| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 24 | | adverbTagCount | 2 | | adverbTags | | 0 | "he said softly [softly]" | | 1 | "Rory pulled back [back]" |
| | dialogueSentences | 44 | | tagDensity | 0.545 | | leniency | 1 | | rawRatio | 0.083 | | effectiveRatio | 0.083 | |
| 79.69% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1723 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "precisely" | | 1 | "softly" | | 2 | "suddenly" | | 3 | "truly" | | 4 | "slightly" |
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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) | |
| 62.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1723 | | totalAiIsms | 13 | | found | | 0 | | | 1 | | | 2 | | word | "down her spine" | | count | 1 |
| | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | word | "mask of indifference" | | count | 1 |
| | 8 | | | 9 | | | 10 | | | 11 | | | 12 | |
| | highlights | | 0 | "echoed" | | 1 | "rhythmic" | | 2 | "down her spine" | | 3 | "chaotic" | | 4 | "charged" | | 5 | "throb" | | 6 | "flicker" | | 7 | "mask of indifference" | | 8 | "reminder" | | 9 | "electric" | | 10 | "raced" | | 11 | "variables" | | 12 | "firmly" |
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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 | 84 | | matches | (empty) | |
| 74.83% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 4 | | narrationSentences | 84 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 100 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 62 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1717 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.18% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 70 | | wordCount | 1193 | | uniqueNames | 22 | | maxNameDensity | 1.68 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Tuesday | 1 | | Oxford | 1 | | Ptolemy | 3 | | Cardiff | 2 | | Evan | 3 | | London | 2 | | Golden | 1 | | Empress | 1 | | Moreau | 1 | | Brick | 2 | | Lane | 2 | | Rory | 20 | | Lucien | 20 | | Eva | 2 | | Aurora | 1 | | Carter | 1 | | Avaros | 2 | | Marseille | 1 | | Moscow | 1 | | Southwark | 1 | | Let | 1 | | Bentley | 1 |
| | persons | | 0 | "Ptolemy" | | 1 | "Evan" | | 2 | "Empress" | | 3 | "Moreau" | | 4 | "Rory" | | 5 | "Lucien" | | 6 | "Eva" | | 7 | "Aurora" | | 8 | "Carter" | | 9 | "Let" |
| | places | | 0 | "Oxford" | | 1 | "Cardiff" | | 2 | "London" | | 3 | "Golden" | | 4 | "Brick" | | 5 | "Lane" | | 6 | "Marseille" | | 7 | "Moscow" | | 8 | "Bentley" |
| | globalScore | 0.662 | | windowScore | 0.667 | |
| 74.24% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like a more dangerous version of e" | | 1 | "tasted like smoke and secrets" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.582 | | wordCount | 1717 | | matches | | 0 | "Not a flat with three locks, but a place" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 100 | | matches | | |
| 94.09% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 39.93 | | std | 19.14 | | cv | 0.479 | | sampleLengths | | 0 | 87 | | 1 | 57 | | 2 | 61 | | 3 | 23 | | 4 | 39 | | 5 | 51 | | 6 | 19 | | 7 | 37 | | 8 | 63 | | 9 | 59 | | 10 | 31 | | 11 | 37 | | 12 | 55 | | 13 | 64 | | 14 | 13 | | 15 | 80 | | 16 | 51 | | 17 | 58 | | 18 | 44 | | 19 | 42 | | 20 | 35 | | 21 | 48 | | 22 | 32 | | 23 | 42 | | 24 | 8 | | 25 | 31 | | 26 | 40 | | 27 | 65 | | 28 | 16 | | 29 | 41 | | 30 | 50 | | 31 | 41 | | 32 | 26 | | 33 | 16 | | 34 | 9 | | 35 | 23 | | 36 | 60 | | 37 | 20 | | 38 | 16 | | 39 | 22 | | 40 | 22 | | 41 | 22 | | 42 | 61 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 84 | | matches | | |
| 63.25% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 195 | | matches | | 0 | "was building" | | 1 | "was indeed attempting" | | 2 | "was currently sniffing" | | 3 | "wasn't just hiding" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 4 | | flaggedSentences | 8 | | totalSentences | 100 | | ratio | 0.08 | | matches | | 0 | "Ptolemy was indeed attempting to squeeze past her shins to investigate the expensive scent of Lucien’s cologne—sandalwood and something sharper, something metallic." | | 1 | "He didn't lean on his cane; he held it like a scepter." | | 2 | "It was worse than hate; it was an exhausting, tethering longing." | | 3 | "His touch was warm—too warm for a human, a reminder of his lineage from the realm of Avaros." | | 4 | "And beneath the logic, there was the heat. The way Lucien looked at her—as if she were the only thing in the world that held any value. He didn't see a delivery girl or a broken survivor; he saw a partner." | | 5 | "He leaned in the rest of the way, and when his lips met hers, it wasn't the tentative kiss of a reunion. It was a claim—desperate, fierce, and tasting of everything Rory had missed. It was the heat of Avaros and the cold iron of London, a collision of worlds that left her breathless and clinging to his charcoal lapels." | | 6 | "\"The cat stays, or I stay,\" Rory countered, a spark of the old Rory—the one who bargained with demons—returning to her gaze." | | 7 | "Rory smiled, a real one this time, as she reached for her coat. The three deadbolts felt suddenly unnecessary. For the first time in months, she wasn't just hiding; she was moving again. And as she followed Lucien out into the humid, spice-laden night of Brick Lane, she knew that whatever happened next, the terms had finally changed in her favor." |
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| 82.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1098 | | adjectiveStacks | 3 | | stackExamples | | 0 | "dim, spice-scented hallway" | | 1 | "small, crescent-shaped scar" | | 2 | "humid, spice-laden night" |
| | adverbCount | 42 | | adverbRatio | 0.03825136612021858 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.011839708561020037 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 100 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 100 | | mean | 17.17 | | std | 10.86 | | cv | 0.633 | | sampleLengths | | 0 | 15 | | 1 | 9 | | 2 | 26 | | 3 | 30 | | 4 | 7 | | 5 | 8 | | 6 | 6 | | 7 | 21 | | 8 | 22 | | 9 | 25 | | 10 | 18 | | 11 | 18 | | 12 | 3 | | 13 | 20 | | 14 | 19 | | 15 | 20 | | 16 | 5 | | 17 | 15 | | 18 | 16 | | 19 | 15 | | 20 | 19 | | 21 | 25 | | 22 | 12 | | 23 | 3 | | 24 | 22 | | 25 | 22 | | 26 | 16 | | 27 | 3 | | 28 | 26 | | 29 | 12 | | 30 | 18 | | 31 | 18 | | 32 | 13 | | 33 | 15 | | 34 | 4 | | 35 | 18 | | 36 | 5 | | 37 | 12 | | 38 | 38 | | 39 | 21 | | 40 | 3 | | 41 | 17 | | 42 | 23 | | 43 | 13 | | 44 | 10 | | 45 | 27 | | 46 | 11 | | 47 | 32 | | 48 | 22 | | 49 | 9 |
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| 41.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.26 | | totalSentences | 100 | | uniqueOpeners | 26 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 68.10% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 79 | | matches | | 0 | "It was nearly eleven on" | | 1 | "She told herself she wasn't" | | 2 | "She had survived Cardiff, survived" | | 3 | "He was impeccably, almost offensively," | | 4 | "His voice was a rich," | | 5 | "He looked tired, though on" | | 6 | "he murmured, using the name" | | 7 | "She nudged the cat back" | | 8 | "She stepped aside." | | 9 | "He seemed to take up" | | 10 | "He stopped in the center" | | 11 | "He didn't lean on his" | | 12 | "she countered, walking past him" | | 13 | "She needed distance." | | 14 | "he said, his voice dropping" | | 15 | "She felt the small, crescent-shaped" | | 16 | "She turned, her blue eyes" | | 17 | "He moved toward her, his" | | 18 | "He stopped just outside her" | | 19 | "It was worse than hate;" |
| | ratio | 0.38 | |
| 16.96% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 79 | | matches | | 0 | "The first bolt slid back" | | 1 | "Rory paused, her fingers hovering" | | 2 | "It was nearly eleven on" | | 3 | "Eva was away in Oxford" | | 4 | "Rory turned the second deadbolt," | | 5 | "She told herself she wasn't" | | 6 | "She had survived Cardiff, survived" | | 7 | "Lucien Moreau stood in the" | | 8 | "He was impeccably, almost offensively," | | 9 | "The ivory handle of his" | | 10 | "His voice was a rich," | | 11 | "Rory didn't step back, but" | | 12 | "Lucien’s heterochromatic eyes searched hers." | | 13 | "The black one was a" | | 14 | "He looked tired, though on" | | 15 | "he murmured, using the name" | | 16 | "Rory looked down." | | 17 | "Ptolemy was indeed attempting to" | | 18 | "She nudged the cat back" | | 19 | "She stepped aside." |
| | ratio | 0.886 | |
| 63.29% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 79 | | matches | | 0 | "Although, I suspect I am" |
| | ratio | 0.013 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 2 | | matches | | 0 | "His voice was a rich, low cello note that skipped down her spine despite her best efforts to remain numb." | | 1 | "He leaned in the rest of the way, and when his lips met hers, it wasn't the tentative kiss of a reunion. It was a claim—desperate, fierce, and tasting of everyt…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 5 | | matches | | 0 | "he said, his voice dropping an octave" | | 1 | "Lucien said, his amber eye glowing with a faint, demonic light" | | 2 | "Rory whispered, her heart hammering against her ribs like a trapped bird" | | 3 | "he conceded, his face dipping closer to hers" | | 4 | "she said, her voice steadying" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 8 | | fancyTags | | 0 | "he murmured (murmur)" | | 1 | "Rory snapped (snap)" | | 2 | "he whispered (whisper)" | | 3 | "Lucien promised (promise)" | | 4 | "Rory whispered (whisper)" | | 5 | "he conceded (concede)" | | 6 | "Rory corrected (correct)" | | 7 | "Lucien sighed (sigh)" |
| | dialogueSentences | 44 | | tagDensity | 0.318 | | leniency | 0.636 | | rawRatio | 0.571 | | effectiveRatio | 0.364 | |