| 2.82% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 29 | | adverbTagCount | 7 | | adverbTags | | 0 | "Rory pushed away [away]" | | 1 | "Eva stepped fully [fully]" | | 2 | "Eva said quietly [quietly]" | | 3 | "Rory gestured around [around]" | | 4 | "she said finally [finally]" | | 5 | "she said quickly [quickly]" | | 6 | "he said mildly [mildly]" |
| | dialogueSentences | 71 | | tagDensity | 0.408 | | leniency | 0.817 | | rawRatio | 0.241 | | effectiveRatio | 0.197 | |
| 76.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1944 | | totalAiIsmAdverbs | 9 | | found | | 0 | | | 1 | | | 2 | | adverb | "deliberately" | | count | 1 |
| | 3 | | | 4 | | | 5 | | | 6 | |
| | highlights | | 0 | "very" | | 1 | "suddenly" | | 2 | "deliberately" | | 3 | "really" | | 4 | "softly" | | 5 | "slightly" | | 6 | "quickly" |
| |
| 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) | |
| 87.14% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1944 | | totalAiIsms | 5 | | found | | 0 | | | 1 | | | 2 | | | 3 | | word | "practiced ease" | | count | 1 |
|
| | highlights | | 0 | "silence" | | 1 | "flickered" | | 2 | "unspoken" | | 3 | "practiced ease" |
| |
| 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 | 1 | | narrationSentences | 123 | | matches | | |
| 96.40% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 123 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "happened to" | | 2 | "began to" |
| |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 165 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1932 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 31 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 104 | | wordCount | 1414 | | uniqueNames | 15 | | maxNameDensity | 2.48 | | worstName | "Rory" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | Chapter | 1 | | One | 1 | | Raven | 5 | | Nest | 5 | | Silas | 13 | | Female | 1 | | Castellano | 1 | | Eva | 33 | | Rory | 35 | | Welsh | 1 | | Soho | 1 | | London | 2 | | Cardiff | 1 | | Yu-Fei | 1 | | Had | 3 |
| | persons | | 0 | "One" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Silas" | | 4 | "Castellano" | | 5 | "Eva" | | 6 | "Rory" | | 7 | "Had" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Cardiff" | | 3 | "Yu-Fei" |
| | globalScore | 0.262 | | windowScore | 0.167 | |
| 60.71% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 84 | | glossingSentenceCount | 3 | | matches | | 0 | "quite suppress" | | 1 | "looked like someone who spent her time in" | | 2 | "as though seeing her for the first time since entering the bar—really seeing her, past the initial shock of recognition into whatever it was she'd become" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1932 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 165 | | matches | | 0 | "knew that voice" | | 1 | "pretend that years" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 85 | | mean | 22.73 | | std | 19.38 | | cv | 0.853 | | sampleLengths | | 0 | 6 | | 1 | 21 | | 2 | 71 | | 3 | 64 | | 4 | 21 | | 5 | 33 | | 6 | 2 | | 7 | 14 | | 8 | 41 | | 9 | 47 | | 10 | 25 | | 11 | 3 | | 12 | 55 | | 13 | 2 | | 14 | 21 | | 15 | 104 | | 16 | 1 | | 17 | 21 | | 18 | 28 | | 19 | 33 | | 20 | 13 | | 21 | 21 | | 22 | 44 | | 23 | 2 | | 24 | 46 | | 25 | 27 | | 26 | 10 | | 27 | 11 | | 28 | 35 | | 29 | 3 | | 30 | 23 | | 31 | 10 | | 32 | 30 | | 33 | 13 | | 34 | 26 | | 35 | 58 | | 36 | 7 | | 37 | 3 | | 38 | 7 | | 39 | 3 | | 40 | 17 | | 41 | 29 | | 42 | 9 | | 43 | 18 | | 44 | 40 | | 45 | 3 | | 46 | 33 | | 47 | 13 | | 48 | 2 | | 49 | 40 |
| |
| 93.85% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 123 | | matches | | 0 | "been formed" | | 1 | "been replaced" | | 2 | "being asked" | | 3 | "was meant" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 262 | | matches | | |
| 73.59% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 165 | | ratio | 0.024 | | matches | | 0 | "Silas glanced toward the entrance, and something flickered across his weathered face—a micro-expression of recognition that his trained composure couldn't quite suppress." | | 1 | "Eva looked at her as though seeing her for the first time since entering the bar—really seeing her, past the initial shock of recognition into whatever it was she'd become." | | 2 | "A man stepped inside—expensive suit, purposeful gait, the kind of confidence that suggested money and family name and futures already written before birth." | | 3 | "She wrote her number in neat, angular script—so different from the looping, careless handwriting Rory remembered—and slid it across the bar." |
| |
| 86.10% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1238 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 68 | | adverbRatio | 0.05492730210016155 | | lyAdverbCount | 26 | | lyAdverbRatio | 0.0210016155088853 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 165 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 165 | | mean | 11.71 | | std | 7.89 | | cv | 0.674 | | sampleLengths | | 0 | 27 | | 1 | 28 | | 2 | 26 | | 3 | 14 | | 4 | 3 | | 5 | 23 | | 6 | 41 | | 7 | 21 | | 8 | 11 | | 9 | 22 | | 10 | 2 | | 11 | 14 | | 12 | 24 | | 13 | 8 | | 14 | 9 | | 15 | 4 | | 16 | 21 | | 17 | 22 | | 18 | 7 | | 19 | 1 | | 20 | 17 | | 21 | 3 | | 22 | 4 | | 23 | 5 | | 24 | 29 | | 25 | 17 | | 26 | 2 | | 27 | 21 | | 28 | 31 | | 29 | 15 | | 30 | 25 | | 31 | 14 | | 32 | 19 | | 33 | 1 | | 34 | 5 | | 35 | 16 | | 36 | 23 | | 37 | 5 | | 38 | 17 | | 39 | 16 | | 40 | 10 | | 41 | 3 | | 42 | 7 | | 43 | 7 | | 44 | 7 | | 45 | 29 | | 46 | 15 | | 47 | 2 | | 48 | 34 | | 49 | 12 |
| |
| 52.73% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.36363636363636365 | | totalSentences | 165 | | uniqueOpeners | 60 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 105 | | matches | | 0 | "Of course her mother had" | | 1 | "Of course she'd made it" | | 2 | "Instead, it sounded fresh." | | 3 | "Sometimes anger was easier than" | | 4 | "Instead, she found herself looking" | | 5 | "Instead, she followed the expensive" |
| | ratio | 0.057 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 105 | | matches | | 0 | "She'd made this walk a" | | 1 | "She nudged the door wider" | | 2 | "She didn't look up immediately," | | 3 | "She knew that voice." | | 4 | "Her hair was cut into" | | 5 | "She looked like someone who" | | 6 | "It stung regardless." | | 7 | "She hadn't meant to answer" | | 8 | "She'd expected distance to have" | | 9 | "It wasn't a kind thing" | | 10 | "It was accusatory in ways" | | 11 | "He was good at that." | | 12 | "She found instead that the" | | 13 | "She thought of her flat" | | 14 | "She thought of the routes" | | 15 | "She thought of Silas, who'd" | | 16 | "she said finally" | | 17 | "She wanted to ask where" | | 18 | "He spotted Eva immediately, his" | | 19 | "she said quickly" |
| | ratio | 0.238 | |
| 45.71% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 87 | | totalSentences | 105 | | matches | | 0 | "# Chapter One: The Raven's" | | 1 | "Rory stepped into The Raven's" | | 2 | "She'd made this walk a" | | 3 | "Something about inventory." | | 4 | "She nudged the door wider" | | 5 | "The lunch crowd had cleared" | | 6 | "Silas emerged from behind the" | | 7 | "Rory announced, beginning to unpack" | | 8 | "The bar's old maps watched" | | 9 | "Rory had memorised most of" | | 10 | "Silas collected them the way" | | 11 | "The front door opened." | | 12 | "She didn't look up immediately," | | 13 | "Silas glanced toward the entrance," | | 14 | "a voice said" | | 15 | "Rory's hands stilled." | | 16 | "She knew that voice." | | 17 | "The sort of promise people" | | 18 | "Eva Castellano stood in the" | | 19 | "The girl Rory had known" |
| | ratio | 0.829 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 105 | | matches | | 0 | "As though no time had" | | 1 | "Before Rory could respond, the" | | 2 | "Before Rory could answer, her" |
| | ratio | 0.029 | |
| 42.61% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 8 | | matches | | 0 | "Rory stepped into The Raven's Nest carrying three delivery boxes stacked higher than her head, the smell of hot ginger and sesame oil preceding her like an anno…" | | 1 | "The lunch crowd had cleared out, leaving behind the usual ghosts of the place: half-empty pint glasses, the faint residue of cigarette smoke that no amount of a…" | | 2 | "Eva Castellano stood in the doorway of The Raven's Nest, and she was not the Eva that existed in Rory's memory." | | 3 | "Her hair was cut into something fashionable and precise, the kind of style that required regular maintenance from someone who knew what they were doing." | | 4 | "She looked like someone who spent her time in conference rooms and restaurants with wine lists that required translation." | | 5 | "Eva's expression cycled through several stages: confusion, then recognition, then something that looked almost like guilt." | | 6 | "Eva looked at her as though seeing her for the first time since entering the bar—really seeing her, past the initial shock of recognition into whatever it was s…" | | 7 | "His hazel eyes held no judgment, only the kind of understanding that came from a lifetime of watching people collide with their own histories." |
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| 90.52% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 29 | | uselessAdditionCount | 2 | | matches | | 0 | "Rory announced, beginning to unpack the boxes" | | 1 | "Eva said, her voice softer now" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 21 | | fancyCount | 2 | | fancyTags | | 0 | "Rory announced (announce)" | | 1 | "Eva agreed (agree)" |
| | dialogueSentences | 71 | | tagDensity | 0.296 | | leniency | 0.592 | | rawRatio | 0.095 | | effectiveRatio | 0.056 | |