| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 70.76% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1539 | | totalAiIsmAdverbs | 9 | | found | | | highlights | | 0 | "sharply" | | 1 | "slightly" | | 2 | "utterly" | | 3 | "carefully" | | 4 | "lightly" | | 5 | "softly" | | 6 | "slowly" | | 7 | "gently" |
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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) | |
| 41.52% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1539 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "vibrated" | | 1 | "silk" | | 2 | "unspoken" | | 3 | "fractured" | | 4 | "predictable" | | 5 | "chaotic" | | 6 | "navigated" | | 7 | "whisper" | | 8 | "could feel" | | 9 | "warmth" | | 10 | "tracing" | | 11 | "scanning" | | 12 | "searing" | | 13 | "magnetic" | | 14 | "weight" |
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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 | 122 | | matches | (empty) | |
| 60.89% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 3 | | narrationSentences | 122 | | filterMatches | | 0 | "look" | | 1 | "feel" | | 2 | "see" | | 3 | "know" |
| | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 122 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1526 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 8 | | matches | | 0 | "Please, he said quietly." | | 1 | "Even the beasts of this city have missed you, he murmured, though his unblinking gaze remained fixed on Aurora." | | 2 | "It was, he replied, straightening up." | | 3 | "You do not get to do this, she said, her voice dropping to a fierce whisper." | | 4 | "I can take care of myself, she said stubbornly." | | 5 | "I know you are not, Lucien said softly." | | 6 | "I remembered this scar every single day I was away, he confessed, his voice turning ragged." | | 7 | "I came for you, he said, his heterochromatic eyes searing into hers." |
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| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 67 | | wordCount | 1526 | | uniqueNames | 23 | | maxNameDensity | 1.05 | | worstName | "Aurora" | | maxWindowNameDensity | 2.5 | | worstWindowName | "You" | | discoveredNames | | Brick | 1 | | Lane | 1 | | Golden | 1 | | Empress | 1 | | Yu-Fei | 1 | | Cheung | 1 | | Eva | 6 | | London | 4 | | Moreau | 1 | | Lucien | 11 | | Thames | 1 | | Rory | 2 | | French | 1 | | Cardiff | 1 | | Evan | 2 | | Aurora | 16 | | Frenchman | 1 | | Luc | 2 | | Parisian | 1 | | Ptolemy | 3 | | Avaros | 1 | | Marseille | 1 | | You | 7 |
| | persons | | 0 | "Yu-Fei" | | 1 | "Cheung" | | 2 | "Eva" | | 3 | "Moreau" | | 4 | "Lucien" | | 5 | "Rory" | | 6 | "Evan" | | 7 | "Aurora" | | 8 | "Luc" | | 9 | "Ptolemy" | | 10 | "You" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Golden" | | 3 | "London" | | 4 | "Thames" | | 5 | "Cardiff" | | 6 | "Avaros" | | 7 | "Marseille" |
| | globalScore | 0.976 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 103 | | glossingSentenceCount | 1 | | matches | | 0 | "as if approaching a wild animal, he reached out and took hold of her left hand" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.655 | | wordCount | 1526 | | matches | | 0 | "not tower, but his presence seemed to consume the available oxygen" |
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| 57.38% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 4 | | totalSentences | 122 | | matches | | 0 | "doubt that, she" | | 1 | "clear that my" | | 2 | "learned that a" | | 3 | "opened that door" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 39.13 | | std | 21.81 | | cv | 0.557 | | sampleLengths | | 0 | 48 | | 1 | 62 | | 2 | 64 | | 3 | 28 | | 4 | 79 | | 5 | 32 | | 6 | 27 | | 7 | 25 | | 8 | 40 | | 9 | 24 | | 10 | 42 | | 11 | 8 | | 12 | 67 | | 13 | 14 | | 14 | 78 | | 15 | 42 | | 16 | 19 | | 17 | 44 | | 18 | 20 | | 19 | 41 | | 20 | 51 | | 21 | 6 | | 22 | 4 | | 23 | 90 | | 24 | 58 | | 25 | 32 | | 26 | 37 | | 27 | 3 | | 28 | 57 | | 29 | 62 | | 30 | 22 | | 31 | 27 | | 32 | 44 | | 33 | 28 | | 34 | 11 | | 35 | 31 | | 36 | 58 | | 37 | 68 | | 38 | 33 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 122 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 268 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 122 | | ratio | 0.008 | | matches | | 0 | "Every available surface—the meager dining table, the sagging sofa, even the kitchen counters—was buried under towers of esoteric books, crumbling scrolls, and frantically scribbled research notes." |
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| 93.34% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1539 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, crescent-shaped scar" |
| | adverbCount | 57 | | adverbRatio | 0.037037037037037035 | | lyAdverbCount | 32 | | lyAdverbRatio | 0.02079272254710851 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 122 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 122 | | mean | 12.51 | | std | 7.23 | | cv | 0.578 | | sampleLengths | | 0 | 27 | | 1 | 14 | | 2 | 3 | | 3 | 2 | | 4 | 2 | | 5 | 16 | | 6 | 21 | | 7 | 25 | | 8 | 16 | | 9 | 9 | | 10 | 4 | | 11 | 13 | | 12 | 22 | | 13 | 28 | | 14 | 14 | | 15 | 16 | | 16 | 20 | | 17 | 7 | | 18 | 10 | | 19 | 12 | | 20 | 7 | | 21 | 25 | | 22 | 27 | | 23 | 7 | | 24 | 9 | | 25 | 9 | | 26 | 12 | | 27 | 2 | | 28 | 26 | | 29 | 8 | | 30 | 10 | | 31 | 6 | | 32 | 9 | | 33 | 22 | | 34 | 11 | | 35 | 4 | | 36 | 4 | | 37 | 9 | | 38 | 26 | | 39 | 9 | | 40 | 6 | | 41 | 17 | | 42 | 14 | | 43 | 17 | | 44 | 11 | | 45 | 18 | | 46 | 6 | | 47 | 26 | | 48 | 16 | | 49 | 15 |
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| 36.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.2786885245901639 | | totalSentences | 122 | | uniqueOpeners | 34 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 119 | | matches | | 0 | "Then the middle lock." | | 1 | "Finally, she twisted the top" | | 2 | "Even the beasts of this" | | 3 | "Then why did you?" | | 4 | "Slowly, as if approaching a" |
| | ratio | 0.042 | |
| 41.85% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 53 | | totalSentences | 119 | | matches | | 0 | "She paused with a stack" | | 1 | "She undid the bottom deadbolt" | | 2 | "She opened the door just" | | 3 | "His tailored charcoal suit fit" | | 4 | "His slicked-back platinum blond hair" | | 5 | "They had not spoken in" | | 6 | "He leaned slightly on his" | | 7 | "His voice was a low," | | 8 | "She did not move to" | | 9 | "You do not exactly have" | | 10 | "She had spent a long" | | 11 | "She had finally carved out" | | 12 | "He was chaotic, preternaturally dangerous," | | 13 | "I doubt that, she countered," | | 14 | "You said it was a" | | 15 | "It was, he replied, straightening" | | 16 | "It still is." | | 17 | "He took a step toward" | | 18 | "She craned her neck to" | | 19 | "You do not get to" |
| | ratio | 0.445 | |
| 90.25% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 88 | | totalSentences | 119 | | matches | | 0 | "The heavy scent of roasted" | | 1 | "Aurora ignored it, focusing instead" | | 2 | "She paused with a stack" | | 3 | "Ptolemy, Eva’s massive tabby cat," | | 4 | "Aurora set the containers down" | | 5 | "She undid the bottom deadbolt" | | 6 | "She opened the door just" | | 7 | "The air in the narrow" | | 8 | "Lucien Moreau stood beneath the" | | 9 | "His tailored charcoal suit fit" | | 10 | "His slicked-back platinum blond hair" | | 11 | "Aurora’s breath caught as she" | | 12 | "They had not spoken in" | | 13 | "Aurora stared at him, acutely" | | 14 | "He leaned slightly on his" | | 15 | "Aurora knew it concealed a" | | 16 | "His voice was a low," | | 17 | "She did not move to" | | 18 | "You do not exactly have" | | 19 | "A shadow passed over his" |
| | ratio | 0.739 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 119 | | matches | | 0 | "To the untrained eye, it" | | 1 | "Because of you!" | | 2 | "Because you do not belong" | | 3 | "Because three hours ago, I" |
| | ratio | 0.034 | |
| 75.29% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 74 | | technicalSentenceCount | 7 | | matches | | 0 | "Ptolemy, Eva’s massive tabby cat, wound himself in a figure eight around her ankles, letting out a low, demanding yowl that vibrated against her calves." | | 1 | "His voice was a low, melodic drawl, his French accent wrapping around her name in a way that made the hairs on her arms stand up." | | 2 | "The half-demon fixer of the London underworld was famously impassive, a man who brokered secrets and survived by never showing his hand." | | 3 | "She had spent a long time rebuilding her life, escaping an abusive ex in Cardiff named Evan, fleeing to London, taking refuge with her friend Eva." | | 4 | "Slowly, as if approaching a wild animal, he reached out and took hold of her left hand." | | 5 | "His thumb brushed over her wrist, tracing the small, crescent-shaped scar she had earned falling out of a tree in her childhood." | | 6 | "Aurora looked up at him, her chest rising and falling rapidly." |
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| 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 | |