| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.571 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1244 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 35.69% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1244 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "lilt" | | 1 | "tracing" | | 2 | "familiar" | | 3 | "traced" | | 4 | "weight" | | 5 | "scanning" | | 6 | "perfect" | | 7 | "facade" | | 8 | "database" | | 9 | "silence" | | 10 | "flickered" | | 11 | "rhythmic" | | 12 | "reminder" | | 13 | "pulse" |
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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 | 62 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 62 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 74 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1242 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 851 | | uniqueNames | 8 | | maxNameDensity | 2.23 | | worstName | "Rory" | | maxWindowNameDensity | 4 | | worstWindowName | "Eva" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Rory | 19 | | Cardiff | 2 | | Ford | 1 | | Eva | 17 | | Silas | 4 |
| | persons | | | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "Cardiff" |
| | globalScore | 0.384 | | windowScore | 0.333 | |
| 55.66% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 2 | | matches | | 0 | "something like glass—transparent, but lethal" | | 1 | "felt like a canyon" |
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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 | 1242 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 74 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 40.06 | | std | 20.8 | | cv | 0.519 | | sampleLengths | | 0 | 81 | | 1 | 57 | | 2 | 32 | | 3 | 52 | | 4 | 81 | | 5 | 46 | | 6 | 51 | | 7 | 44 | | 8 | 40 | | 9 | 35 | | 10 | 23 | | 11 | 13 | | 12 | 65 | | 13 | 66 | | 14 | 36 | | 15 | 56 | | 16 | 55 | | 17 | 25 | | 18 | 63 | | 19 | 41 | | 20 | 17 | | 21 | 10 | | 22 | 21 | | 23 | 8 | | 24 | 39 | | 25 | 18 | | 26 | 74 | | 27 | 13 | | 28 | 24 | | 29 | 23 | | 30 | 33 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 62 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 141 | | matches | (empty) | |
| 65.64% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 74 | | ratio | 0.027 | | matches | | 0 | "The face was the same, but the softness had hardened into something like glass—transparent, but lethal to the touch." | | 1 | "He didn’t look up from his ledger, but his right hand, adorned with the silver signet ring, tapped once against the wood—a warning, or perhaps a salute." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 859 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.02211874272409779 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0034924330616996507 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 74 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 74 | | mean | 16.78 | | std | 8.48 | | cv | 0.505 | | sampleLengths | | 0 | 19 | | 1 | 13 | | 2 | 24 | | 3 | 25 | | 4 | 11 | | 5 | 10 | | 6 | 17 | | 7 | 19 | | 8 | 3 | | 9 | 18 | | 10 | 11 | | 11 | 18 | | 12 | 17 | | 13 | 17 | | 14 | 4 | | 15 | 23 | | 16 | 35 | | 17 | 19 | | 18 | 11 | | 19 | 15 | | 20 | 20 | | 21 | 13 | | 22 | 14 | | 23 | 24 | | 24 | 17 | | 25 | 27 | | 26 | 19 | | 27 | 21 | | 28 | 5 | | 29 | 9 | | 30 | 21 | | 31 | 23 | | 32 | 3 | | 33 | 10 | | 34 | 15 | | 35 | 50 | | 36 | 21 | | 37 | 20 | | 38 | 25 | | 39 | 21 | | 40 | 15 | | 41 | 26 | | 42 | 30 | | 43 | 10 | | 44 | 17 | | 45 | 28 | | 46 | 12 | | 47 | 13 | | 48 | 20 | | 49 | 43 |
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| 42.34% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3108108108108108 | | totalSentences | 74 | | uniqueOpeners | 23 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 58 | | matches | (empty) | | ratio | 0 | |
| 88.97% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 58 | | matches | | 0 | "She focused on the rhythm" | | 1 | "She shed a trench coat," | | 2 | "Her fingers toyed with a" | | 3 | "She stepped toward the bar," | | 4 | "She leaned against the wood," | | 5 | "She tucked the wet cloth" | | 6 | "She grabbed a clean glass" | | 7 | "He didn’t look up from" | | 8 | "She signaled for a wine," | | 9 | "She watched Rory work, her" | | 10 | "She stepped around the counter," | | 11 | "She gestured to the wall" | | 12 | "She stood inches from the" | | 13 | "She reached out, stopping just" | | 14 | "She pulled a crisp bill" | | 15 | "She didn't offer a hand" | | 16 | "She turned, her coat billowing" | | 17 | "He stopped next to her," | | 18 | "She turned back to the" |
| | ratio | 0.328 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 58 | | matches | | 0 | "The green neon hum of" | | 1 | "Rory wiped the mahogany counter," | | 2 | "She focused on the rhythm" | | 3 | "The front door groaned, admitting" | | 4 | "A woman stepped inside, her" | | 5 | "She shed a trench coat," | | 6 | "The woman paused, her gaze" | | 7 | "Eva stopped dead." | | 8 | "Her fingers toyed with a" | | 9 | "She stepped toward the bar," | | 10 | "Eva murmured, her voice stripped" | | 11 | "She leaned against the wood," | | 12 | "Rory’s hand froze mid-circle." | | 13 | "She tucked the wet cloth" | | 14 | "The bright blue of her" | | 15 | "The face was the same," | | 16 | "Rory said, her voice steady" | | 17 | "She grabbed a clean glass" | | 18 | "Eva traced the perimeter of" | | 19 | "The lack of gold on" |
| | ratio | 0.983 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 58 | | matches | (empty) | | ratio | 0 | |
| 67.67% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 4 | | matches | | 0 | "She focused on the rhythm of her cloth, a repetitive circular motion that acted as a barrier against the low-frequency drone of the evening crowd." | | 1 | "She tucked the wet cloth into her apron, tracing the small, familiar crescent scar on her wrist with her thumb before looking up." | | 2 | "The bright blue of her eyes caught the light from the overhead bulbs, searching the other woman's face for the girl who had smuggled her out of Cardiff in the t…" | | 3 | "She watched Rory work, her eyes tracking the way Rory shifted her weight, favoring her right side, always scanning the door." |
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| 31.25% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 3 | | matches | | 0 | "Rory said, her voice steady" | | 1 | "Eva said, her voice returning to that polished, impenetrable tone" | | 2 | "Silas asked, his voice a low rasp" |
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| 50.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 3 | | fancyTags | | 0 | "Eva murmured (murmur)" | | 1 | "Eva continued (continue)" | | 2 | "Eva conceded (concede)" |
| | dialogueSentences | 28 | | tagDensity | 0.536 | | leniency | 1 | | rawRatio | 0.2 | | effectiveRatio | 0.2 | |