| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 31 | | tagDensity | 0.419 | | leniency | 0.839 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.64% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1214 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "suddenly" | | 1 | "softly" | | 2 | "really" |
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| 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) | |
| 54.70% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1214 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "familiar" | | 1 | "weight" | | 2 | "echoing" | | 3 | "silence" | | 4 | "traced" | | 5 | "glinting" | | 6 | "tension" | | 7 | "unspoken" | | 8 | "furrowed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "weight of words/silence" | | count | 1 |
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| | highlights | | 0 | "the weight of unspoken words" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 51 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 51 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 69 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 55 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1196 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 707 | | uniqueNames | 13 | | maxNameDensity | 0.85 | | worstName | "Silas" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Golden | 1 | | Empress | 1 | | London | 2 | | Cardiff | 2 | | Cold | 1 | | War | 1 | | Europe | 1 | | Prague | 1 | | Welsh | 1 | | Silas | 6 | | Rory | 3 |
| | persons | | | places | | 0 | "Golden" | | 1 | "London" | | 2 | "Cardiff" | | 3 | "Europe" | | 4 | "Prague" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | 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 | 1196 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 69 | | matches | (empty) | |
| 57.01% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 23 | | mean | 52 | | std | 18.18 | | cv | 0.35 | | sampleLengths | | 0 | 53 | | 1 | 49 | | 2 | 71 | | 3 | 45 | | 4 | 58 | | 5 | 56 | | 6 | 28 | | 7 | 73 | | 8 | 87 | | 9 | 61 | | 10 | 73 | | 11 | 47 | | 12 | 71 | | 13 | 62 | | 14 | 64 | | 15 | 49 | | 16 | 54 | | 17 | 51 | | 18 | 27 | | 19 | 51 | | 20 | 8 | | 21 | 36 | | 22 | 22 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 51 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 115 | | matches | (empty) | |
| 60.04% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 69 | | ratio | 0.029 | | matches | | 0 | "That limp in his step as he moved to adjust a stool, the grey streaks threading through his auburn beard—they painted a picture she hadn't seen up close in years." | | 1 | "The knee injury, she remembered— the one that ended his field days." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 714 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.02661064425770308 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0070028011204481795 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 69 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 69 | | mean | 17.33 | | std | 9.74 | | cv | 0.562 | | sampleLengths | | 0 | 27 | | 1 | 26 | | 2 | 23 | | 3 | 15 | | 4 | 11 | | 5 | 13 | | 6 | 30 | | 7 | 28 | | 8 | 10 | | 9 | 15 | | 10 | 20 | | 11 | 16 | | 12 | 24 | | 13 | 18 | | 14 | 11 | | 15 | 22 | | 16 | 23 | | 17 | 10 | | 18 | 5 | | 19 | 13 | | 20 | 9 | | 21 | 14 | | 22 | 36 | | 23 | 14 | | 24 | 15 | | 25 | 12 | | 26 | 29 | | 27 | 31 | | 28 | 21 | | 29 | 21 | | 30 | 19 | | 31 | 18 | | 32 | 11 | | 33 | 35 | | 34 | 9 | | 35 | 9 | | 36 | 38 | | 37 | 8 | | 38 | 20 | | 39 | 43 | | 40 | 16 | | 41 | 9 | | 42 | 18 | | 43 | 19 | | 44 | 10 | | 45 | 54 | | 46 | 25 | | 47 | 24 | | 48 | 6 | | 49 | 23 |
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| 99.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.5942028985507246 | | totalSentences | 69 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 50 | | matches | (empty) | | ratio | 0 | |
| 4.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 50 | | matches | | 0 | "He polished a glass with" | | 1 | "She froze midway to the" | | 2 | "She set the boxes down" | | 3 | "He set the glass down" | | 4 | "She slid onto a stool," | | 5 | "Her bright blue eyes met" | | 6 | "She took a sip, the" | | 7 | "She gestured at the bar," | | 8 | "He leaned on the counter," | | 9 | "He nodded at the hidden" | | 10 | "She glanced at the small" | | 11 | "She straightened her straight shoulder-length" | | 12 | "He poured himself a measure" | | 13 | "She set her pint down," | | 14 | "His signet ring tapped the" | | 15 | "She followed his gaze to" | | 16 | "Her voice dropped, the bar's" | | 17 | "She leaned in, the scent" | | 18 | "He mentioned her mother's name" | | 19 | "She traced the edge of" |
| | ratio | 0.54 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 46 | | totalSentences | 50 | | matches | | 0 | "Rory shoved through the door" | | 1 | "The familiar tang of spilled" | | 2 | "Silas called from behind the" | | 3 | "He polished a glass with" | | 4 | "She froze midway to the" | | 5 | "That limp in his step" | | 6 | "The name slipped out before" | | 7 | "She set the boxes down" | | 8 | "He set the glass down" | | 9 | "The bar's dim glow from" | | 10 | "She slid onto a stool," | | 11 | "Her bright blue eyes met" | | 12 | "Silas poured her a pint" | | 13 | "Foam clung to the rim." | | 14 | "The name made her fingers" | | 15 | "She took a sip, the" | | 16 | "She gestured at the bar," | | 17 | "He leaned on the counter," | | 18 | "The knee injury, she remembered—" | | 19 | "He nodded at the hidden" |
| | ratio | 0.92 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 50 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 1 | | matches | | 0 | "Her bright blue eyes met his, searching for the man who'd once pulled her out of a bad spot without asking questions." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 4 | | matches | | 0 | "He poured, the amber liquid swirling in the glass" | | 1 | "Her voice dropped, the bar's murmur fading around them" | | 2 | "She traced, foam bubbling down" | | 3 | "He swept, bottles glinting in the low light" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "He mentioned (mention)" |
| | dialogueSentences | 31 | | tagDensity | 0.065 | | leniency | 0.129 | | rawRatio | 0.5 | | effectiveRatio | 0.065 | |