| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.357 | | leniency | 0.714 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 966 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 43.06% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 966 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "fluttered" | | 2 | "scanned" | | 3 | "perfect" | | 4 | "etched" | | 5 | "magnetic" | | 6 | "vibrated" | | 7 | "intensity" | | 8 | "pulsed" | | 9 | "echoing" | | 10 | "shimmered" |
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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 | 87 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 87 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 105 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 964 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 23.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 752 | | uniqueNames | 10 | | maxNameDensity | 2.53 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Quinn | 19 | | Sergeant | 1 | | Miller | 11 | | North | 1 | | South | 1 | | East | 1 | | West | 1 | | Morris | 1 | | Metropolitan | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Sergeant" | | 2 | "Miller" | | 3 | "Morris" |
| | places | (empty) | | globalScore | 0.237 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 964 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 105 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 18.9 | | std | 17.56 | | cv | 0.929 | | sampleLengths | | 0 | 59 | | 1 | 4 | | 2 | 44 | | 3 | 23 | | 4 | 51 | | 5 | 6 | | 6 | 7 | | 7 | 8 | | 8 | 50 | | 9 | 17 | | 10 | 9 | | 11 | 22 | | 12 | 41 | | 13 | 44 | | 14 | 5 | | 15 | 16 | | 16 | 2 | | 17 | 21 | | 18 | 41 | | 19 | 4 | | 20 | 2 | | 21 | 10 | | 22 | 52 | | 23 | 5 | | 24 | 2 | | 25 | 17 | | 26 | 55 | | 27 | 5 | | 28 | 4 | | 29 | 7 | | 30 | 50 | | 31 | 13 | | 32 | 8 | | 33 | 14 | | 34 | 9 | | 35 | 43 | | 36 | 6 | | 37 | 5 | | 38 | 4 | | 39 | 2 | | 40 | 40 | | 41 | 8 | | 42 | 5 | | 43 | 29 | | 44 | 5 | | 45 | 4 | | 46 | 2 | | 47 | 33 | | 48 | 14 | | 49 | 26 |
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| 97.20% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 87 | | matches | | 0 | "been carved" | | 1 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 128 | | matches | | |
| 61.22% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 105 | | ratio | 0.029 | | matches | | 0 | "Only one set of tracks existed—those leading toward the man." | | 1 | "She remembered the files on DS Morris—the unexplained disappearances, the reports of \"ghost stations\" that didn't appear on any Metropolitan map." | | 2 | "The liquid didn't soak into the concrete; it flowed backward, defying gravity, sliding up the man's skin and disappearing back into the wound." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 754 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.023872679045092837 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003978779840848806 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 105 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 105 | | mean | 9.18 | | std | 5.53 | | cv | 0.603 | | sampleLengths | | 0 | 13 | | 1 | 18 | | 2 | 17 | | 3 | 11 | | 4 | 4 | | 5 | 17 | | 6 | 10 | | 7 | 17 | | 8 | 3 | | 9 | 20 | | 10 | 7 | | 11 | 6 | | 12 | 5 | | 13 | 10 | | 14 | 13 | | 15 | 10 | | 16 | 6 | | 17 | 7 | | 18 | 8 | | 19 | 2 | | 20 | 11 | | 21 | 2 | | 22 | 2 | | 23 | 3 | | 24 | 7 | | 25 | 23 | | 26 | 17 | | 27 | 9 | | 28 | 22 | | 29 | 3 | | 30 | 11 | | 31 | 15 | | 32 | 8 | | 33 | 4 | | 34 | 7 | | 35 | 8 | | 36 | 9 | | 37 | 20 | | 38 | 5 | | 39 | 5 | | 40 | 11 | | 41 | 2 | | 42 | 21 | | 43 | 11 | | 44 | 7 | | 45 | 4 | | 46 | 13 | | 47 | 6 | | 48 | 4 | | 49 | 2 |
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| 40.48% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.2761904761904762 | | totalSentences | 105 | | uniqueOpeners | 29 | |
| 44.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 75 | | matches | | 0 | "Only one set of tracks" |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 75 | | matches | | 0 | "She glanced at the worn" | | 1 | "She didn't look at the" | | 2 | "Her eyes scanned the perimeter." | | 3 | "It looked painted." | | 4 | "She leaned closer, her sharp" | | 5 | "She spotted a glimmer of" | | 6 | "She reached out, her fingers" | | 7 | "She flipped the lid." | | 8 | "It spun in a violent," | | 9 | "She pressed her palm against" | | 10 | "She looked back at the" | | 11 | "He wore a heavy wool" | | 12 | "She reached into the coat" | | 13 | "It had been carved into" | | 14 | "She looked at the blood" | | 15 | "She remembered the files on" | | 16 | "She watched the man's chest" | | 17 | "His eyes shifted, focusing on" | | 18 | "He didn't look terrified." | | 19 | "He looked exhausted." |
| | ratio | 0.293 | |
| 13.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 75 | | matches | | 0 | "The descent into the abandoned" | | 1 | "Dust motes danced in the" | | 2 | "Harlow Quinn stepped over a" | | 3 | "She glanced at the worn" | | 4 | "A circle of yellow tape" | | 5 | "Detective Sergeant Miller stood over" | | 6 | "Quinn stopped three feet from" | | 7 | "She didn't look at the" | | 8 | "Her eyes scanned the perimeter." | | 9 | "The platform was empty of" | | 10 | "Miller frowned, glancing back at" | | 11 | "The blood formed a perfect," | | 12 | "It looked painted." | | 13 | "She leaned closer, her sharp" | | 14 | "The victim’s face remained frozen" | | 15 | "Miller sighed and tapped his" | | 16 | "Quinn ignored him." | | 17 | "She spotted a glimmer of" | | 18 | "She reached out, her fingers" | | 19 | "A thick patina of verdigris" |
| | ratio | 0.893 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 75 | | matches | (empty) | | ratio | 0 | |
| 99.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 2 | | matches | | 0 | "Dust motes danced in the beams of industrial torches, illuminating tiles that had peeled away like dead skin." | | 1 | "The needle on the compass stopped vibrating and pointed straight ahead, as if the wall had ceased to exist." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 2 | | matches | | 0 | "She remembered, the reports of" | | 1 | "Miller stammered, his face pale" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 5 | | fancyTags | | 0 | "Miller noted (note)" | | 1 | "Quinn observed (observe)" | | 2 | "Quinn whispered (whisper)" | | 3 | "Quinn stated (state)" | | 4 | "Miller stammered (stammer)" |
| | dialogueSentences | 28 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.714 | | effectiveRatio | 0.357 | |