| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 23 | | tagDensity | 0.261 | | leniency | 0.522 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.95% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 830 | | totalAiIsmAdverbs | 2 | | 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) | |
| 15.66% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 830 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "silence" | | 1 | "stomach" | | 2 | "familiar" | | 3 | "weight" | | 4 | "whisper" | | 5 | "etched" | | 6 | "pulse" | | 7 | "flicked" | | 8 | "raced" | | 9 | "echoed" | | 10 | "tension" | | 11 | "trembled" | | 12 | "pounding" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 64 | | matches | | |
| 75.89% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 64 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 81 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 8 | | markdownWords | 8 | | totalWords | 819 | | ratio | 0.01 | | matches | | 0 | "breathe" | | 1 | "not" | | 2 | "draining" | | 3 | "power" | | 4 | "slowly" | | 5 | "personal" | | 6 | "click" | | 7 | "door" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 38.23% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 671 | | uniqueNames | 8 | | maxNameDensity | 2.24 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Harlow" | | discoveredNames | | Tube | 1 | | Harlow | 15 | | Quinn | 1 | | Veil | 1 | | Market | 1 | | Camden | 1 | | Kowalski | 1 | | Eva | 12 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Kowalski" | | 4 | "Eva" |
| | places | (empty) | | globalScore | 0.382 | | windowScore | 0.5 | |
| 33.72% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 2 | | matches | | 0 | "smelled like damp stone and something olde" | | 1 | "quite human—too pale, too still" |
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| 77.90% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.221 | | wordCount | 819 | | matches | | 0 | "Not a victim of a fall or a struggle, but something else entirely" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 81 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 25.59 | | std | 22.75 | | cv | 0.889 | | sampleLengths | | 0 | 63 | | 1 | 50 | | 2 | 4 | | 3 | 89 | | 4 | 2 | | 5 | 5 | | 6 | 57 | | 7 | 10 | | 8 | 11 | | 9 | 15 | | 10 | 40 | | 11 | 13 | | 12 | 67 | | 13 | 10 | | 14 | 39 | | 15 | 43 | | 16 | 22 | | 17 | 11 | | 18 | 44 | | 19 | 5 | | 20 | 24 | | 21 | 7 | | 22 | 16 | | 23 | 18 | | 24 | 5 | | 25 | 48 | | 26 | 3 | | 27 | 6 | | 28 | 54 | | 29 | 6 | | 30 | 11 | | 31 | 21 |
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| 94.30% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 64 | | matches | | 0 | "was stretched" | | 1 | "been drained" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 113 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 81 | | ratio | 0.074 | | matches | | 0 | "The air in the abandoned Tube station smelled like damp stone and something older—something that clung to the walls like a second skin." | | 1 | "The usual chaos of the market—laughter, the clatter of trinkets, the scent of incense and something darker—had vanished." | | 2 | "The coroner’s report would say it was a homicide, but something about the way the air around the body seemed to *breathe*—like the victim had been drained of something more than blood." | | 3 | "But this—this was different." | | 4 | "He staggered, his hood slipping back to reveal a face that wasn’t quite human—too pale, too still." | | 5 | "And as they stepped through, the world around them dissolved into something far stranger—and far more dangerous—than anything they’d ever imagined." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 681 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.03671071953010279 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005873715124816446 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 81 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 81 | | mean | 10.11 | | std | 7.28 | | cv | 0.72 | | sampleLengths | | 0 | 23 | | 1 | 22 | | 2 | 16 | | 3 | 2 | | 4 | 17 | | 5 | 18 | | 6 | 15 | | 7 | 4 | | 8 | 12 | | 9 | 13 | | 10 | 16 | | 11 | 3 | | 12 | 13 | | 13 | 32 | | 14 | 2 | | 15 | 4 | | 16 | 1 | | 17 | 9 | | 18 | 2 | | 19 | 2 | | 20 | 24 | | 21 | 20 | | 22 | 10 | | 23 | 6 | | 24 | 5 | | 25 | 10 | | 26 | 5 | | 27 | 17 | | 28 | 10 | | 29 | 13 | | 30 | 9 | | 31 | 4 | | 32 | 6 | | 33 | 26 | | 34 | 18 | | 35 | 17 | | 36 | 6 | | 37 | 4 | | 38 | 10 | | 39 | 29 | | 40 | 3 | | 41 | 19 | | 42 | 4 | | 43 | 3 | | 44 | 6 | | 45 | 8 | | 46 | 19 | | 47 | 3 | | 48 | 2 | | 49 | 9 |
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| 47.74% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.30864197530864196 | | totalSentences | 81 | | uniqueOpeners | 25 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 58 | | matches | | 0 | "Only silence remained, thick as" | | 1 | "Then she saw it." | | 2 | "Then he collapsed." |
| | ratio | 0.052 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 58 | | matches | | 0 | "She stepped over the rusted" | | 1 | "She knelt, her military precision" | | 2 | "She didn’t look up." | | 3 | "She gestured to the body" | | 4 | "She reached into her coat" | | 5 | "She’d been part of the" | | 6 | "His fingers twitched toward something" | | 7 | "She drew her revolver, her" | | 8 | "He staggered, his hood slipping" | | 9 | "His eyes locked onto hers," | | 10 | "She was already moving, her" |
| | ratio | 0.19 | |
| 11.72% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 58 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn adjusted the" | | 2 | "The Veil Market had always" | | 3 | "She stepped over the rusted" | | 4 | "The usual chaos of the" | | 5 | "A body, sprawled across the" | | 6 | "The skin around the throat" | | 7 | "Harlow’s stomach twisted." | | 8 | "She knelt, her military precision" | | 9 | "The coroner’s report would say" | | 10 | "She didn’t look up." | | 11 | "The voice was familiar, but" | | 12 | "Harlow stood, her watch ticking" | | 13 | "Eva Kowalski stood there, her" | | 14 | "Harlow said, voice low" | | 15 | "Eva’s smile didn’t reach her" | | 16 | "Harlow’s fingers tightened around the" | | 17 | "Eva stepped closer, her satchel" | | 18 | "She gestured to the body" | | 19 | "Harlow exhaled through her nose," |
| | ratio | 0.897 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 58 | | matches | (empty) | | ratio | 0 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 3 | | matches | | 0 | "The air in the abandoned Tube station smelled like damp stone and something older—something that clung to the walls like a second skin." | | 1 | "He staggered, his hood slipping back to reveal a face that wasn’t quite human—too pale, too still." | | 2 | "She was already moving, her boots pounding against the metal grates as she led the way toward the rift." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 4 | | matches | | 0 | "Harlow said, voice low" | | 1 | "She reached, its casing etched with protective sigils" | | 2 | "Harlow said, her voice steady despite the unease creeping up her spine" | | 3 | "Harlow shot back, her voice cutting through the tension" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "Eva whispered (whisper)" |
| | dialogueSentences | 23 | | tagDensity | 0.13 | | leniency | 0.261 | | rawRatio | 0.333 | | effectiveRatio | 0.087 | |