| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1330 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 84.96% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1330 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "etched" | | 1 | "aligned" | | 2 | "measured" | | 3 | "warmth" |
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| 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 | 113 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 113 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 130 | | 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 | 1330 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 1101 | | uniqueNames | 16 | | maxNameDensity | 1.09 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Blood" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Kowalski | 1 | | British | 2 | | Museum | 2 | | Shade | 2 | | Ancient | 1 | | History | 1 | | Oxford | 1 | | Eva | 8 | | Veil | 1 | | Market | 1 | | Morris | 2 | | Quinn | 12 | | Blood | 9 | | Dust | 3 |
| | persons | | 0 | "Kowalski" | | 1 | "Museum" | | 2 | "Eva" | | 3 | "Market" | | 4 | "Morris" | | 5 | "Quinn" | | 6 | "Blood" |
| | places | | 0 | "British" | | 1 | "Oxford" | | 2 | "Veil" | | 3 | "Dust" |
| | globalScore | 0.955 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 99 | | 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 | 1330 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 130 | | matches | | 0 | "broke that sheet" | | 1 | "followed that path" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 38 | | std | 28.96 | | cv | 0.762 | | sampleLengths | | 0 | 93 | | 1 | 75 | | 2 | 18 | | 3 | 81 | | 4 | 4 | | 5 | 35 | | 6 | 26 | | 7 | 59 | | 8 | 11 | | 9 | 22 | | 10 | 12 | | 11 | 45 | | 12 | 8 | | 13 | 54 | | 14 | 24 | | 15 | 78 | | 16 | 11 | | 17 | 30 | | 18 | 11 | | 19 | 75 | | 20 | 12 | | 21 | 30 | | 22 | 17 | | 23 | 89 | | 24 | 13 | | 25 | 37 | | 26 | 18 | | 27 | 76 | | 28 | 15 | | 29 | 70 | | 30 | 10 | | 31 | 65 | | 32 | 15 | | 33 | 87 | | 34 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 113 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 156 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 130 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1105 | | adjectiveStacks | 1 | | stackExamples | | 0 | "pressed hard against leather" |
| | adverbCount | 8 | | adverbRatio | 0.007239819004524887 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0018099547511312218 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 130 | | echoCount | 0 | | echoWords | (empty) | |
| 99.70% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 130 | | mean | 10.23 | | std | 4.08 | | cv | 0.399 | | sampleLengths | | 0 | 17 | | 1 | 14 | | 2 | 16 | | 3 | 7 | | 4 | 9 | | 5 | 5 | | 6 | 9 | | 7 | 16 | | 8 | 13 | | 9 | 10 | | 10 | 7 | | 11 | 7 | | 12 | 6 | | 13 | 15 | | 14 | 17 | | 15 | 18 | | 16 | 13 | | 17 | 9 | | 18 | 11 | | 19 | 14 | | 20 | 10 | | 21 | 6 | | 22 | 10 | | 23 | 8 | | 24 | 4 | | 25 | 21 | | 26 | 9 | | 27 | 5 | | 28 | 26 | | 29 | 11 | | 30 | 6 | | 31 | 6 | | 32 | 5 | | 33 | 12 | | 34 | 10 | | 35 | 9 | | 36 | 11 | | 37 | 12 | | 38 | 10 | | 39 | 12 | | 40 | 8 | | 41 | 8 | | 42 | 7 | | 43 | 12 | | 44 | 10 | | 45 | 8 | | 46 | 8 | | 47 | 5 | | 48 | 14 | | 49 | 13 |
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| 48.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.34615384615384615 | | totalSentences | 130 | | uniqueOpeners | 45 | |
| 29.50% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 113 | | matches | | 0 | "Closely cropped salt-and-pepper hair sat" |
| | ratio | 0.009 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 113 | | matches | | 0 | "Her torch beam crossed cracked" | | 1 | "Her five-foot-nine frame filled the" | | 2 | "Her worn leather watch knocked" | | 3 | "She tucked hair behind her" | | 4 | "His right hand clutched a" | | 5 | "Her finger tapped the tear." | | 6 | "Her glasses slipped and she" | | 7 | "Her satchel thumped her knee." | | 8 | "She pulled a rubbing from" | | 9 | "Her master of Ancient History" | | 10 | "Her torch swept back across" | | 11 | "Her mouth flattened." | | 12 | "She pushed her glasses up" | | 13 | "His soles stayed clean." | | 14 | "Her freckles stood out in" | | 15 | "She shook her head at" | | 16 | "His back had pressed the" | | 17 | "Her worn leather watch showed" | | 18 | "She shoved it behind her" | | 19 | "Her mouth tightened." |
| | ratio | 0.195 | |
| 48.50% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 113 | | matches | | 0 | "Quinn ducked under the tape" | | 1 | "Water dripped through a cracked" | | 2 | "Her torch beam crossed cracked" | | 3 | "Her five-foot-nine frame filled the" | | 4 | "Brown eyes narrowed against dust." | | 5 | "A sharp jaw caught light" | | 6 | "Her worn leather watch knocked" | | 7 | "Eva Kowalski knelt beside the" | | 8 | "Books crowded the satchel and" | | 9 | "She tucked hair behind her" | | 10 | "A British Museum archive pass" | | 11 | "Quinn crouched on the opposite" | | 12 | "The man lay face down" | | 13 | "His right hand clutched a" | | 14 | "Blood pooled under his torso" | | 15 | "A small brass compass sat" | | 16 | "A Shade artisan etched protective" | | 17 | "The needle pointed down through" | | 18 | "Eva lifted the coat hem" | | 19 | "Blood caked the tear and" |
| | ratio | 0.823 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 113 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | 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 | |