| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 49 | | adverbTagCount | 2 | | adverbTags | | 0 | "Miller stepped back [back]" | | 1 | "Miller turned away [away]" |
| | dialogueSentences | 127 | | tagDensity | 0.386 | | leniency | 0.772 | | rawRatio | 0.041 | | effectiveRatio | 0.031 | |
| 96.88% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1604 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 75.06% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1604 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "shimmered" | | 1 | "furrowed" | | 2 | "traced" | | 3 | "etched" | | 4 | "throbbed" | | 5 | "pulsed" | | 6 | "flickered" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 224 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 224 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 301 | | gibberishSentences | 1 | | adjustedGibberishSentences | 1 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 20 | | ratio | 0.003 | | matches | | 0 | "Miller leaned against the ticket booth, a当你 had a cigarette stuck in his mouth." |
| |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1604 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 119 | | wordCount | 1052 | | uniqueNames | 9 | | maxNameDensity | 5.51 | | worstName | "Quinn" | | maxWindowNameDensity | 8.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 58 | | Camden | 1 | | Miller | 53 | | Cold | 2 | | Skin | 1 | | Time | 1 | | Veil | 1 | | Compass | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Camden" | | 3 | "Miller" | | 4 | "Skin" | | 5 | "Time" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | 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 | 1604 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 301 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 123 | | mean | 13.04 | | std | 6.78 | | cv | 0.52 | | sampleLengths | | 0 | 59 | | 1 | 12 | | 2 | 18 | | 3 | 14 | | 4 | 9 | | 5 | 16 | | 6 | 7 | | 7 | 28 | | 8 | 9 | | 9 | 17 | | 10 | 17 | | 11 | 17 | | 12 | 13 | | 13 | 19 | | 14 | 14 | | 15 | 4 | | 16 | 8 | | 17 | 9 | | 18 | 23 | | 19 | 11 | | 20 | 9 | | 21 | 30 | | 22 | 11 | | 23 | 7 | | 24 | 16 | | 25 | 26 | | 26 | 17 | | 27 | 3 | | 28 | 8 | | 29 | 14 | | 30 | 13 | | 31 | 16 | | 32 | 12 | | 33 | 15 | | 34 | 21 | | 35 | 3 | | 36 | 19 | | 37 | 6 | | 38 | 19 | | 39 | 11 | | 40 | 21 | | 41 | 16 | | 42 | 15 | | 43 | 17 | | 44 | 6 | | 45 | 8 | | 46 | 8 | | 47 | 12 | | 48 | 6 | | 49 | 10 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 224 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 235 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 301 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1052 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.017110266159695818 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0028517110266159697 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 301 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 301 | | mean | 5.33 | | std | 2.92 | | cv | 0.548 | | sampleLengths | | 0 | 6 | | 1 | 4 | | 2 | 12 | | 3 | 8 | | 4 | 9 | | 5 | 20 | | 6 | 4 | | 7 | 8 | | 8 | 8 | | 9 | 6 | | 10 | 4 | | 11 | 14 | | 12 | 9 | | 13 | 6 | | 14 | 10 | | 15 | 7 | | 16 | 4 | | 17 | 11 | | 18 | 4 | | 19 | 4 | | 20 | 5 | | 21 | 9 | | 22 | 2 | | 23 | 12 | | 24 | 3 | | 25 | 11 | | 26 | 6 | | 27 | 5 | | 28 | 12 | | 29 | 3 | | 30 | 10 | | 31 | 9 | | 32 | 10 | | 33 | 2 | | 34 | 8 | | 35 | 4 | | 36 | 3 | | 37 | 1 | | 38 | 3 | | 39 | 3 | | 40 | 2 | | 41 | 5 | | 42 | 4 | | 43 | 8 | | 44 | 5 | | 45 | 6 | | 46 | 4 | | 47 | 6 | | 48 | 5 | | 49 | 6 |
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| 44.68% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.21262458471760798 | | totalSentences | 301 | | uniqueOpeners | 64 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 191 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 49 | | totalSentences | 191 | | matches | | 0 | "She stepped over a puddle" | | 1 | "Her boot made no sound" | | 2 | "She tightened the strap of" | | 3 | "It was recently condemned by" | | 4 | "She touched the fabric of" | | 5 | "She wiped a smudge of" | | 6 | "She looked at the door" | | 7 | "She traced the patterns etched" | | 8 | "Her jawline set." | | 9 | "It looked like brass." | | 10 | "She picked it up" | | 11 | "It lay perpendicular to the" | | 12 | "His hand jerked back." | | 13 | "She grabbed a glove." | | 14 | "It felt heavy." | | 15 | "She opened the satchel on" | | 16 | "She crossed her fingers." | | 17 | "It spun faster." | | 18 | "She looked at the wall" | | 19 | "She pinned the compass to" |
| | ratio | 0.257 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 181 | | totalSentences | 191 | | matches | | 0 | "The smell hit Harlow Quinn" | | 1 | "She stepped over a puddle" | | 2 | "Her boot made no sound" | | 3 | "She tightened the strap of" | | 4 | "The station felt wrong." | | 5 | "It was recently condemned by" | | 6 | "Quinn reached the corner near" | | 7 | "Bodies lay twisted in a" | | 8 | "Blood spatter looked dry." | | 9 | "Miller leaned against the ticket" | | 10 | "Miller asked, pointing at the" | | 11 | "The watch on her left" | | 12 | "Miller exhaled smoke" | | 13 | "Quinn ignored the response." | | 14 | "She touched the fabric of" | | 15 | "The weave felt translucent." | | 16 | "Fibre spun from shadow itself." | | 17 | "She wiped a smudge of" | | 18 | "The mark remained." | | 19 | "She looked at the door" |
| | ratio | 0.948 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 191 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 7 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 49 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn spoke, as if the dark prison would hear" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn spoke (speak)" | | 1 | "Quinn whispered (whisper)" |
| | dialogueSentences | 127 | | tagDensity | 0.047 | | leniency | 0.094 | | rawRatio | 0.333 | | effectiveRatio | 0.031 | |