| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 589 | | tagDensity | 0.005 | | leniency | 0.01 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 11277 | | 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) | |
| 72.95% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 11277 | | totalAiIsms | 61 | | found | | | highlights | | 0 | "silence" | | 1 | "familiar" | | 2 | "weight" | | 3 | "traced" | | 4 | "etched" | | 5 | "flicked" | | 6 | "scanning" | | 7 | "pulsed" | | 8 | "racing" | | 9 | "echoing" | | 10 | "dancing" | | 11 | "pulse" | | 12 | "furrowed" | | 13 | "scanned" | | 14 | "trembled" |
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| 0.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 136 | | maxInWindow | 15 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 136 |
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| | highlights | | 0 | "eyes widened" | | 1 | "eyes narrowed" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 635 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 2 | | narrationSentences | 635 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 1221 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 11276 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 470 | | wordCount | 3243 | | uniqueNames | 6 | | maxNameDensity | 7.52 | | worstName | "Harlow" | | maxWindowNameDensity | 17 | | worstWindowName | "Eva" | | discoveredNames | | Harlow | 244 | | Quinn | 1 | | Kowalski | 1 | | Eva | 222 | | Veil | 1 | | Tube | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 211 | | 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 | 11276 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 1221 | | matches | (empty) | |
| 78.78% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 598 | | mean | 18.86 | | std | 8.03 | | cv | 0.426 | | sampleLengths | | 0 | 79 | | 1 | 82 | | 2 | 53 | | 3 | 55 | | 4 | 20 | | 5 | 21 | | 6 | 15 | | 7 | 26 | | 8 | 14 | | 9 | 12 | | 10 | 23 | | 11 | 18 | | 12 | 35 | | 13 | 15 | | 14 | 16 | | 15 | 20 | | 16 | 44 | | 17 | 11 | | 18 | 8 | | 19 | 19 | | 20 | 12 | | 21 | 20 | | 22 | 33 | | 23 | 8 | | 24 | 17 | | 25 | 51 | | 26 | 8 | | 27 | 11 | | 28 | 20 | | 29 | 8 | | 30 | 22 | | 31 | 42 | | 32 | 12 | | 33 | 19 | | 34 | 16 | | 35 | 19 | | 36 | 22 | | 37 | 22 | | 38 | 16 | | 39 | 19 | | 40 | 16 | | 41 | 20 | | 42 | 22 | | 43 | 19 | | 44 | 16 | | 45 | 22 | | 46 | 16 | | 47 | 19 | | 48 | 22 | | 49 | 22 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 635 | | matches | | 0 | "being pulled" | | 1 | "was surrounded" | | 2 | "was cloaked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 706 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 1221 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 4834 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 65 | | adverbRatio | 0.013446421183285064 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.0016549441456350847 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 1221 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 1221 | | mean | 9.24 | | std | 5.87 | | cv | 0.636 | | sampleLengths | | 0 | 14 | | 1 | 20 | | 2 | 16 | | 3 | 29 | | 4 | 10 | | 5 | 23 | | 6 | 11 | | 7 | 22 | | 8 | 16 | | 9 | 7 | | 10 | 14 | | 11 | 8 | | 12 | 11 | | 13 | 8 | | 14 | 5 | | 15 | 8 | | 16 | 14 | | 17 | 17 | | 18 | 16 | | 19 | 6 | | 20 | 14 | | 21 | 4 | | 22 | 17 | | 23 | 3 | | 24 | 12 | | 25 | 11 | | 26 | 15 | | 27 | 2 | | 28 | 12 | | 29 | 6 | | 30 | 6 | | 31 | 3 | | 32 | 6 | | 33 | 14 | | 34 | 2 | | 35 | 16 | | 36 | 7 | | 37 | 15 | | 38 | 13 | | 39 | 7 | | 40 | 8 | | 41 | 8 | | 42 | 8 | | 43 | 4 | | 44 | 16 | | 45 | 14 | | 46 | 13 | | 47 | 17 | | 48 | 5 | | 49 | 6 |
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| 39.35% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 130 | | diversityRatio | 0.0171990171990172 | | totalSentences | 1221 | | uniqueOpeners | 21 | |
| 5.29% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 630 | | matches | | 0 | "Just then, a figure emerged" |
| | ratio | 0.002 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 120 | | totalSentences | 630 | | matches | | 0 | "She slipped past the rusted" | | 1 | "Her salt‑and‑pepper hair brushed the" | | 2 | "She rose, her eyes flicking" | | 3 | "She wore round glasses that" | | 4 | "Her nervous habit of tucking" | | 5 | "She knelt beside the body," | | 6 | "She noticed a faint, almost" | | 7 | "she said, pointing to the" | | 8 | "She pushed aside a loose" | | 9 | "She turned to Eva." | | 10 | "She turned the compass, and" | | 11 | "She stepped forward, her boots" | | 12 | "She turned to Eva." | | 13 | "She turned the compass, and" | | 14 | "It was the market’s guardian," | | 15 | "She set it down, her" | | 16 | "She knelt beside the body," | | 17 | "She felt a faint hum," | | 18 | "She pushed aside the crates," | | 19 | "She turned to Eva." |
| | ratio | 0.19 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 627 | | totalSentences | 630 | | matches | | 0 | "The first thing Harlow Quinn" | | 1 | "She slipped past the rusted" | | 2 | "The air smelled faintly of" | | 3 | "Her salt‑and‑pepper hair brushed the" | | 4 | "There, in the centre of" | | 5 | "The victim’s skin was pallid," | | 6 | "The body lay face‑up, but" | | 7 | "A small, brass compass lay" | | 8 | "Harlow knelt, her fingers brushing" | | 9 | "The needle spun faster, then" | | 10 | "She rose, her eyes flicking" | | 11 | "The platform was empty save" | | 12 | "The evidence didn’t add up." | | 13 | "Eva Kowalski stepped onto the" | | 14 | "She wore round glasses that" | | 15 | "Her nervous habit of tucking" | | 16 | "Eva said, her voice low" | | 17 | "Harlow glanced at her." | | 18 | "Eva’s eyes widened." | | 19 | "She knelt beside the body," |
| | ratio | 0.995 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 630 | | matches | (empty) | | ratio | 0 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 5 | | matches | | 0 | "A small, brass compass lay beside the corpse, its needle twitching erratically as if it were being pulled by an unseen hand." | | 1 | "The glow intensified as she opened it, revealing a narrow passage that led deeper into the station." | | 2 | "The altar was surrounded by a circle of candles, each flame flickering as if held by an unseen breeze." | | 3 | "The only light came from a flickering bulb that sputtered, casting long shadows." | | 4 | "The glow intensified as she opened it, revealing a narrow passage that led deeper into the station." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 2 | | matches | | 0 | "Eva said, her voice low" | | 1 | "Eva said, voice low," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 589 | | tagDensity | 0.005 | | leniency | 0.01 | | rawRatio | 0 | | effectiveRatio | 0 | |