches | | 0 | "She ran, boots splashing through" | | 1 | "she shouted, voice cutting through" | | 2 | "His scar caught the glow," | | 3 | "He didn’t slow." | | 4 | "She adjusted her leather watch," | | 5 | "He hesitated, hand drifting to" | | 6 | "She paused, listening" | | 7 | "She stepped toward a stall" | | 8 | "Her eyes burned with fury." | | 9 | "She met Elise’s gaze." | | 10 | "Her watch clicked once." | | 11 | "She turned to Tomás." | | 12 | "He nodded, eyes hollow." | | 13 | "It had only begun." |
| | ratio | 0.206 | |
| 11.47% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 68 | | matches | | 0 | "Rain fell in sheets across" | | 1 | "Streetlights blurred into smears of" | | 2 | "She ran, boots splashing through" | | 3 | "The air reeked of wet" | | 4 | "she shouted, voice cutting through" | | 5 | "A figure turned, silhouette sharp" | | 6 | "His scar caught the glow," | | 7 | "He didn’t slow." | | 8 | "Harlow called, breath fogging in" | | 9 | "Tomás glanced over his shoulder," | | 10 | "She adjusted her leather watch," | | 11 | "He hesitated, hand drifting to" | | 12 | "Harlow’s jaw tightened." | | 13 | "A sudden turn." | | 14 | "The alley narrowed, brick walls" | | 15 | "Rain drummed on metal grates." | | 16 | "Tomás darted left, disappearing into" | | 17 | "Harlow followed, boots slipping on" | | 18 | "Stairs spiraled downward, each step" | | 19 | "The air grew thicker, damp" |
| | ratio | 0.897 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 10 | | technicalSentenceCount | 1 | | matches | | 0 | "She ran, boots splashing through puddles that reflected the neon glow of The Raven’s Nest sign." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 4 | | matches | | 0 | "she shouted, voice cutting through the storm" | | 1 | "Harlow called, breath fogging in the cold" | | 2 | "She adjusted, fingers brushing the worn strap" | | 3 | "Tomás asked, voice low" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 30 | | tagDensity | 0.1 | | leniency | 0.2 | | rawRatio | 0.333 | | effectiveRatio | 0.067 | |