| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 27 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva said quietly [quietly]" |
| | dialogueSentences | 84 | | tagDensity | 0.321 | | leniency | 0.643 | | rawRatio | 0.037 | | effectiveRatio | 0.024 | |
| 93.49% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1537 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 57.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1537 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "familiar" | | 1 | "chill" | | 2 | "footsteps" | | 3 | "measured" | | 4 | "flicked" | | 5 | "weight" | | 6 | "silence" | | 7 | "flickered" | | 8 | "shattered" |
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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 | 187 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 187 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 244 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 16 | | markdownWords | 23 | | totalWords | 1517 | | ratio | 0.015 | | matches | | 0 | "Had to go. Won’t be far." | | 1 | "him" | | 2 | "have" | | 3 | "chose" | | 4 | "botched" | | 5 | "burned" | | 6 | "order" | | 7 | "is" | | 8 | "me" | | 9 | "him" | | 10 | "you" | | 11 | "anyone" | | 12 | "On the team." | | 13 | "saw" | | 14 | "working" | | 15 | "him" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 35 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 76 | | wordCount | 1043 | | uniqueNames | 14 | | maxNameDensity | 2.68 | | worstName | "Eva" | | maxWindowNameDensity | 7 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Dean | 1 | | Street | 1 | | Coltrane | 1 | | Silas | 14 | | European | 1 | | Latin | 1 | | Soho | 1 | | Cardiff | 1 | | Aurora | 3 | | Rory | 21 | | Eva | 28 | | Channel | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Aurora" | | 4 | "Rory" | | 5 | "Eva" |
| | places | | 0 | "Dean" | | 1 | "Street" | | 2 | "Latin" | | 3 | "Soho" | | 4 | "Cardiff" | | 5 | "Channel" |
| | globalScore | 0.158 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | 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 | 1517 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 244 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 132 | | mean | 11.49 | | std | 11.12 | | cv | 0.967 | | sampleLengths | | 0 | 16 | | 1 | 45 | | 2 | 48 | | 3 | 4 | | 4 | 31 | | 5 | 22 | | 6 | 36 | | 7 | 6 | | 8 | 23 | | 9 | 3 | | 10 | 37 | | 11 | 6 | | 12 | 39 | | 13 | 4 | | 14 | 52 | | 15 | 3 | | 16 | 7 | | 17 | 31 | | 18 | 4 | | 19 | 18 | | 20 | 5 | | 21 | 1 | | 22 | 19 | | 23 | 2 | | 24 | 42 | | 25 | 5 | | 26 | 12 | | 27 | 9 | | 28 | 5 | | 29 | 6 | | 30 | 16 | | 31 | 5 | | 32 | 5 | | 33 | 21 | | 34 | 2 | | 35 | 8 | | 36 | 10 | | 37 | 9 | | 38 | 3 | | 39 | 4 | | 40 | 12 | | 41 | 4 | | 42 | 6 | | 43 | 18 | | 44 | 8 | | 45 | 9 | | 46 | 9 | | 47 | 20 | | 48 | 4 | | 49 | 29 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 187 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 198 | | matches | (empty) | |
| 2.34% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 18 | | semicolonCount | 0 | | flaggedSentences | 12 | | totalSentences | 244 | | ratio | 0.049 | | matches | | 0 | "A record played low—jazz, Coltrane, something from the sixties that felt heavier than music." | | 1 | "Aurora’s thumb brushed the scar on her wrist—crescent white against dark skin." | | 2 | "The old European rail routes—the ones with red pins marking surveillance drop points—were gone." | | 3 | "But the photographs—black-and-white shots of Soho streets in the fifties—now included one of her mother, young, laughing beside a jukebox." | | 4 | "But edged with something careful—like a hand hovering over a flame." | | 5 | "Her eyes—hazel, like Silas’s, but sharper—flicked from Aurora to the glass in her hand, then to Silas." | | 6 | "The slope of her shoulders had changed—no longer slumped under the weight of shared secrets, but squared, braced." | | 7 | "Rory laughed—short, sharp." | | 8 | "Inside—a tiny photo." | | 9 | "Something in her chest split open—slow, inevitable." | | 10 | "Outside, a siren wailed—distant, closing." | | 11 | "And then the glass shattered—in her hand—without warning." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1061 | | adjectiveStacks | 1 | | stackExamples | | 0 | "white against dark skin." |
| | adverbCount | 31 | | adverbRatio | 0.029217719132893498 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.003770028275212064 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 244 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 244 | | mean | 6.22 | | std | 5.23 | | cv | 0.841 | | sampleLengths | | 0 | 16 | | 1 | 27 | | 2 | 18 | | 3 | 4 | | 4 | 23 | | 5 | 7 | | 6 | 14 | | 7 | 4 | | 8 | 23 | | 9 | 8 | | 10 | 7 | | 11 | 2 | | 12 | 8 | | 13 | 5 | | 14 | 7 | | 15 | 6 | | 16 | 4 | | 17 | 14 | | 18 | 5 | | 19 | 6 | | 20 | 10 | | 21 | 10 | | 22 | 3 | | 23 | 3 | | 24 | 13 | | 25 | 2 | | 26 | 6 | | 27 | 12 | | 28 | 2 | | 29 | 2 | | 30 | 6 | | 31 | 10 | | 32 | 14 | | 33 | 15 | | 34 | 4 | | 35 | 5 | | 36 | 5 | | 37 | 16 | | 38 | 20 | | 39 | 6 | | 40 | 3 | | 41 | 7 | | 42 | 22 | | 43 | 4 | | 44 | 3 | | 45 | 2 | | 46 | 4 | | 47 | 2 | | 48 | 2 | | 49 | 1 |
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| 52.32% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.3483606557377049 | | totalSentences | 244 | | uniqueOpeners | 85 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 135 | | matches | | 0 | "Just left a note on" | | 1 | "Too soft for this life." | | 2 | "Then slowly, carefully, slipped the" | | 3 | "Then reached into her inner" | | 4 | "Then she dropped it into" |
| | ratio | 0.037 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 135 | | matches | | 0 | "She dropped the delivery bag" | | 1 | "He polished a glass with" | | 2 | "She ran a hand through" | | 3 | "She wrapped her fingers around" | | 4 | "It burned clean, not bitter." | | 5 | "She’d been far." | | 6 | "She turned on the stool." | | 7 | "She stared at her mother’s" | | 8 | "She didn’t need to turn." | | 9 | "Her eyes—hazel, like Silas’s, but" | | 10 | "Her fingers brushed the locket." | | 11 | "She thought of all the" | | 12 | "Her hand moved to her" | | 13 | "She reached for it." | | 14 | "Her eyes met Eva’s." | | 15 | "She set it beside the" | | 16 | "she said, voice low" | | 17 | "His eyes locked on the" |
| | ratio | 0.133 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 92 | | totalSentences | 135 | | matches | | 0 | "The door of The Raven’s" | | 1 | "Aurora’s boots hit the worn" | | 2 | "She dropped the delivery bag" | | 3 | "Silas didn’t look up." | | 4 | "He polished a glass with" | | 5 | "The hum of the ice" | | 6 | "A record played low—jazz, Coltrane," | | 7 | "She ran a hand through" | | 8 | "Silas slid a tumbler across" | | 9 | "She wrapped her fingers around" | | 10 | "The chill bit into her" | | 11 | "Whisky, peat-heavy, nothing like the" | | 12 | "It burned clean, not bitter." | | 13 | "The last time she’d walked" | | 14 | "She’d been far." | | 15 | "A man in a trench" | | 16 | "Eyes didn’t move across the" | | 17 | "Aurora’s thumb brushed the scar" | | 18 | "Silas followed her gaze to" | | 19 | "The old European rail routes—the" |
| | ratio | 0.681 | |
| 74.07% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 135 | | matches | | 0 | "Now it was an antique" | | 1 | "Before law school." |
| | ratio | 0.015 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 87.96% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 27 | | uselessAdditionCount | 2 | | matches | | 0 | "Silas said, dry" | | 1 | "she said, voice low" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 21 | | fancyCount | 1 | | fancyTags | | 0 | "Rory repeated (repeat)" |
| | dialogueSentences | 84 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.048 | | effectiveRatio | 0.024 | |