| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 6 | | adverbTags | | 0 | "Oliver added nervously [nervously]" | | 1 | "the woman said breathlessly [breathlessly]" | | 2 | "Eva replied mysteriously [mysteriously]" | | 3 | "Eva explained patiently [patiently]" | | 4 | "Harlow said grimly [grimly]" | | 5 | "Eva asked anxiously [anxiously]" |
| | dialogueSentences | 19 | | tagDensity | 0.474 | | leniency | 0.947 | | rawRatio | 0.667 | | effectiveRatio | 0.632 | |
| 73.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 954 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "nervously" | | 1 | "suddenly" | | 2 | "anxiously" |
| |
| 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) | |
| 10.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 954 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoed" | | 2 | "clandestine" | | 3 | "unravel" | | 4 | "furrowing" | | 5 | "intricate" | | 6 | "scanning" | | 7 | "eyebrow" | | 8 | "raced" | | 9 | "scanned" | | 10 | "tension" | | 11 | "weight" | | 12 | "silence" | | 13 | "determined" | | 14 | "depths" |
| |
| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
| | 1 | | label | "couldn't help but" | | count | 1 |
| | 2 | | label | "weight of words/silence" | | count | 1 |
|
| | highlights | | 0 | "clenched her fists" | | 1 | "couldn't help but feel" | | 2 | "the weight of the words" |
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| 87.12% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 3 | | narrationSentences | 66 | | matches | | 0 | "t in determination" | | 1 | "filled with determination" | | 2 | "d with determination" |
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| 56.28% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 66 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 76 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 955 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 46.72% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 823 | | uniqueNames | 9 | | maxNameDensity | 2.07 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 17 | | Tube | 1 | | Veil | 5 | | Market | 4 | | Morris | 1 | | Oliver | 5 | | Compass | 1 | | Eva | 10 | | Kowalski | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Market" | | 2 | "Morris" | | 3 | "Oliver" | | 4 | "Compass" | | 5 | "Eva" | | 6 | "Kowalski" |
| | places | | | globalScore | 0.467 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 95.29% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.047 | | wordCount | 955 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 76 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 28.94 | | std | 14.52 | | cv | 0.502 | | sampleLengths | | 0 | 62 | | 1 | 31 | | 2 | 56 | | 3 | 15 | | 4 | 20 | | 5 | 43 | | 6 | 8 | | 7 | 26 | | 8 | 33 | | 9 | 31 | | 10 | 13 | | 11 | 39 | | 12 | 12 | | 13 | 34 | | 14 | 9 | | 15 | 23 | | 16 | 8 | | 17 | 22 | | 18 | 34 | | 19 | 15 | | 20 | 17 | | 21 | 42 | | 22 | 21 | | 23 | 30 | | 24 | 7 | | 25 | 15 | | 26 | 33 | | 27 | 46 | | 28 | 34 | | 29 | 50 | | 30 | 40 | | 31 | 39 | | 32 | 47 |
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| 94.63% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 66 | | matches | | 0 | "been contained" | | 1 | "was gone" | | 2 | "been unleashed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 143 | | matches | | 0 | "was carrying" | | 1 | "was looking" |
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| 67.67% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 76 | | ratio | 0.026 | | matches | | 0 | "Harlow recognized it instantly – a Veil Compass, attuned to supernatural energy." | | 1 | "A figure emerged from the shadows – a woman with curly red hair and round glasses perched on her freckled nose." |
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| 94.36% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 822 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.037712895377128956 | | lyAdverbCount | 22 | | lyAdverbRatio | 0.0267639902676399 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 76 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 76 | | mean | 12.57 | | std | 6.16 | | cv | 0.49 | | sampleLengths | | 0 | 27 | | 1 | 16 | | 2 | 19 | | 3 | 18 | | 4 | 13 | | 5 | 13 | | 6 | 18 | | 7 | 16 | | 8 | 9 | | 9 | 15 | | 10 | 3 | | 11 | 17 | | 12 | 8 | | 13 | 11 | | 14 | 17 | | 15 | 7 | | 16 | 6 | | 17 | 2 | | 18 | 14 | | 19 | 12 | | 20 | 10 | | 21 | 14 | | 22 | 9 | | 23 | 21 | | 24 | 10 | | 25 | 6 | | 26 | 7 | | 27 | 26 | | 28 | 13 | | 29 | 5 | | 30 | 7 | | 31 | 7 | | 32 | 15 | | 33 | 12 | | 34 | 8 | | 35 | 1 | | 36 | 6 | | 37 | 17 | | 38 | 4 | | 39 | 4 | | 40 | 22 | | 41 | 6 | | 42 | 17 | | 43 | 11 | | 44 | 8 | | 45 | 7 | | 46 | 17 | | 47 | 13 | | 48 | 13 | | 49 | 16 |
| |
| 56.58% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.35526315789473684 | | totalSentences | 76 | | uniqueOpeners | 27 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 66 | | matches | | 0 | "Suddenly, the sound of footsteps" | | 1 | "Suddenly, the body convulsed violently," |
| | ratio | 0.03 | |
| 92.73% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 66 | | matches | | 0 | "Her footsteps echoed off the" | | 1 | "Her fingers brushed against the" | | 2 | "She didn't believe in magic" | | 3 | "She lifted her eyes to" | | 4 | "His face was pale, his" | | 5 | "She frowned, her brow furrowing" | | 6 | "It was unlike any she'd" | | 7 | "He pointed to a small" | | 8 | "She stood up abruptly, her" | | 9 | "She was carrying a worn" | | 10 | "She knelt beside the body" | | 11 | "Her green eyes darted back" | | 12 | "He was a vessel for" | | 13 | "She turned back to Eva," | | 14 | "she said, holding the book" | | 15 | "She couldn't afford to let" | | 16 | "She had no choice but" | | 17 | "She glanced at Eva, who" | | 18 | "She was a detective, damn" | | 19 | "She had sworn an oath" |
| | ratio | 0.318 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 66 | | matches | | 0 | "The stench of decay and" | | 1 | "Her footsteps echoed off the" | | 2 | "Her fingers brushed against the" | | 3 | "She didn't believe in magic" | | 4 | "The victim's body lay sprawled" | | 5 | "She lifted her eyes to" | | 6 | "His face was pale, his" | | 7 | "Harlow asked, her sharp jaw" | | 8 | "Oliver swallowed hard." | | 9 | "Harlow knelt beside the body," | | 10 | "She frowned, her brow furrowing" | | 11 | "The man's chest bore an" | | 12 | "It was unlike any she'd" | | 13 | "Oliver added nervously" | | 14 | "He pointed to a small" | | 15 | "Harlow recognized it instantly –" | | 16 | "She stood up abruptly, her" | | 17 | "Harlow tensed, her hand instinctively" | | 18 | "A figure emerged from the" | | 19 | "She was carrying a worn" |
| | ratio | 0.833 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 66 | | matches | | 0 | "If Eva was right, then" | | 1 | "If the entity found another" |
| | ratio | 0.03 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 44.74% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 2 | | fancyTags | | 0 | "Oliver added nervously (add)" | | 1 | "Eva explained patiently (explain)" |
| | dialogueSentences | 19 | | tagDensity | 0.421 | | leniency | 0.842 | | rawRatio | 0.25 | | effectiveRatio | 0.211 | |