| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 97.19% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1778 | | totalAiIsmAdverbs | 1 | | 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) | |
| 80.31% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1778 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "gloom" | | 1 | "scanned" | | 2 | "weight" | | 3 | "traced" | | 4 | "coded" | | 5 | "eyebrow" | | 6 | "flickered" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 121 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 121 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 183 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1778 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 89 | | wordCount | 983 | | uniqueNames | 10 | | maxNameDensity | 4.27 | | worstName | "Rory" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Rory" | | discoveredNames | | Berwick | 1 | | Street | 1 | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Rory | 42 | | Silas | 7 | | Coke | 2 | | Megan | 30 | | Rain | 3 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Silas" | | 4 | "Megan" | | 5 | "Rain" |
| | places | | 0 | "Berwick" | | 1 | "Street" | | 2 | "Soho" |
| | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 91 | | 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 | 1778 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 183 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 131 | | mean | 13.57 | | std | 10.14 | | cv | 0.747 | | sampleLengths | | 0 | 11 | | 1 | 39 | | 2 | 36 | | 3 | 46 | | 4 | 6 | | 5 | 46 | | 6 | 48 | | 7 | 2 | | 8 | 11 | | 9 | 2 | | 10 | 12 | | 11 | 1 | | 12 | 24 | | 13 | 11 | | 14 | 11 | | 15 | 2 | | 16 | 17 | | 17 | 6 | | 18 | 15 | | 19 | 7 | | 20 | 18 | | 21 | 5 | | 22 | 13 | | 23 | 11 | | 24 | 16 | | 25 | 15 | | 26 | 19 | | 27 | 8 | | 28 | 31 | | 29 | 4 | | 30 | 11 | | 31 | 8 | | 32 | 10 | | 33 | 23 | | 34 | 2 | | 35 | 3 | | 36 | 7 | | 37 | 8 | | 38 | 22 | | 39 | 34 | | 40 | 12 | | 41 | 5 | | 42 | 10 | | 43 | 19 | | 44 | 7 | | 45 | 3 | | 46 | 19 | | 47 | 3 | | 48 | 9 | | 49 | 3 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 121 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 168 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 183 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 991 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 11 | | adverbRatio | 0.011099899091826439 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0020181634712411706 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 183 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 183 | | mean | 9.72 | | std | 7.06 | | cv | 0.727 | | sampleLengths | | 0 | 11 | | 1 | 13 | | 2 | 7 | | 3 | 19 | | 4 | 8 | | 5 | 9 | | 6 | 8 | | 7 | 11 | | 8 | 7 | | 9 | 8 | | 10 | 6 | | 11 | 18 | | 12 | 7 | | 13 | 6 | | 14 | 8 | | 15 | 8 | | 16 | 21 | | 17 | 9 | | 18 | 21 | | 19 | 10 | | 20 | 8 | | 21 | 9 | | 22 | 2 | | 23 | 11 | | 24 | 2 | | 25 | 6 | | 26 | 6 | | 27 | 1 | | 28 | 11 | | 29 | 13 | | 30 | 11 | | 31 | 11 | | 32 | 2 | | 33 | 7 | | 34 | 10 | | 35 | 6 | | 36 | 7 | | 37 | 8 | | 38 | 7 | | 39 | 8 | | 40 | 10 | | 41 | 5 | | 42 | 4 | | 43 | 9 | | 44 | 11 | | 45 | 16 | | 46 | 15 | | 47 | 4 | | 48 | 15 | | 49 | 8 |
| |
| 46.72% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.23497267759562843 | | totalSentences | 183 | | uniqueOpeners | 43 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 116 | | matches | (empty) | | ratio | 0 | |
| 95.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 116 | | matches | | 0 | "It buzzed and spat against" | | 1 | "His grey-streaked auburn hair caught" | | 2 | "His beard held the same" | | 3 | "His right hand, with its" | | 4 | "His hazel eyes lifted to" | | 5 | "He gave Rory a single" | | 6 | "It stuck to her neck" | | 7 | "She shrugged out of her" | | 8 | "Her bright blue eyes scanned" | | 9 | "She wore a charcoal suit" | | 10 | "Her blonde hair sat in" | | 11 | "She stared at Rory with" | | 12 | "Her grip tightened on the" | | 13 | "She righted it with her" | | 14 | "Her perfume cut through the" | | 15 | "Her eyes stopped on the" | | 16 | "He set down the polished" | | 17 | "His left leg dragged a" | | 18 | "Her nails were short and" | | 19 | "Her suit jacket creased at" |
| | ratio | 0.31 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 112 | | totalSentences | 116 | | matches | | 0 | "The green neon above The" | | 1 | "It buzzed and spat against" | | 2 | "Rory ducked under it with" | | 3 | "The air smelled of malt" | | 4 | "Silas stood behind the long" | | 5 | "His grey-streaked auburn hair caught" | | 6 | "His beard held the same" | | 7 | "His right hand, with its" | | 8 | "His hazel eyes lifted to" | | 9 | "He gave Rory a single" | | 10 | "Rory shook rain from her" | | 11 | "It stuck to her neck" | | 12 | "She shrugged out of her" | | 13 | "Her bright blue eyes scanned" | | 14 | "A woman sat at the" | | 15 | "She wore a charcoal suit" | | 16 | "Her blonde hair sat in" | | 17 | "She stared at Rory with" | | 18 | "Rory froze with one hand" | | 19 | "Rory squinted through the low" |
| | ratio | 0.966 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 116 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |