| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 85.09% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1677 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "perfectly" | | 1 | "slowly" | | 2 | "really" | | 3 | "lightly" | | 4 | "sharply" |
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| 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) | |
| 22.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1677 | | totalAiIsms | 26 | | found | | | highlights | | 0 | "traced" | | 1 | "lilt" | | 2 | "weight" | | 3 | "electric" | | 4 | "flicked" | | 5 | "silence" | | 6 | "facade" | | 7 | "measured" | | 8 | "vibrated" | | 9 | "grave" | | 10 | "charm" | | 11 | "shattered" | | 12 | "pulse" | | 13 | "unspoken" | | 14 | "aligned" | | 15 | "warmth" | | 16 | "fluttered" |
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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 | 364 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 5 | | hedgeCount | 1 | | narrationSentences | 364 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 364 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1677 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 63 | | wordCount | 1677 | | uniqueNames | 16 | | maxNameDensity | 1.61 | | worstName | "You" | | maxWindowNameDensity | 5.5 | | worstWindowName | "You" | | discoveredNames | | London | 2 | | Marseille | 3 | | Lucien | 2 | | Dover | 1 | | Cardiff | 1 | | Europe | 1 | | Paris | 1 | | Berlin | 1 | | You | 27 | | Watched | 5 | | Shoulders | 3 | | Fingers | 4 | | Didn | 3 | | Tell | 3 | | Warmed | 3 | | Breath | 3 |
| | persons | | 0 | "Lucien" | | 1 | "You" | | 2 | "Shoulders" | | 3 | "Fingers" | | 4 | "Didn" | | 5 | "Breath" |
| | places | | 0 | "London" | | 1 | "Marseille" | | 2 | "Dover" | | 3 | "Cardiff" | | 4 | "Europe" | | 5 | "Paris" | | 6 | "Berlin" |
| | globalScore | 0.695 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 96 | | 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 | 1677 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 364 | | matches | | |
| 73.51% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 39.93 | | std | 16.26 | | cv | 0.407 | | sampleLengths | | 0 | 88 | | 1 | 30 | | 2 | 36 | | 3 | 27 | | 4 | 47 | | 5 | 5 | | 6 | 27 | | 7 | 66 | | 8 | 45 | | 9 | 16 | | 10 | 29 | | 11 | 38 | | 12 | 53 | | 13 | 43 | | 14 | 62 | | 15 | 23 | | 16 | 29 | | 17 | 41 | | 18 | 46 | | 19 | 42 | | 20 | 32 | | 21 | 33 | | 22 | 29 | | 23 | 29 | | 24 | 3 | | 25 | 52 | | 26 | 35 | | 27 | 44 | | 28 | 69 | | 29 | 41 | | 30 | 48 | | 31 | 40 | | 32 | 41 | | 33 | 49 | | 34 | 40 | | 35 | 15 | | 36 | 60 | | 37 | 40 | | 38 | 34 | | 39 | 59 | | 40 | 55 | | 41 | 36 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 364 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 367 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 364 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1679 | | adjectiveStacks | 1 | | stackExamples | | 0 | "blue against heterochromatic amber" |
| | adverbCount | 52 | | adverbRatio | 0.030970815961882073 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.009529481834425254 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 364 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 364 | | mean | 4.61 | | std | 3.53 | | cv | 0.766 | | sampleLengths | | 0 | 4 | | 1 | 21 | | 2 | 22 | | 3 | 5 | | 4 | 5 | | 5 | 6 | | 6 | 9 | | 7 | 16 | | 8 | 5 | | 9 | 10 | | 10 | 7 | | 11 | 4 | | 12 | 4 | | 13 | 7 | | 14 | 17 | | 15 | 7 | | 16 | 5 | | 17 | 5 | | 18 | 5 | | 19 | 5 | | 20 | 6 | | 21 | 2 | | 22 | 4 | | 23 | 7 | | 24 | 3 | | 25 | 4 | | 26 | 5 | | 27 | 17 | | 28 | 2 | | 29 | 2 | | 30 | 2 | | 31 | 5 | | 32 | 5 | | 33 | 2 | | 34 | 14 | | 35 | 8 | | 36 | 3 | | 37 | 7 | | 38 | 6 | | 39 | 6 | | 40 | 5 | | 41 | 7 | | 42 | 6 | | 43 | 6 | | 44 | 5 | | 45 | 8 | | 46 | 10 | | 47 | 4 | | 48 | 8 | | 49 | 7 |
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| 84.98% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 29 | | diversityRatio | 0.5576923076923077 | | totalSentences | 364 | | uniqueOpeners | 203 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 9 | | totalSentences | 252 | | matches | | 0 | "Then you walked away." | | 1 | "Then I waited again." | | 2 | "Always convenient for you." | | 3 | "Then you vanished." | | 4 | "Bright blue against heterochromatic amber" | | 5 | "Just like everyone else." | | 6 | "Sometimes they wash everything clean." | | 7 | "Only rhythm remained." | | 8 | "All ready to break." |
| | ratio | 0.036 | |
| 45.40% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 110 | | totalSentences | 252 | | matches | | 0 | "She stood barefoot on the" | | 1 | "His silhouette filled the doorway." | | 2 | "He looked exactly like the" | | 3 | "She did not step aside." | | 4 | "Her thumb traced the crescent" | | 5 | "You knocked three times." | | 6 | "His voice carried the low" | | 7 | "They never blinked fast enough." | | 8 | "It is a cheap building." | | 9 | "She shifted the delivery box." | | 10 | "He stepped forward." | | 11 | "She watched his stride, memorizing" | | 12 | "She counted every single one." | | 13 | "He set the cane against" | | 14 | "She turned toward the narrow" | | 15 | "She poured cold water anyway." | | 16 | "You packed a single leather" | | 17 | "You took the train to" | | 18 | "You didn send a postcard." | | 19 | "You didn answer my letters" |
| | ratio | 0.437 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 180 | | totalSentences | 252 | | matches | | 0 | "The deadbolt clicked back." | | 1 | "She stood barefoot on the" | | 2 | "His silhouette filled the doorway." | | 3 | "Charcoal wool suit, perfectly pressed." | | 4 | "Ivory cane resting against his" | | 5 | "He looked exactly like the" | | 6 | "She did not step aside." | | 7 | "Her thumb traced the crescent" | | 8 | "The raised tissue stung against" | | 9 | "You knocked three times." | | 10 | "The lock was heavier than" | | 11 | "His voice carried the low" | | 12 | "Amber and black eyes locked" | | 13 | "They never blinked fast enough." | | 14 | "It is a cheap building." | | 15 | "Landlord won fix what works." | | 16 | "She shifted the delivery box." | | 17 | "Cardboard corner dug into her" | | 18 | "Silas serves proper tea." | | 19 | "Silas serves watered ale and" |
| | ratio | 0.714 | |
| 99.21% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 5 | | totalSentences | 252 | | matches | | 0 | "If he knew I was" | | 1 | "Because you stopped talking." | | 2 | "Because you look at me" | | 3 | "To the charge crackling in" | | 4 | "To the unspoken truth pressing" |
| | ratio | 0.02 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | 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 | |