| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1459 | | 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) | |
| 76.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1459 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "pulse" | | 1 | "footsteps" | | 2 | "silence" | | 3 | "weight" | | 4 | "mechanical" | | 5 | "vibrated" | | 6 | "pulsed" |
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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 | 204 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 204 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 211 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1459 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 1409 | | uniqueNames | 11 | | maxNameDensity | 1.85 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Carter | 1 | | Eva | 3 | | Richmond | 2 | | Park | 2 | | Heartstone | 3 | | Golden | 1 | | Empress | 1 | | Aurora | 26 | | Tube | 1 | | Silas | 1 | | Number | 1 |
| | persons | | 0 | "Carter" | | 1 | "Eva" | | 2 | "Heartstone" | | 3 | "Aurora" | | 4 | "Tube" | | 5 | "Silas" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Golden" |
| | globalScore | 0.577 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 108 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like fingernails against teeth" | | 1 | "as if listening" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.685 | | wordCount | 1459 | | matches | | 0 | "not from sickness but from depth, as if it drew air through a flooded chamber" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 211 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 138 | | mean | 10.57 | | std | 11.25 | | cv | 1.065 | | sampleLengths | | 0 | 31 | | 1 | 37 | | 2 | 9 | | 3 | 17 | | 4 | 12 | | 5 | 43 | | 6 | 10 | | 7 | 13 | | 8 | 4 | | 9 | 32 | | 10 | 2 | | 11 | 8 | | 12 | 12 | | 13 | 2 | | 14 | 20 | | 15 | 8 | | 16 | 4 | | 17 | 19 | | 18 | 17 | | 19 | 5 | | 20 | 61 | | 21 | 4 | | 22 | 3 | | 23 | 7 | | 24 | 2 | | 25 | 11 | | 26 | 1 | | 27 | 12 | | 28 | 1 | | 29 | 8 | | 30 | 19 | | 31 | 6 | | 32 | 6 | | 33 | 6 | | 34 | 26 | | 35 | 6 | | 36 | 4 | | 37 | 40 | | 38 | 13 | | 39 | 4 | | 40 | 9 | | 41 | 3 | | 42 | 30 | | 43 | 2 | | 44 | 4 | | 45 | 3 | | 46 | 37 | | 47 | 7 | | 48 | 3 | | 49 | 28 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 204 | | matches | | 0 | "been written" | | 1 | "been taken" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 249 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 211 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1416 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 40 | | adverbRatio | 0.02824858757062147 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.00211864406779661 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 211 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 211 | | mean | 6.91 | | std | 5.13 | | cv | 0.742 | | sampleLengths | | 0 | 31 | | 1 | 7 | | 2 | 13 | | 3 | 17 | | 4 | 5 | | 5 | 4 | | 6 | 5 | | 7 | 2 | | 8 | 10 | | 9 | 12 | | 10 | 20 | | 11 | 6 | | 12 | 6 | | 13 | 11 | | 14 | 10 | | 15 | 6 | | 16 | 7 | | 17 | 4 | | 18 | 12 | | 19 | 2 | | 20 | 3 | | 21 | 15 | | 22 | 2 | | 23 | 8 | | 24 | 12 | | 25 | 2 | | 26 | 20 | | 27 | 8 | | 28 | 4 | | 29 | 19 | | 30 | 17 | | 31 | 5 | | 32 | 8 | | 33 | 5 | | 34 | 4 | | 35 | 19 | | 36 | 25 | | 37 | 4 | | 38 | 3 | | 39 | 7 | | 40 | 2 | | 41 | 7 | | 42 | 4 | | 43 | 1 | | 44 | 12 | | 45 | 1 | | 46 | 8 | | 47 | 5 | | 48 | 3 | | 49 | 3 |
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| 40.52% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.27488151658767773 | | totalSentences | 211 | | uniqueOpeners | 58 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 171 | | matches | | 0 | "Then she had come here." | | 1 | "Instead, she stepped onto the" | | 2 | "Even the city’s distant hum" | | 3 | "Only her footsteps remained." | | 4 | "Then another set joined them." | | 5 | "Then once more." | | 6 | "Then it moved." |
| | ratio | 0.041 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 49 | | totalSentences | 171 | | matches | | 0 | "It clung to every leaf" | | 1 | "Her trainers sank into black" | | 2 | "Her phone showed 11:47 p.m." | | 3 | "She shoved it into her" | | 4 | "Their branches crossed overhead, cutting" | | 5 | "She had received the envelope" | | 6 | "Her name had been written" | | 7 | "he had told her" | | 8 | "She told herself the reason" | | 9 | "She had spent weeks following" | | 10 | "She turned towards it." | | 11 | "Her voice travelled a short" | | 12 | "She waited for an answer." | | 13 | "It sounded like fingernails against" | | 14 | "Her thumb hovered over Eva’s" | | 15 | "They had five soft petals" | | 16 | "It had the uneven rhythm" | | 17 | "She should have walked back" | | 18 | "She knew that." | | 19 | "She pictured herself doing it:" |
| | ratio | 0.287 | |
| 41.87% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 143 | | totalSentences | 171 | | matches | | 0 | "Aurora Carter found the gap" | | 1 | "Rain had passed through an" | | 2 | "It clung to every leaf" | | 3 | "Her trainers sank into black" | | 4 | "Her phone showed 11:47 p.m." | | 5 | "The screen held one bar" | | 6 | "She shoved it into her" | | 7 | "Richmond Park lay behind her:" | | 8 | "The trunks stood too close" | | 9 | "Their branches crossed overhead, cutting" | | 10 | "The pendant under her shirt" | | 11 | "Aurora touched it through the" | | 12 | "The Heartstone answered with a" | | 13 | "She had received the envelope" | | 14 | "Her name had been written" | | 15 | "Yu-Fei had looked over her" | | 16 | "he had told her" | | 17 | "Aurora had folded the note," | | 18 | "She told herself the reason" | | 19 | "Someone knew about the pendant." |
| | ratio | 0.836 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 171 | | matches | (empty) | | ratio | 0 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 3 | | matches | | 0 | "She had spent weeks following dead ends, asking questions that earned blank looks or doors shut in her face." | | 1 | "They had five soft petals each and blue-black centres, their heads tipped towards the path as if listening." | | 2 | "Its body leaned forward, as though it had caught a scent." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 3 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she whispered (whisper)" | | 2 | "the voice breathed (breathe)" |
| | dialogueSentences | 11 | | tagDensity | 0.273 | | leniency | 0.545 | | rawRatio | 1 | | effectiveRatio | 0.545 | |