| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 90 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.75% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2040 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "sweetly" | | 1 | "perfectly" | | 2 | "very" | | 3 | "quickly" | | 4 | "slowly" |
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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) | |
| 75.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2040 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "porcelain" | | 1 | "silence" | | 2 | "charm" | | 3 | "etched" | | 4 | "flicked" | | 5 | "trembled" | | 6 | "aligned" | | 7 | "footsteps" | | 8 | "traced" |
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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 | 211 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 5 | | narrationSentences | 211 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 281 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2037 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 25 | | unquotedAttributions | 1 | | matches | | 0 | "Behind her, Bell said her name, but the sound seemed to come from far away." |
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| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 83 | | wordCount | 1630 | | uniqueNames | 9 | | maxNameDensity | 2.33 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 38 | | Northern | 1 | | Line | 1 | | Eva | 26 | | Kowalski | 1 | | Bell | 9 | | Morris | 5 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Line" | | 3 | "Eva" | | 4 | "Kowalski" | | 5 | "Bell" | | 6 | "Morris" |
| | places | (empty) | | globalScore | 0.334 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 119 | | glossingSentenceCount | 1 | | matches | | |
| 52.72% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 1.473 | | wordCount | 2037 | | matches | | 0 | "not tunnel dust, which was brown with damp, but fine" | | 1 | "Not any alphabet she knew, but the arrangement stirred a memory from three years ago: a pie" | | 2 | "not a room, but a crowded street beneath a sky with no stars" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 281 | | matches | | 0 | "joking that it" | | 1 | "saw that each" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 171 | | mean | 11.91 | | std | 14.15 | | cv | 1.188 | | sampleLengths | | 0 | 22 | | 1 | 36 | | 2 | 10 | | 3 | 2 | | 4 | 67 | | 5 | 3 | | 6 | 59 | | 7 | 7 | | 8 | 3 | | 9 | 13 | | 10 | 3 | | 11 | 2 | | 12 | 5 | | 13 | 5 | | 14 | 4 | | 15 | 58 | | 16 | 5 | | 17 | 25 | | 18 | 3 | | 19 | 2 | | 20 | 4 | | 21 | 13 | | 22 | 2 | | 23 | 3 | | 24 | 4 | | 25 | 4 | | 26 | 18 | | 27 | 6 | | 28 | 9 | | 29 | 2 | | 30 | 7 | | 31 | 36 | | 32 | 2 | | 33 | 4 | | 34 | 10 | | 35 | 68 | | 36 | 6 | | 37 | 3 | | 38 | 10 | | 39 | 12 | | 40 | 4 | | 41 | 4 | | 42 | 11 | | 43 | 3 | | 44 | 9 | | 45 | 46 | | 46 | 31 | | 47 | 4 | | 48 | 4 | | 49 | 9 |
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| 88.63% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 10 | | totalSentences | 211 | | matches | | 0 | "been abandoned" | | 1 | "been flooded" | | 2 | "were caked" | | 3 | "been etched" | | 4 | "was gone" | | 5 | "been etched" | | 6 | "was gone" | | 7 | "was interrupted" | | 8 | "been dragged" | | 9 | "was blistered" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 291 | | matches | | 0 | "were burning" | | 1 | "was staring" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 281 | | ratio | 0.011 | | matches | | 0 | "The soles were caked in pale gray dust—not tunnel dust, which was brown with damp, but fine and powdery, like ash." | | 1 | "Not damp from rain or condensation—soaked through in a neat crescent around the neck." | | 2 | "It traced the outline of the station, then extended beyond it—through the platform, beneath the city, toward a point marked by a tiny black circle." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1636 | | adjectiveStacks | 1 | | stackExamples | | 0 | "green, blue, black, gold." |
| | adverbCount | 50 | | adverbRatio | 0.030562347188264057 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.006723716381418093 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 281 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 281 | | mean | 7.25 | | std | 5.44 | | cv | 0.75 | | sampleLengths | | 0 | 22 | | 1 | 15 | | 2 | 6 | | 3 | 15 | | 4 | 10 | | 5 | 2 | | 6 | 15 | | 7 | 11 | | 8 | 15 | | 9 | 26 | | 10 | 3 | | 11 | 17 | | 12 | 19 | | 13 | 7 | | 14 | 16 | | 15 | 7 | | 16 | 3 | | 17 | 6 | | 18 | 7 | | 19 | 3 | | 20 | 2 | | 21 | 5 | | 22 | 5 | | 23 | 4 | | 24 | 16 | | 25 | 22 | | 26 | 6 | | 27 | 14 | | 28 | 2 | | 29 | 3 | | 30 | 9 | | 31 | 16 | | 32 | 3 | | 33 | 2 | | 34 | 4 | | 35 | 6 | | 36 | 7 | | 37 | 2 | | 38 | 3 | | 39 | 4 | | 40 | 4 | | 41 | 5 | | 42 | 7 | | 43 | 5 | | 44 | 1 | | 45 | 6 | | 46 | 9 | | 47 | 2 | | 48 | 7 | | 49 | 2 |
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| 43.95% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.298932384341637 | | totalSentences | 281 | | uniqueOpeners | 84 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 8 | | totalSentences | 178 | | matches | | 0 | "Perhaps that was why Quinn" | | 1 | "Instead, they curled into small" | | 2 | "At least one question had" | | 3 | "Only the dust, sprinkled in" | | 4 | "Too long, too narrow." | | 5 | "Just enough for Quinn to" | | 6 | "Somewhere in that impossible distance," | | 7 | "Then she saw the gray" |
| | ratio | 0.045 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 178 | | matches | | 0 | "They glowed a sickly amber" | | 1 | "Her left wrist was damp" | | 2 | "She wiped it with her" | | 3 | "Her curly red hair had" | | 4 | "She looked more like a" | | 5 | "He wore a dark wool" | | 6 | "It lay perfectly still, reflecting" | | 7 | "She stood and moved closer" | | 8 | "His boots were clean, except" | | 9 | "She examined the exposed hand." | | 10 | "It appeared in the margins" | | 11 | "She had assumed it was" | | 12 | "She took the token with" | | 13 | "It was warm." | | 14 | "It did not run along" | | 15 | "It seemed to lie inside" | | 16 | "She set it in an" | | 17 | "She inspected the mask." | | 18 | "She leaned closer." | | 19 | "It was small enough to" |
| | ratio | 0.213 | |
| 69.55% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 139 | | totalSentences | 178 | | matches | | 0 | "The station had been abandoned" | | 1 | "They glowed a sickly amber" | | 2 | "Water ticked somewhere in the" | | 3 | "The air smelled of wet" | | 4 | "Quinn paused on the last" | | 5 | "Her left wrist was damp" | | 6 | "She wiped it with her" | | 7 | "Eva stood beside the tiled" | | 8 | "Her curly red hair had" | | 9 | "She looked more like a" | | 10 | "Quinn descended onto the platform" | | 11 | "Eva glanced toward the body." | | 12 | "That was not an answer." | | 13 | "Quinn followed her gaze." | | 14 | "A man lay on the" | | 15 | "He wore a dark wool" | | 16 | "The other gripped a white" | | 17 | "A constable waited beside the" | | 18 | "Quinn looked at Eva." | | 19 | "Quinn let the silence settle." |
| | ratio | 0.781 | |
| 28.09% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 178 | | matches | | 0 | "Now she could not look" |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 59 | | technicalSentenceCount | 1 | | matches | | 0 | "The soles were caked in pale gray dust—not tunnel dust, which was brown with damp, but fine and powdery, like ash." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 19 | | fancyCount | 2 | | fancyTags | | 0 | "Eva murmured (murmur)" | | 1 | "it whispered (whisper)" |
| | dialogueSentences | 90 | | tagDensity | 0.211 | | leniency | 0.422 | | rawRatio | 0.105 | | effectiveRatio | 0.044 | |