| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 1 | | adverbTags | | 0 | "She looked like [like]" |
| | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |
| 89.28% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1399 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "really" | | 2 | "softly" |
| |
| 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) | |
| 35.67% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1399 | | totalAiIsms | 18 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | word | "carried the weight" | | count | 1 |
| | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | |
| | highlights | | 0 | "traced" | | 1 | "reminder" | | 2 | "scanned" | | 3 | "stomach" | | 4 | "carried the weight" | | 5 | "navigating" | | 6 | "measured" | | 7 | "flicked" | | 8 | "comfortable" | | 9 | "potential" | | 10 | "dancing" | | 11 | "sanctuary" | | 12 | "predictable" | | 13 | "silence" | | 14 | "rhythmic" | | 15 | "weight" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "the air was thick with" | | 1 | "hung in the air" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 146 | | matches | (empty) | |
| 84.15% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 5 | | hedgeCount | 1 | | narrationSentences | 146 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 146 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1399 | | ratio | 0 | | matches | (empty) | |
| 20.83% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 5 | | matches | | 0 | "Rory, he said." | | 1 | "Rhys, she replied." | | 2 | "You look well, he said." | | 3 | "Here is quiet, Rory said." | | 4 | "We all have, Rory said." |
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| 81.80% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 75 | | wordCount | 1393 | | uniqueNames | 24 | | maxNameDensity | 1.36 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Soho | 2 | | Carter | 2 | | London | 6 | | Underground | 1 | | Golden | 1 | | Empress | 1 | | Rory | 19 | | Rhys | 12 | | Pre-Law | 1 | | Cardiff | 2 | | University | 1 | | Brendan | 2 | | Jennifer | 2 | | Evan | 4 | | Christmas | 1 | | Irish | 1 | | Welsh | 1 | | Raven | 1 | | Nest | 1 | | Blackwood | 1 | | Si | 1 | | Eva | 1 | | Silas | 5 | | You | 6 |
| | persons | | 0 | "Carter" | | 1 | "Rory" | | 2 | "Rhys" | | 3 | "Brendan" | | 4 | "Jennifer" | | 5 | "Evan" | | 6 | "Raven" | | 7 | "Blackwood" | | 8 | "Eva" | | 9 | "Silas" | | 10 | "You" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Golden" | | 3 | "Cardiff" | | 4 | "University" | | 5 | "Christmas" | | 6 | "Welsh" |
| | globalScore | 0.818 | | windowScore | 0.833 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 5 | | matches | | 0 | "felt like it belonged to someone else e" | | 1 | "felt like an admission that she needed" | | 2 | "looked like someone who spent her nights" | | 3 | "looked like they had seen more than just" | | 4 | "looked like a man returning to a world of" |
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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 | 1399 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 146 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 34.12 | | std | 32.39 | | cv | 0.949 | | sampleLengths | | 0 | 118 | | 1 | 93 | | 2 | 92 | | 3 | 43 | | 4 | 15 | | 5 | 32 | | 6 | 39 | | 7 | 52 | | 8 | 14 | | 9 | 18 | | 10 | 2 | | 11 | 20 | | 12 | 41 | | 13 | 40 | | 14 | 5 | | 15 | 26 | | 16 | 47 | | 17 | 5 | | 18 | 87 | | 19 | 45 | | 20 | 25 | | 21 | 9 | | 22 | 35 | | 23 | 22 | | 24 | 5 | | 25 | 6 | | 26 | 6 | | 27 | 31 | | 28 | 31 | | 29 | 1 | | 30 | 97 | | 31 | 5 | | 32 | 2 | | 33 | 2 | | 34 | 36 | | 35 | 67 | | 36 | 5 | | 37 | 21 | | 38 | 37 | | 39 | 3 | | 40 | 119 |
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| 95.65% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 146 | | matches | | 0 | "was stowed" | | 1 | "was tucked" | | 2 | "was destined" | | 3 | "being asked" |
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| 43.14% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 255 | | matches | | 0 | "was waiting" | | 1 | "was wearing" | | 2 | "was still studying" | | 3 | "were looking" | | 4 | "was wiping" | | 5 | "was waiting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 146 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 483 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.035196687370600416 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.016563146997929608 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 146 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 146 | | mean | 9.58 | | std | 7.48 | | cv | 0.78 | | sampleLengths | | 0 | 24 | | 1 | 23 | | 2 | 21 | | 3 | 21 | | 4 | 29 | | 5 | 5 | | 6 | 19 | | 7 | 13 | | 8 | 17 | | 9 | 19 | | 10 | 20 | | 11 | 20 | | 12 | 16 | | 13 | 19 | | 14 | 3 | | 15 | 26 | | 16 | 8 | | 17 | 4 | | 18 | 12 | | 19 | 17 | | 20 | 10 | | 21 | 3 | | 22 | 12 | | 23 | 3 | | 24 | 3 | | 25 | 25 | | 26 | 1 | | 27 | 7 | | 28 | 3 | | 29 | 21 | | 30 | 5 | | 31 | 3 | | 32 | 5 | | 33 | 4 | | 34 | 17 | | 35 | 26 | | 36 | 14 | | 37 | 2 | | 38 | 2 | | 39 | 9 | | 40 | 5 | | 41 | 2 | | 42 | 1 | | 43 | 1 | | 44 | 7 | | 45 | 5 | | 46 | 4 | | 47 | 2 | | 48 | 9 | | 49 | 10 |
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| 37.21% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 24 | | diversityRatio | 0.3219178082191781 | | totalSentences | 146 | | uniqueOpeners | 47 | |
| 52.49% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 127 | | matches | | 0 | "Then he nodded, once." | | 1 | "Then she thought about Evan's" |
| | ratio | 0.016 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 71 | | totalSentences | 127 | | matches | | 0 | "She traced the crescent-shaped scar" | | 1 | "She was off the clock." | | 2 | "Her straight, shoulder-length black hair" | | 3 | "Her eyes, bright blue and" | | 4 | "She was waiting for no" | | 5 | "He wore a suit that" | | 6 | "It was Rhys." | | 7 | "They had studied Pre-Law together" | | 8 | "They hadn't seen each other" | | 9 | "He walked over, his shoes" | | 10 | "He looked exactly as he" | | 11 | "His voice was warm, but" | | 12 | "She didn't stand." | | 13 | "He slid into the booth" | | 14 | "You look well, he said." | | 15 | "It was a polite lie." | | 16 | "They both knew it." | | 17 | "She looked like someone who" | | 18 | "He paused, swirling the condensation" | | 19 | "I heard you dropped out." |
| | ratio | 0.559 | |
| 42.68% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 106 | | totalSentences | 127 | | matches | | 0 | "The green neon sign above" | | 1 | "Aurora Carter sat in her" | | 2 | "She traced the crescent-shaped scar" | | 3 | "The skin there was pale," | | 4 | "She was off the clock." | | 5 | "The delivery bag from the" | | 6 | "Her straight, shoulder-length black hair" | | 7 | "Her eyes, bright blue and" | | 8 | "She was waiting for no" | | 9 | "The man who stepped out" | | 10 | "He wore a suit that" | | 11 | "It was Rhys." | | 12 | "They had studied Pre-Law together" | | 13 | "They hadn't seen each other" | | 14 | "Rhys spotted her instantly." | | 15 | "He walked over, his shoes" | | 16 | "He looked exactly as he" | | 17 | "Rory, he said." | | 18 | "His voice was warm, but" | | 19 | "Rhys, she replied." |
| | ratio | 0.835 | |
| 39.37% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 127 | | matches | | 0 | "Before Rhys could respond, a" |
| | ratio | 0.008 | |
| 56.65% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 7 | | matches | | 0 | "The skin there was pale, raised slightly against the rest of her hand, a permanent reminder of a childhood accident that felt like it belonged to someone else e…" | | 1 | "Silas Blackwood approached from the bar, moving with the deliberate, measured pace of a man who conserves energy." | | 2 | "He wore a crisp white shirt with the sleeves rolled up, revealing forearms that looked like they had seen more than just pouring drinks." | | 3 | "There was a slight limp in his left leg, the result of an old knee injury that never quite healed right, but he carried himself with a quiet authority that made…" | | 4 | "Photos of spies and soldiers, people who had lived lives of consequence and danger." | | 5 | "He reached across the table, his hand hovering over hers before pulling back." | | 6 | "Then she thought about Evan's hands, the shouting, the fear that had driven her to Eva's phone call, the desperate flight to London." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |