| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.56% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1453 | | 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) | |
| 72.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1453 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "silence" | | 1 | "standard" | | 2 | "tension" | | 3 | "footsteps" | | 4 | "aligned" |
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| 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 | 153 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 153 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 153 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1451 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 65 | | wordCount | 1451 | | uniqueNames | 21 | | maxNameDensity | 0.76 | | worstName | "Lucien" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Lucien" | | discoveredNames | | Carter | 1 | | Moreau | 1 | | Eva | 2 | | Brick | 2 | | Lane | 2 | | Golden | 2 | | Empress | 2 | | Cardiff | 2 | | Evan | 2 | | French | 1 | | Marseille | 2 | | Avaros | 4 | | Lucien | 11 | | London | 2 | | Aurora | 7 | | One | 5 | | Delivery | 3 | | Ptolemy | 4 | | You | 3 | | Silence | 3 | | Attraction | 4 |
| | persons | | 0 | "Carter" | | 1 | "Moreau" | | 2 | "Eva" | | 3 | "Empress" | | 4 | "Evan" | | 5 | "Avaros" | | 6 | "Lucien" | | 7 | "Aurora" | | 8 | "Delivery" | | 9 | "Ptolemy" | | 10 | "You" | | 11 | "Silence" | | 12 | "Attraction" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Golden" | | 3 | "Cardiff" | | 4 | "Marseille" | | 5 | "London" | | 6 | "One" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 119 | | 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 | 1451 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 153 | | matches | | 0 | "crosses that difference" |
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| 68.88% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 34.55 | | std | 13.51 | | cv | 0.391 | | sampleLengths | | 0 | 85 | | 1 | 12 | | 2 | 10 | | 3 | 14 | | 4 | 25 | | 5 | 63 | | 6 | 11 | | 7 | 59 | | 8 | 27 | | 9 | 31 | | 10 | 46 | | 11 | 31 | | 12 | 39 | | 13 | 38 | | 14 | 39 | | 15 | 39 | | 16 | 47 | | 17 | 31 | | 18 | 45 | | 19 | 29 | | 20 | 45 | | 21 | 37 | | 22 | 35 | | 23 | 28 | | 24 | 37 | | 25 | 25 | | 26 | 38 | | 27 | 19 | | 28 | 41 | | 29 | 36 | | 30 | 41 | | 31 | 29 | | 32 | 33 | | 33 | 38 | | 34 | 27 | | 35 | 25 | | 36 | 34 | | 37 | 40 | | 38 | 34 | | 39 | 24 | | 40 | 32 | | 41 | 32 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 153 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 246 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 153 | | ratio | 0.013 | | matches | | 0 | "That same night my languages slipped into the mix—French for discretion, others for confirmation." | | 1 | "Street sounds from Brick Lane filtered upward—footsteps, distant laughter, the low rumble of traffic." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1462 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.023255813953488372 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0006839945280437756 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 153 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 153 | | mean | 9.48 | | std | 4.39 | | cv | 0.463 | | sampleLengths | | 0 | 16 | | 1 | 17 | | 2 | 25 | | 3 | 12 | | 4 | 15 | | 5 | 12 | | 6 | 10 | | 7 | 14 | | 8 | 12 | | 9 | 6 | | 10 | 7 | | 11 | 9 | | 12 | 7 | | 13 | 8 | | 14 | 9 | | 15 | 9 | | 16 | 21 | | 17 | 11 | | 18 | 12 | | 19 | 16 | | 20 | 18 | | 21 | 13 | | 22 | 7 | | 23 | 6 | | 24 | 14 | | 25 | 4 | | 26 | 15 | | 27 | 12 | | 28 | 9 | | 29 | 8 | | 30 | 4 | | 31 | 11 | | 32 | 9 | | 33 | 5 | | 34 | 14 | | 35 | 9 | | 36 | 8 | | 37 | 3 | | 38 | 8 | | 39 | 14 | | 40 | 10 | | 41 | 4 | | 42 | 14 | | 43 | 9 | | 44 | 15 | | 45 | 7 | | 46 | 9 | | 47 | 4 | | 48 | 11 | | 49 | 8 |
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| 72.77% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4444444444444444 | | totalSentences | 153 | | uniqueOpeners | 68 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 153 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 153 | | matches | | 0 | "She held the edge of" | | 1 | "He lowered the tip to" | | 2 | "Your part-time work at the" | | 3 | "She folded her arms." | | 4 | "You appeared in my path" | | 5 | "You collected names then left" | | 6 | "My quick answers kept you" | | 7 | "He remained standing, posture balanced" | | 8 | "She turned toward the table" | | 9 | "Your blade revealed itself when" | | 10 | "Your second eye held the" | | 11 | "His fingers brushed the ivory" | | 12 | "Your questions followed each word." | | 13 | "Her bright blue eyes tracked" | | 14 | "You brokered deals that passed" | | 15 | "He reached across the table" | | 16 | "His sleeve cuff rode up" | | 17 | "Your mind altered routes when" | | 18 | "She lifted her hand from" | | 19 | "His mismatched eyes remained level." |
| | ratio | 0.196 | |
| 44.97% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 127 | | totalSentences | 153 | | matches | | 0 | "The door creaked under the" | | 1 | "Aurora Carter filled the narrow" | | 2 | "Lucien Moreau stood in the" | | 3 | "Platinum hair lay flat against" | | 4 | "She held the edge of" | | 5 | "Delivery routes do not bring" | | 6 | "Lucien shifted the cane forward" | | 7 | "Routes change when information brokers" | | 8 | "This flat sits above safe" | | 9 | "Books and research notes mask" | | 10 | "Aurora eased the door wider" | | 11 | "The cramped room pressed in" | | 12 | "Stacks of volumes leaned against" | | 13 | "Scrolls curled at the ends" | | 14 | "Ptolemy the tabby padded from" | | 15 | "The cat chooses its company" | | 16 | "Lucien entered and closed the" | | 17 | "The cane clicked once on" | | 18 | "He lowered the tip to" | | 19 | "The suit fabric caught the" |
| | ratio | 0.83 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 153 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 66 | | 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 | |