| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 53 | | tagDensity | 0.302 | | leniency | 0.604 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1538 | | 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) | |
| 54.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1538 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "crystal" | | 1 | "rhythmic" | | 2 | "weight" | | 3 | "scanning" | | 4 | "silk" | | 5 | "tracing" | | 6 | "roaring" | | 7 | "silence" | | 8 | "flicked" | | 9 | "flickered" | | 10 | "chaotic" | | 11 | "shattered" |
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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 | 90 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 90 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 126 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1538 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 60.88% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 1066 | | uniqueNames | 12 | | maxNameDensity | 1.78 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 19 | | Silas | 15 | | Monday | 1 | | Soho | 1 | | Nest | 2 | | Cillian | 14 | | Jameson | 1 | | Evan | 1 | | Christmas | 1 | | Cardiff | 1 | | Welsh | 1 | | Raven | 1 |
| | persons | | 0 | "Rory" | | 1 | "Silas" | | 2 | "Nest" | | 3 | "Cillian" | | 4 | "Jameson" | | 5 | "Evan" |
| | places | | 0 | "Soho" | | 1 | "Cardiff" | | 2 | "Raven" |
| | globalScore | 0.609 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | 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 | 1538 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 126 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 63 | | mean | 24.41 | | std | 16.77 | | cv | 0.687 | | sampleLengths | | 0 | 57 | | 1 | 6 | | 2 | 12 | | 3 | 54 | | 4 | 8 | | 5 | 69 | | 6 | 16 | | 7 | 11 | | 8 | 26 | | 9 | 32 | | 10 | 57 | | 11 | 19 | | 12 | 19 | | 13 | 25 | | 14 | 9 | | 15 | 6 | | 16 | 36 | | 17 | 4 | | 18 | 14 | | 19 | 25 | | 20 | 15 | | 21 | 3 | | 22 | 53 | | 23 | 40 | | 24 | 34 | | 25 | 24 | | 26 | 38 | | 27 | 14 | | 28 | 46 | | 29 | 42 | | 30 | 5 | | 31 | 16 | | 32 | 26 | | 33 | 11 | | 34 | 18 | | 35 | 41 | | 36 | 8 | | 37 | 3 | | 38 | 5 | | 39 | 49 | | 40 | 9 | | 41 | 6 | | 42 | 27 | | 43 | 11 | | 44 | 30 | | 45 | 32 | | 46 | 8 | | 47 | 21 | | 48 | 47 | | 49 | 20 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 90 | | matches | | |
| 44.96% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 172 | | matches | | 0 | "was measuring" | | 1 | "was staring" | | 2 | "weren't looking" | | 3 | "was looking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 126 | | ratio | 0.008 | | matches | | 0 | "He wasn't the bar owner anymore; he was the operative." |
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| 70.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1075 | | adjectiveStacks | 5 | | stackExamples | | 0 | "heavy expensive black silk" | | 1 | "small crescent-shaped scar" | | 2 | "ugly large old distorted grey Welsh" | | 3 | "small black electronic device." | | 4 | "old circular blue plastic lighter" |
| | adverbCount | 22 | | adverbRatio | 0.020465116279069766 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.008372093023255815 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 126 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 126 | | mean | 12.21 | | std | 7.85 | | cv | 0.643 | | sampleLengths | | 0 | 19 | | 1 | 9 | | 2 | 3 | | 3 | 14 | | 4 | 12 | | 5 | 6 | | 6 | 12 | | 7 | 22 | | 8 | 21 | | 9 | 11 | | 10 | 8 | | 11 | 20 | | 12 | 11 | | 13 | 7 | | 14 | 31 | | 15 | 2 | | 16 | 14 | | 17 | 11 | | 18 | 6 | | 19 | 19 | | 20 | 1 | | 21 | 7 | | 22 | 24 | | 23 | 1 | | 24 | 5 | | 25 | 24 | | 26 | 28 | | 27 | 19 | | 28 | 19 | | 29 | 20 | | 30 | 5 | | 31 | 9 | | 32 | 6 | | 33 | 8 | | 34 | 28 | | 35 | 4 | | 36 | 14 | | 37 | 8 | | 38 | 17 | | 39 | 15 | | 40 | 3 | | 41 | 38 | | 42 | 6 | | 43 | 9 | | 44 | 5 | | 45 | 22 | | 46 | 13 | | 47 | 29 | | 48 | 5 | | 49 | 24 |
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| 43.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3253968253968254 | | totalSentences | 126 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 88 | | matches | (empty) | | ratio | 0 | |
| 74.55% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 88 | | matches | | 0 | "She didn't flinch." | | 1 | "She simply tucked the thumb" | | 2 | "He adjusted the silver signet" | | 3 | "He didn't look like a" | | 4 | "He wore a sharp charcoal" | | 5 | "He squinted through the dim" | | 6 | "She looked for an exit," | | 7 | "He didn't have the slight" | | 8 | "He reached the brass rail" | | 9 | "He tapped the polished wood" | | 10 | "He didn't say a word," | | 11 | "She pushed the glass toward" | | 12 | "He looked around the room," | | 13 | "He glanced at Silas" | | 14 | "He knew about Evan." | | 15 | "He had seen the bruises" | | 16 | "He knocked the whiskey back" | | 17 | "She looked at Silas, seeking" | | 18 | "His posture had shifted." | | 19 | "He wasn't the bar owner" |
| | ratio | 0.364 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 83 | | totalSentences | 88 | | matches | | 0 | "The rag caught on a" | | 1 | "Blood bloomed, a bright bead" | | 2 | "She didn't flinch." | | 3 | "She simply tucked the thumb" | | 4 | "Silas leaned his weight against" | | 5 | "He adjusted the silver signet" | | 6 | "The bell above the entrance" | | 7 | "A man stepped inside, shaking" | | 8 | "He didn't look like a" | | 9 | "He wore a sharp charcoal" | | 10 | "The rag fell from her" | | 11 | "Silas called out, his voice" | | 12 | "The man didn't look at" | | 13 | "He squinted through the dim" | | 14 | "Rory felt the air leave" | | 15 | "She looked for an exit," | | 16 | "Cillian moved toward the bar." | | 17 | "He didn't have the slight" | | 18 | "He reached the brass rail" | | 19 | "He tapped the polished wood" |
| | ratio | 0.943 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 88 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 2 | | matches | | 0 | "He wore a sharp charcoal suit that cost more than Rory’s annual rent and carried the unmistakable aura of someone who never had to check his bank balance before…" | | 1 | "He didn't have the slight limp of Silas, but he walked with a new, practiced confidence that made him seem taller than she remembered." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 7 | | matches | | 0 | "Silas leaned, his hazel eyes scanning the sparse Monday night crowd" | | 1 | "Silas called out, his voice smooth and professional" | | 2 | "Rory grabbed, her hand steady despite the roaring in her ears" | | 3 | "Silas said, his voice a low growl" | | 4 | "Rory said, her voice dropping to a sharp hiss" | | 5 | "Cillian screamed, his voice cracking" | | 6 | "Rory pulled, her eyes glowing with a terrifying clarity" |
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| 55.66% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 5 | | fancyTags | | 0 | "Silas called out (call out)" | | 1 | "Rory whispered (whisper)" | | 2 | "Silas shouted (shout)" | | 3 | "Cillian screamed (scream)" | | 4 | "Cillian whimpered (whimper)" |
| | dialogueSentences | 53 | | tagDensity | 0.189 | | leniency | 0.377 | | rawRatio | 0.5 | | effectiveRatio | 0.189 | |