| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.04% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2523 | | totalAiIsmAdverbs | 2 | | 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) | |
| 72.26% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2523 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "weight" | | 1 | "navigated" | | 2 | "measured" | | 3 | "reminder" | | 4 | "navigate" | | 5 | "intensity" | | 6 | "aligned" | | 7 | "scanned" | | 8 | "solitary" | | 9 | "traced" |
| |
| 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 | 182 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 182 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 182 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2523 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 2523 | | uniqueNames | 14 | | maxNameDensity | 0.75 | | worstName | "Lucien" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Lucien" | | discoveredNames | | Aurora | 8 | | London | 4 | | Silas | 1 | | Evan | 1 | | Avaros | 1 | | Pre-Law | 1 | | Eva | 1 | | Brick | 1 | | Lane | 1 | | Golden | 1 | | Empress | 1 | | East | 1 | | Cardiff | 1 | | Lucien | 19 |
| | persons | | 0 | "Aurora" | | 1 | "Silas" | | 2 | "Evan" | | 3 | "Eva" | | 4 | "Lucien" |
| | places | | 0 | "London" | | 1 | "Avaros" | | 2 | "Brick" | | 3 | "Lane" | | 4 | "East" | | 5 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 180 | | 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 | 2523 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 182 | | matches | (empty) | |
| 45.27% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 90 | | mean | 28.03 | | std | 8.65 | | cv | 0.308 | | sampleLengths | | 0 | 75 | | 1 | 42 | | 2 | 7 | | 3 | 15 | | 4 | 14 | | 5 | 46 | | 6 | 57 | | 7 | 38 | | 8 | 8 | | 9 | 33 | | 10 | 25 | | 11 | 33 | | 12 | 28 | | 13 | 36 | | 14 | 26 | | 15 | 39 | | 16 | 31 | | 17 | 32 | | 18 | 33 | | 19 | 31 | | 20 | 24 | | 21 | 23 | | 22 | 32 | | 23 | 21 | | 24 | 30 | | 25 | 26 | | 26 | 30 | | 27 | 29 | | 28 | 24 | | 29 | 28 | | 30 | 30 | | 31 | 39 | | 32 | 23 | | 33 | 34 | | 34 | 32 | | 35 | 27 | | 36 | 25 | | 37 | 30 | | 38 | 19 | | 39 | 20 | | 40 | 29 | | 41 | 20 | | 42 | 24 | | 43 | 21 | | 44 | 27 | | 45 | 38 | | 46 | 14 | | 47 | 30 | | 48 | 30 | | 49 | 22 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 182 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 385 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 182 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2529 | | adjectiveStacks | 1 | | stackExamples | | 0 | "tabby settled near his" |
| | adverbCount | 34 | | adverbRatio | 0.013444049031237644 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.005140371688414393 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 182 | | echoCount | 0 | | echoWords | (empty) | |
| 67.46% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 182 | | mean | 13.86 | | std | 4.42 | | cv | 0.319 | | sampleLengths | | 0 | 17 | | 1 | 20 | | 2 | 15 | | 3 | 23 | | 4 | 22 | | 5 | 20 | | 6 | 7 | | 7 | 7 | | 8 | 8 | | 9 | 6 | | 10 | 8 | | 11 | 23 | | 12 | 23 | | 13 | 18 | | 14 | 15 | | 15 | 24 | | 16 | 19 | | 17 | 19 | | 18 | 8 | | 19 | 10 | | 20 | 10 | | 21 | 13 | | 22 | 18 | | 23 | 7 | | 24 | 23 | | 25 | 10 | | 26 | 14 | | 27 | 14 | | 28 | 7 | | 29 | 19 | | 30 | 10 | | 31 | 10 | | 32 | 16 | | 33 | 11 | | 34 | 14 | | 35 | 14 | | 36 | 6 | | 37 | 25 | | 38 | 19 | | 39 | 13 | | 40 | 8 | | 41 | 25 | | 42 | 15 | | 43 | 16 | | 44 | 10 | | 45 | 14 | | 46 | 5 | | 47 | 18 | | 48 | 18 | | 49 | 14 |
| |
| 36.81% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 24 | | diversityRatio | 0.2032967032967033 | | totalSentences | 182 | | uniqueOpeners | 37 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 182 | | matches | (empty) | | ratio | 0 | |
| 94.73% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 57 | | totalSentences | 182 | | matches | | 0 | "She swung the door open" | | 1 | "His charcoal suit fitted without" | | 2 | "Her shoulder-length black hair framed" | | 3 | "You arrive without invitation at" | | 4 | "She released the knob and" | | 5 | "His presence narrowed the available" | | 6 | "She cleared a narrow section" | | 7 | "He propped the cane against" | | 8 | "His left hand brushed a" | | 9 | "She picked up a bound" | | 10 | "Her eyes lifted every few" | | 11 | "My current location changes nothing" | | 12 | "Your escape from the previous" | | 13 | "Her fingers closed the book" | | 14 | "She turned to face the" | | 15 | "She placed the kettle on" | | 16 | "His black eye stayed fixed" | | 17 | "She withdrew two mugs and" | | 18 | "My history with Evan created" | | 19 | "She reached for a tin" |
| | ratio | 0.313 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 171 | | totalSentences | 182 | | matches | | 0 | "The deadbolts clicked in their" | | 1 | "She swung the door open" | | 2 | "Lucien stood positioned on the" | | 3 | "His charcoal suit fitted without" | | 4 | "Her shoulder-length black hair framed" | | 5 | "The small crescent scar on" | | 6 | "You arrive without invitation at" | | 7 | "Lucien shifted his weight forward" | | 8 | "The sole of his polished" | | 9 | "Invitation would have altered the" | | 10 | "She released the knob and" | | 11 | "The aroma of spiced dishes" | | 12 | "Lucien entered behind her and" | | 13 | "His presence narrowed the available" | | 14 | "Ptolemy the tabby cat emerged" | | 15 | "Aurora navigated a path through" | | 16 | "She cleared a narrow section" | | 17 | "The visit explains itself or" | | 18 | "He propped the cane against" | | 19 | "The motion revealed the slight" |
| | ratio | 0.94 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 182 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 157 | | technicalSentenceCount | 3 | | matches | | 0 | "The purpose ignored the attraction that made the separation difficult to accept." | | 1 | "Their positions forced a turn that brought her face near to his during the motion." | | 2 | "Her fingers traced the outline of East London streets that matched her usual paths for the restaurant drops." |
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| 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 | |