| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.58% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 594 | | 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) | |
| 24.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 594 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "navigated" | | 1 | "stomach" | | 2 | "lurch" | | 3 | "jaw clenched" | | 4 | "footsteps" | | 5 | "echoed" | | 6 | "wavered" | | 7 | "determined" | | 8 | "etched" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 39 | | matches | (empty) | |
| 32.97% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 39 | | filterMatches | | | hedgeMatches | | 0 | "happened to" | | 1 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 45 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 592 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 40.66% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 503 | | uniqueNames | 12 | | maxNameDensity | 2.19 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Quinn | 11 | | Soho | 1 | | London | 1 | | Morris | 4 | | Camden | 1 | | Tube | 1 | | Underground | 1 | | Tomás | 1 | | Herrera | 3 | | Saint | 1 | | Christopher | 1 |
| | persons | | 0 | "Detective" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Underground" | | 4 | "Tomás" | | 5 | "Herrera" | | 6 | "Saint" | | 7 | "Christopher" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Camden" |
| | globalScore | 0.407 | | windowScore | 0.833 | |
| 7.14% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 35 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like a carved token of bone" | | 1 | "symbols that seemed to shift in the torchlight" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 592 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 45 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 19 | | mean | 31.16 | | std | 16.38 | | cv | 0.526 | | sampleLengths | | 0 | 59 | | 1 | 46 | | 2 | 9 | | 3 | 37 | | 4 | 47 | | 5 | 45 | | 6 | 32 | | 7 | 41 | | 8 | 36 | | 9 | 6 | | 10 | 34 | | 11 | 17 | | 12 | 4 | | 13 | 29 | | 14 | 44 | | 15 | 16 | | 16 | 46 | | 17 | 40 | | 18 | 4 |
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| 96.27% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 39 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 90 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 45 | | ratio | 0.111 | | matches | | 0 | "Her leather watch caught a flash of streetlight – nearly midnight." | | 1 | "The figure glanced back, and Quinn caught a glimpse of something that made her stomach lurch – the suspect's eyes reflected the dim light like a cat's." | | 2 | "The air changed – became heavy with incense and something else, something ancient." | | 3 | "She recognized him from her surveillance photos – Tomás Herrera, the disgraced paramedic she'd been investigating." | | 4 | "Her instincts screamed danger, but Morris's face flashed through her mind – his empty desk, his family still waiting for answers." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 505 | | adjectiveStacks | 1 | | stackExamples | | 0 | "illuminating graffiti-covered walls" |
| | adverbCount | 9 | | adverbRatio | 0.01782178217821782 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.009900990099009901 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 45 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 45 | | mean | 13.16 | | std | 6.2 | | cv | 0.472 | | sampleLengths | | 0 | 25 | | 1 | 13 | | 2 | 21 | | 3 | 8 | | 4 | 16 | | 5 | 11 | | 6 | 11 | | 7 | 9 | | 8 | 27 | | 9 | 10 | | 10 | 10 | | 11 | 14 | | 12 | 23 | | 13 | 5 | | 14 | 13 | | 15 | 16 | | 16 | 3 | | 17 | 8 | | 18 | 11 | | 19 | 14 | | 20 | 7 | | 21 | 7 | | 22 | 18 | | 23 | 16 | | 24 | 13 | | 25 | 13 | | 26 | 10 | | 27 | 6 | | 28 | 2 | | 29 | 16 | | 30 | 16 | | 31 | 11 | | 32 | 6 | | 33 | 4 | | 34 | 13 | | 35 | 16 | | 36 | 9 | | 37 | 14 | | 38 | 21 | | 39 | 16 | | 40 | 22 | | 41 | 24 | | 42 | 16 | | 43 | 24 | | 44 | 4 |
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| 64.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.4 | | totalSentences | 45 | | uniqueOpeners | 18 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 38 | | matches | (empty) | | ratio | 0 | |
| 83.16% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 38 | | matches | | 0 | "Her quarry darted between late-night" | | 1 | "Her leather watch caught a" | | 2 | "Her voice cut through the" | | 3 | "They burst out of the" | | 4 | "Her jaw clenched." | | 5 | "She'd lost him once by" | | 6 | "Her footsteps echoed in the" | | 7 | "She followed, emerging into a" | | 8 | "She recognized him from her" | | 9 | "He fingered the Saint Christopher" | | 10 | "His warm brown eyes held" | | 11 | "Her instincts screamed danger, but" | | 12 | "She took the token." |
| | ratio | 0.342 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 37 | | totalSentences | 38 | | matches | | 0 | "Rain pelted Detective Quinn's face" | | 1 | "Her quarry darted between late-night" | | 2 | "Quinn's legs burned, but eighteen" | | 3 | "The suspect veered sharply into" | | 4 | "Quinn followed, her hand brushing" | | 5 | "Her leather watch caught a" | | 6 | "The timing nagged at her" | | 7 | "Her voice cut through the" | | 8 | "The figure glanced back, and" | | 9 | "The same unnatural gleam she'd" | | 10 | "They burst out of the" | | 11 | "The suspect vaulted over a" | | 12 | "Quinn skidded to a halt" | | 13 | "Everything about this felt wrong." | | 14 | "The station had been abandoned" | | 15 | "Her jaw clenched." | | 16 | "She'd lost him once by" | | 17 | "Quinn drew her torch and" | | 18 | "The beam cut through darkness" | | 19 | "Her footsteps echoed in the" |
| | ratio | 0.974 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 38 | | matches | (empty) | | ratio | 0 | |
| 32.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 4 | | matches | | 0 | "Rain pelted Detective Quinn's face as she sprinted after the hooded figure, her boots splashing through puddles that reflected the neon glow of Soho's nightlife…" | | 1 | "The figure glanced back, and Quinn caught a glimpse of something that made her stomach lurch – the suspect's eyes reflected the dim light like a cat's." | | 2 | "She followed, emerging into a service tunnel that shouldn't exist according to any official Underground maps." | | 3 | "Music drifted up from below, a discordant melody that made her skin prickle." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |