| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 2 | | adverbTags | | 0 | "She swallowed hard [hard]" | | 1 | "she said finally [finally]" |
| | dialogueSentences | 43 | | tagDensity | 0.465 | | leniency | 0.93 | | rawRatio | 0.1 | | effectiveRatio | 0.093 | |
| 91.09% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1684 | | totalAiIsmAdverbs | 3 | | 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) | |
| 37.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1684 | | totalAiIsms | 21 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | word | "practiced ease" | | count | 1 |
| | 14 | | | 15 | |
| | highlights | | 0 | "tracing" | | 1 | "familiar" | | 2 | "crystal" | | 3 | "scanned" | | 4 | "fractured" | | 5 | "etched" | | 6 | "weight" | | 7 | "lilt" | | 8 | "pulse" | | 9 | "reminder" | | 10 | "traced" | | 11 | "unspoken" | | 12 | "silence" | | 13 | "practiced ease" | | 14 | "porcelain" | | 15 | "echo" |
| |
| 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 | 112 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 112 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 134 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 51 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1682 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 1102 | | uniqueNames | 7 | | maxNameDensity | 0.91 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 3 | | Soho | 2 | | Cardiff | 3 | | Silas | 10 | | Silence | 1 | | Comfort | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Silence" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like someone who had learned to ca" |
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| 21.64% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 1.784 | | wordCount | 1682 | | matches | | 0 | "Not the heavy thud of a regular, but the quick, hesitant chime of someone stepping out of the sto" | | 1 | "not the bar, not the rain, but the echo of a young woman’s laughter from a Cardiff pub, bri" | | 2 | "not the rain, but the echo of a young woman’s laughter from a Cardiff pub, bri" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 134 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 54.26 | | std | 29.16 | | cv | 0.537 | | sampleLengths | | 0 | 131 | | 1 | 25 | | 2 | 71 | | 3 | 23 | | 4 | 110 | | 5 | 29 | | 6 | 42 | | 7 | 42 | | 8 | 53 | | 9 | 30 | | 10 | 40 | | 11 | 48 | | 12 | 29 | | 13 | 53 | | 14 | 37 | | 15 | 61 | | 16 | 69 | | 17 | 34 | | 18 | 24 | | 19 | 78 | | 20 | 97 | | 21 | 120 | | 22 | 53 | | 23 | 20 | | 24 | 69 | | 25 | 49 | | 26 | 19 | | 27 | 24 | | 28 | 59 | | 29 | 76 | | 30 | 67 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 112 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 198 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 134 | | ratio | 0 | | matches | (empty) | |
| 91.13% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1109 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 48 | | adverbRatio | 0.04328223624887286 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.009918845807033363 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 134 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 134 | | mean | 12.55 | | std | 9.99 | | cv | 0.796 | | sampleLengths | | 0 | 20 | | 1 | 20 | | 2 | 17 | | 3 | 7 | | 4 | 17 | | 5 | 50 | | 6 | 6 | | 7 | 19 | | 8 | 4 | | 9 | 13 | | 10 | 14 | | 11 | 19 | | 12 | 11 | | 13 | 1 | | 14 | 1 | | 15 | 6 | | 16 | 2 | | 17 | 3 | | 18 | 20 | | 19 | 5 | | 20 | 10 | | 21 | 7 | | 22 | 14 | | 23 | 9 | | 24 | 10 | | 25 | 7 | | 26 | 3 | | 27 | 2 | | 28 | 8 | | 29 | 5 | | 30 | 17 | | 31 | 13 | | 32 | 3 | | 33 | 20 | | 34 | 1 | | 35 | 1 | | 36 | 1 | | 37 | 3 | | 38 | 22 | | 39 | 20 | | 40 | 17 | | 41 | 13 | | 42 | 12 | | 43 | 11 | | 44 | 7 | | 45 | 9 | | 46 | 13 | | 47 | 13 | | 48 | 7 | | 49 | 16 |
| |
| 66.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.43283582089552236 | | totalSentences | 134 | | uniqueOpeners | 58 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 100 | | matches | | 0 | "Bright blue eyes scanned the" | | 1 | "Always three steps ahead, even" | | 2 | "Then it reset, smoother this" | | 3 | "Just an invitation." | | 4 | "Just a thread offered across" | | 5 | "Then she stepped out into" | | 6 | "Somewhere behind the bookshelf, a" |
| | ratio | 0.07 | |
| 40.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 100 | | matches | | 0 | "He rested his forearms on" | | 1 | "He tapped his silver signet" | | 2 | "Her hair fell straight and" | | 3 | "She pushed it back with" | | 4 | "Her head snapped toward him." | | 5 | "She stepped fully into the" | | 6 | "She didn’t look twenty-five anymore." | | 7 | "She looked like someone who" | | 8 | "Her voice was lower than" | | 9 | "He reached for a clean" | | 10 | "She ordered a single malt," | | 11 | "He didn’t ask how she’d" | | 12 | "She took the glass but" | | 13 | "Her eyes dropped to his" | | 14 | "He shifted his weight, favoring" | | 15 | "She traced the rim of" | | 16 | "She finally took a sip" | | 17 | "His tone softened, losing the" | | 18 | "She looked down at her" | | 19 | "He remembered the young woman" |
| | ratio | 0.45 | |
| 45.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 83 | | totalSentences | 100 | | matches | | 0 | "The green neon sign buzzed" | | 1 | "Silas watched the rain bead" | | 2 | "He rested his forearms on" | | 3 | "Prague still remembered how to" | | 4 | "He tapped his silver signet" | | 5 | "The bell above the door" | | 6 | "Silas lifted his gaze." | | 7 | "A woman stood just inside" | | 8 | "Her hair fell straight and" | | 9 | "She pushed it back with" | | 10 | "The name left his mouth" | | 11 | "Her head snapped toward him." | | 12 | "She stepped fully into the" | | 13 | "The movement exposed the inside" | | 14 | "A small crescent-shaped scar caught" | | 15 | "Silas knew exactly where that" | | 16 | "Childhood kitchen tile." | | 17 | "A laugh later, explained away" | | 18 | "She didn’t look twenty-five anymore." | | 19 | "The lines around her eyes" |
| | ratio | 0.83 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 100 | | matches | (empty) | | ratio | 0 | |
| 86.47% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 3 | | matches | | 0 | "She pushed it back with a swift, irritated motion, revealing a face that hit him like a physical blow." | | 1 | "He remembered the young woman who used to sit in the corner booth of a different bar in Cardiff, sketching arguments on napkins, convinced she could dissect any…" | | 2 | "She saw the man who had once walked through firewalls and dead drops, who had once looked at her as if she were a promising mind worth nurturing rather than a b…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "She ordered (order)" | | 1 | "She laughed (laugh)" |
| | dialogueSentences | 43 | | tagDensity | 0.116 | | leniency | 0.233 | | rawRatio | 0.4 | | effectiveRatio | 0.093 | |