| 3.92% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 5 | | adverbTags | | 0 | "he said quietly [quietly]" | | 1 | "She looked around [around]" | | 2 | "he said finally [finally]" | | 3 | "Rory said softly [softly]" | | 4 | "he said quietly [quietly]" |
| | dialogueSentences | 51 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.294 | | effectiveRatio | 0.196 | |
| 81.06% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1056 | | totalAiIsmAdverbs | 4 | | 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) | |
| 43.18% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1056 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "familiar" | | 1 | "comforting" | | 2 | "coded" | | 3 | "tracing" | | 4 | "unreadable" | | 5 | "scanning" | | 6 | "eyebrow" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 47 | | matches | | |
| 82.07% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 47 | | filterMatches | (empty) | | hedgeMatches | | |
| 94.93% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 81 | | gibberishSentences | 1 | | adjustedGibberishSentences | 1 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0.012 | | matches | | 0 | "The familiar burn felt comforting, aзо ideal thread connecting who she was with who she had become." |
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| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1054 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 32.94% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 598 | | uniqueNames | 8 | | maxNameDensity | 2.34 | | worstName | "Rory" | | maxWindowNameDensity | 4 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 2 | | Nest | 2 | | London | 3 | | Carter | 1 | | Rory | 14 | | Blackwood | 1 | | Silas | 9 | | Silvia | 2 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Rory" | | 4 | "Blackwood" | | 5 | "Silas" | | 6 | "Silvia" |
| | places | | | globalScore | 0.329 | | windowScore | 0.333 | |
| 87.50% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | glossingSentenceCount | 1 | | matches | | 0 | "as if looking for something" |
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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 | 1054 | | matches | (empty) | |
| 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 | 46 | | mean | 22.91 | | std | 15.5 | | cv | 0.676 | | sampleLengths | | 0 | 68 | | 1 | 63 | | 2 | 25 | | 3 | 21 | | 4 | 29 | | 5 | 19 | | 6 | 41 | | 7 | 7 | | 8 | 24 | | 9 | 50 | | 10 | 44 | | 11 | 24 | | 12 | 32 | | 13 | 9 | | 14 | 10 | | 15 | 6 | | 16 | 18 | | 17 | 11 | | 18 | 19 | | 19 | 6 | | 20 | 47 | | 21 | 19 | | 22 | 15 | | 23 | 5 | | 24 | 7 | | 25 | 18 | | 26 | 47 | | 27 | 4 | | 28 | 10 | | 29 | 26 | | 30 | 18 | | 31 | 5 | | 32 | 9 | | 33 | 29 | | 34 | 13 | | 35 | 26 | | 36 | 17 | | 37 | 10 | | 38 | 25 | | 39 | 17 | | 40 | 31 | | 41 | 19 | | 42 | 26 | | 43 | 18 | | 44 | 53 | | 45 | 14 |
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| 97.80% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 47 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 107 | | matches | (empty) | |
| 72.31% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 81 | | ratio | 0.025 | | matches | | 0 | "Inside, the bar smelled of stale beer, older wine, and something indefinably bitter—sweet memories woven into the very air." | | 1 | "\"Old friends can visit. You're about the only one who did. The others\"—he picked up a cloth and began wiping down the already spotless counter—\"the others seem to have misplaced the address.\"" |
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| 82.61% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 547 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 29 | | adverbRatio | 0.05301645338208409 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.012797074954296161 | |
| 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 | 13.01 | | std | 7.49 | | cv | 0.576 | | sampleLengths | | 0 | 24 | | 1 | 24 | | 2 | 20 | | 3 | 19 | | 4 | 20 | | 5 | 24 | | 6 | 25 | | 7 | 11 | | 8 | 10 | | 9 | 19 | | 10 | 10 | | 11 | 11 | | 12 | 8 | | 13 | 23 | | 14 | 10 | | 15 | 8 | | 16 | 7 | | 17 | 24 | | 18 | 21 | | 19 | 25 | | 20 | 4 | | 21 | 9 | | 22 | 24 | | 23 | 11 | | 24 | 6 | | 25 | 18 | | 26 | 32 | | 27 | 9 | | 28 | 10 | | 29 | 6 | | 30 | 4 | | 31 | 14 | | 32 | 4 | | 33 | 7 | | 34 | 9 | | 35 | 10 | | 36 | 6 | | 37 | 16 | | 38 | 18 | | 39 | 13 | | 40 | 7 | | 41 | 12 | | 42 | 8 | | 43 | 7 | | 44 | 5 | | 45 | 7 | | 46 | 6 | | 47 | 12 | | 48 | 28 | | 49 | 19 |
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| 74.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4691358024691358 | | totalSentences | 81 | | uniqueOpeners | 38 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 47 | | matches | (empty) | | ratio | 0 | |
| 83.83% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 47 | | matches | | 0 | "She pushed through the heavy" | | 1 | "He chuckled, the sound deep" | | 2 | "she replied, sliding onto a" | | 3 | "His beard, meticulously trimmed, caught" | | 4 | "She lifted her gaze to" | | 5 | "He paused, his eyes scanning" | | 6 | "he picked up a cloth" | | 7 | "he asked, his eyes meeting" | | 8 | "he said quietly" | | 9 | "She looked around the bar," | | 10 | "he said finally" | | 11 | "he said quietly" | | 12 | "she replied, lifting it to" | | 13 | "he called after as she" | | 14 | "She pushed through the heavy" | | 15 | "he whispered to the empty" |
| | ratio | 0.34 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 47 | | matches | | 0 | "The neon glow of the" | | 1 | "Rory Carter pulled her lightweight" | | 2 | "She pushed through the heavy" | | 3 | "The dim lighting and the" | | 4 | "The walls, as always, were" | | 5 | "Silas Blackwood's voice came from" | | 6 | "Rory expelled a breath that" | | 7 | "He chuckled, the sound deep" | | 8 | "she replied, sliding onto a" | | 9 | "Silas nodded thoughtfully, running a" | | 10 | "His beard, meticulously trimmed, caught" | | 11 | "Rory nodded, tracing the pattern" | | 12 | "She lifted her gaze to" | | 13 | "Silas studied her for a" | | 14 | "He paused, his eyes scanning" | | 15 | "Rory's lips quirked into a" | | 16 | "he picked up a cloth" | | 17 | "he asked, his eyes meeting" | | 18 | "Silas barked a laugh." | | 19 | "Rory shook her head." |
| | ratio | 0.936 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 47 | | matches | | 0 | "Before she could protest further," |
| | ratio | 0.021 | |
| 6.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 4 | | matches | | 0 | "The neon glow of the green Raven's Nest sign washed over the damp London pavement, casting long shadows that danced with the evening crowd." | | 1 | "The walls, as always, were adorned with old maps and black and white photographs that told stories Rory had long since committed to memory." | | 2 | "Silas nodded thoughtfully, running a hand through his hair with the grey streaks that hadn't been there the last time she'd seen him." | | 3 | "A group of young professionals entered, laughing loudly, their voices cutting through the low hum of the bar." |
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| 66.18% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 2 | | matches | | 0 | "He paused, his eyes scanning the room as if looking for something" | | 1 | "Silas asked, his expression softening with surprise" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 2 | | fancyTags | | 0 | "she could (could)" | | 1 | "he whispered (whisper)" |
| | dialogueSentences | 51 | | tagDensity | 0.235 | | leniency | 0.471 | | rawRatio | 0.167 | | effectiveRatio | 0.078 | |