| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 86.76% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1133 | | totalAiIsmAdverbs | 3 | | 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) | |
| 24.98% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1133 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "electric" | | 1 | "traced" | | 2 | "reminder" | | 3 | "throbbed" | | 4 | "methodical" | | 5 | "comforting" | | 6 | "familiar" | | 7 | "warmth" | | 8 | "silence" | | 9 | "scanned" | | 10 | "tension" | | 11 | "weight" | | 12 | "flickered" | | 13 | "sanctuary" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | 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" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 111 | | matches | | |
| 91.38% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 0 | | narrationSentences | 111 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 111 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1133 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 5 | | matches | | 0 | "You look well, Eva said." | | 1 | "I thought about calling, Aurora said, the words feeling rough in her throat." | | 2 | "I know, Eva replied." | | 3 | "I changed, Aurora said softly." | | 4 | "I made it, Aurora said." |
| |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 63 | | wordCount | 1133 | | uniqueNames | 16 | | maxNameDensity | 1.85 | | worstName | "Aurora" | | maxWindowNameDensity | 4 | | worstWindowName | "Aurora" | | discoveredNames | | Soho | 1 | | Carter | 1 | | Raven | 1 | | Nest | 2 | | Golden | 1 | | Empress | 1 | | Blackwood | 1 | | Aurora | 21 | | Cardiff | 3 | | London | 4 | | Eva | 15 | | Evan | 2 | | Silas | 5 | | Rory | 1 | | Premier | 1 | | You | 3 |
| | persons | | 0 | "Carter" | | 1 | "Raven" | | 2 | "Empress" | | 3 | "Blackwood" | | 4 | "Aurora" | | 5 | "Eva" | | 6 | "Evan" | | 7 | "Silas" | | 8 | "Rory" | | 9 | "You" |
| | places | | 0 | "Soho" | | 1 | "Golden" | | 2 | "Cardiff" | | 3 | "London" | | 4 | "Premier" |
| | globalScore | 0.573 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like I was abandoning you" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1133 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 111 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 35.41 | | std | 27.8 | | cv | 0.785 | | sampleLengths | | 0 | 88 | | 1 | 64 | | 2 | 80 | | 3 | 120 | | 4 | 28 | | 5 | 21 | | 6 | 61 | | 7 | 53 | | 8 | 45 | | 9 | 21 | | 10 | 17 | | 11 | 20 | | 12 | 2 | | 13 | 52 | | 14 | 17 | | 15 | 18 | | 16 | 22 | | 17 | 15 | | 18 | 64 | | 19 | 12 | | 20 | 28 | | 21 | 4 | | 22 | 26 | | 23 | 38 | | 24 | 9 | | 25 | 24 | | 26 | 2 | | 27 | 29 | | 28 | 14 | | 29 | 11 | | 30 | 57 | | 31 | 71 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 111 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 208 | | matches | | 0 | "was abandoning" | | 1 | "was wiping" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 111 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1139 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 30 | | adverbRatio | 0.02633889376646181 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.00877963125548727 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 111 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 111 | | mean | 10.21 | | std | 7.68 | | cv | 0.753 | | sampleLengths | | 0 | 24 | | 1 | 19 | | 2 | 26 | | 3 | 19 | | 4 | 8 | | 5 | 19 | | 6 | 25 | | 7 | 12 | | 8 | 12 | | 9 | 20 | | 10 | 21 | | 11 | 27 | | 12 | 14 | | 13 | 13 | | 14 | 8 | | 15 | 17 | | 16 | 4 | | 17 | 13 | | 18 | 24 | | 19 | 27 | | 20 | 12 | | 21 | 10 | | 22 | 6 | | 23 | 20 | | 24 | 1 | | 25 | 9 | | 26 | 15 | | 27 | 22 | | 28 | 15 | | 29 | 4 | | 30 | 14 | | 31 | 15 | | 32 | 11 | | 33 | 9 | | 34 | 9 | | 35 | 9 | | 36 | 27 | | 37 | 5 | | 38 | 16 | | 39 | 10 | | 40 | 2 | | 41 | 5 | | 42 | 8 | | 43 | 6 | | 44 | 6 | | 45 | 2 | | 46 | 20 | | 47 | 32 | | 48 | 13 | | 49 | 4 |
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| 36.64% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.3063063063063063 | | totalSentences | 111 | | uniqueOpeners | 34 | |
| 68.03% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 98 | | matches | | 0 | "Too much time." | | 1 | "Too much water under the" |
| | ratio | 0.02 | |
| 28.16% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 47 | | totalSentences | 98 | | matches | | 0 | "She shook the rain from" | | 1 | "She had not planned to" | | 2 | "Her shift at the Golden" | | 3 | "She needed the noise of" | | 4 | "She traced the small crescent-shaped" | | 5 | "It was a reminder of" | | 6 | "She found a stool near" | | 7 | "He looked up, his hazel" | | 8 | "He gave a slight nod," | | 9 | "He did not speak." | | 10 | "He knew better than to" | | 11 | "He simply poured a glass" | | 12 | "He moved with a slight" | | 13 | "She stared into the liquid," | | 14 | "They had not seen each" | | 15 | "She should have turned around" | | 16 | "She beckoned with a slight" | | 17 | "She slid into the booth" | | 18 | "You look well, Eva said." | | 19 | "Her voice was the same," |
| | ratio | 0.48 | |
| 46.73% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 81 | | totalSentences | 98 | | matches | | 0 | "The green neon sign above" | | 1 | "Aurora Carter pushed open the" | | 2 | "She shook the rain from" | | 3 | "She had not planned to" | | 4 | "Her shift at the Golden" | | 5 | "She needed the noise of" | | 6 | "Aurora moved toward the bar," | | 7 | "The walls were covered with" | | 8 | "She traced the small crescent-shaped" | | 9 | "It was a reminder of" | | 10 | "She found a stool near" | | 11 | "Silas Blackwood was behind the" | | 12 | "He looked up, his hazel" | | 13 | "He gave a slight nod," | | 14 | "He did not speak." | | 15 | "He knew better than to" | | 16 | "He simply poured a glass" | | 17 | "He moved with a slight" | | 18 | "Aurora wrapped her hands around" | | 19 | "She stared into the liquid," |
| | ratio | 0.827 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 98 | | matches | | 0 | "Because it felt like I" | | 1 | "To who we were." | | 2 | "But, Eva added, her voice" |
| | ratio | 0.031 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 3 | | matches | | 0 | "Inside, the air was thick with the scent of old wood, polished brass, and the faint, lingering smoke of cigars that hadn't been lit in years." | | 1 | "Eva looked older, the lines around her mouth deeper than Aurora remembered, her hair styled in a way that spoke of a stability Aurora had never achieved." | | 2 | "Eva reached across the table, her hand hovering over Aurora's before pulling back." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |