| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 49 | | tagDensity | 0.388 | | leniency | 0.776 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.18% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1085 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slowly" | | 1 | "very" | | 2 | "really" |
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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) | |
| 90.78% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1085 | | totalAiIsms | 2 | | found | | | highlights | | |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 56 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 56 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 86 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 59 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1090 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 652 | | uniqueNames | 7 | | maxNameDensity | 0.77 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 5 | | Eva | 2 | | Marseille | 1 | | Started | 1 | | Ptolemy | 2 | | Commercial | 1 | | Road | 1 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Started" | | 3 | "Ptolemy" |
| | places | | 0 | "Marseille" | | 1 | "Commercial" | | 2 | "Road" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 35 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.917 | | wordCount | 1090 | | matches | | 0 | "not toward her, but to the window" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 86 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 23.19 | | std | 23.73 | | cv | 1.023 | | sampleLengths | | 0 | 28 | | 1 | 52 | | 2 | 6 | | 3 | 2 | | 4 | 6 | | 5 | 37 | | 6 | 5 | | 7 | 28 | | 8 | 3 | | 9 | 7 | | 10 | 61 | | 11 | 26 | | 12 | 7 | | 13 | 47 | | 14 | 11 | | 15 | 2 | | 16 | 8 | | 17 | 24 | | 18 | 62 | | 19 | 2 | | 20 | 8 | | 21 | 75 | | 22 | 5 | | 23 | 3 | | 24 | 43 | | 25 | 14 | | 26 | 81 | | 27 | 5 | | 28 | 69 | | 29 | 9 | | 30 | 3 | | 31 | 2 | | 32 | 24 | | 33 | 47 | | 34 | 69 | | 35 | 8 | | 36 | 1 | | 37 | 11 | | 38 | 10 | | 39 | 59 | | 40 | 6 | | 41 | 2 | | 42 | 7 | | 43 | 39 | | 44 | 15 | | 45 | 3 | | 46 | 48 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 56 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 126 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 1 | | flaggedSentences | 6 | | totalSentences | 86 | | ratio | 0.07 | | matches | | 0 | "\"A conversation. Five minutes.\" His amber eye caught the hallway light; the black one swallowed it." | | 1 | "She hated that he could still do this — turn a doorway into a negotiation, narrow the whole world down to whether or not she let him in." | | 2 | "He came in slowly, drinking the place in the way he drank in everything — the books stacked against the skirting, the scrolls bound with twine, the research notes pinned to the wall in Eva's frantic hand." | | 3 | "Lucien moved then — not toward her, but to the window, where the rain ran down the glass in long seams." | | 4 | "She looked at him — really looked, the way she'd trained herself not to." | | 5 | "\"Recently,\" he said, \"no.\" And he stayed where he stood, hands open and empty, waiting on her the way he'd waited in the corridor — except this time the door was already shut behind him, and the only thing left to decide was whether she crossed the room." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 648 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.026234567901234566 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.007716049382716049 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 86 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 86 | | mean | 12.67 | | std | 11.47 | | cv | 0.905 | | sampleLengths | | 0 | 28 | | 1 | 22 | | 2 | 8 | | 3 | 22 | | 4 | 6 | | 5 | 2 | | 6 | 6 | | 7 | 17 | | 8 | 20 | | 9 | 5 | | 10 | 16 | | 11 | 12 | | 12 | 3 | | 13 | 7 | | 14 | 28 | | 15 | 11 | | 16 | 6 | | 17 | 16 | | 18 | 5 | | 19 | 15 | | 20 | 2 | | 21 | 4 | | 22 | 7 | | 23 | 37 | | 24 | 10 | | 25 | 5 | | 26 | 6 | | 27 | 2 | | 28 | 8 | | 29 | 15 | | 30 | 9 | | 31 | 4 | | 32 | 9 | | 33 | 28 | | 34 | 3 | | 35 | 18 | | 36 | 2 | | 37 | 8 | | 38 | 24 | | 39 | 41 | | 40 | 10 | | 41 | 5 | | 42 | 3 | | 43 | 11 | | 44 | 32 | | 45 | 14 | | 46 | 21 | | 47 | 16 | | 48 | 36 | | 49 | 8 |
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| 46.90% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.37209302325581395 | | totalSentences | 86 | | uniqueOpeners | 32 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 45 | | matches | (empty) | | ratio | 0 | |
| 33.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 45 | | matches | | 0 | "He looked at her the" | | 1 | "His amber eye caught the" | | 2 | "She hated that he could" | | 3 | "She'd watched him do it" | | 4 | "She'd told herself she was" | | 5 | "She'd been wrong about that," | | 6 | "she said, and stepped back" | | 7 | "He came in slowly, drinking" | | 8 | "He set the cane against" | | 9 | "Her full name, the way" | | 10 | "She crossed her arms." | | 11 | "He said it without weight," | | 12 | "He turned his palm up," | | 13 | "Her voice cracked on the" | | 14 | "he said, A thin smile" | | 15 | "He took a step, and" | | 16 | "She looked at him —" | | 17 | "He'd come into her flat" | | 18 | "She'd built three deadbolts against" | | 19 | "She'd known, on some level" |
| | ratio | 0.467 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 43 | | totalSentences | 45 | | matches | | 0 | "The three deadbolts gave way" | | 1 | "Lucien stood in the dim" | | 2 | "The ivory cane hung loose" | | 3 | "He looked at her the" | | 4 | "Rory kept her hand on" | | 5 | "Ptolemy wove between her ankles," | | 6 | "His amber eye caught the" | | 7 | "She hated that he could" | | 8 | "She'd watched him do it" | | 9 | "She'd told herself she was" | | 10 | "She'd been wrong about that," | | 11 | "The rain answered for her." | | 12 | "A gust drove it sideways" | | 13 | "she said, and stepped back" | | 14 | "He came in slowly, drinking" | | 15 | "He set the cane against" | | 16 | "Her full name, the way" | | 17 | "She crossed her arms." | | 18 | "The crescent scar on her" | | 19 | "He said it without weight," |
| | ratio | 0.956 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 45 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 72.37% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 2 | | matches | | 0 | "he said, the vowels rounded by Marseille" | | 1 | "He took, and the floorboard complained beneath him, and he stopped as if the sound were a boundary" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 49 | | tagDensity | 0.265 | | leniency | 0.531 | | rawRatio | 0.077 | | effectiveRatio | 0.041 | |