| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said softly [softly]" |
| | dialogueSentences | 32 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0.167 | | effectiveRatio | 0.063 | |
| 70.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 857 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "really" | | 1 | "slowly" | | 2 | "softly" |
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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) | |
| 47.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 857 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "reminder" | | 1 | "silence" | | 2 | "unspoken" | | 3 | "stomach" | | 4 | "weight" | | 5 | "unreadable" | | 6 | "flicker" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 70 | | matches | | 0 | "was nervous" | | 1 | "n in love" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 70 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 839 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 38.23% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 671 | | uniqueNames | 5 | | maxNameDensity | 2.24 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Eva | 2 | | Carter | 1 | | Moreau | 1 | | Lucien | 12 | | Aurora | 15 |
| | persons | | 0 | "Eva" | | 1 | "Carter" | | 2 | "Moreau" | | 3 | "Lucien" | | 4 | "Aurora" |
| | places | (empty) | | globalScore | 0.382 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 839 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 19.98 | | std | 17.36 | | cv | 0.869 | | sampleLengths | | 0 | 76 | | 1 | 2 | | 2 | 4 | | 3 | 71 | | 4 | 10 | | 5 | 18 | | 6 | 22 | | 7 | 8 | | 8 | 26 | | 9 | 10 | | 10 | 31 | | 11 | 24 | | 12 | 49 | | 13 | 10 | | 14 | 11 | | 15 | 8 | | 16 | 28 | | 17 | 42 | | 18 | 8 | | 19 | 6 | | 20 | 35 | | 21 | 8 | | 22 | 8 | | 23 | 12 | | 24 | 6 | | 25 | 39 | | 26 | 5 | | 27 | 17 | | 28 | 33 | | 29 | 11 | | 30 | 14 | | 31 | 17 | | 32 | 46 | | 33 | 8 | | 34 | 7 | | 35 | 21 | | 36 | 6 | | 37 | 7 | | 38 | 39 | | 39 | 5 | | 40 | 8 | | 41 | 23 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 70 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 118 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 96 | | ratio | 0.083 | | matches | | 0 | "The scar on her left wrist—small but vivid—pulled at her skin, a reminder of the accident that had left her with a habit of gripping things when she was nervous." | | 1 | "His heterochromatic eyes—one amber, one black—locked onto hers, and for a heartbeat, the air between them crackled." | | 2 | "She exhaled through her nose, the scent of coffee and something faintly metallic—old blood, maybe—washing over her." | | 3 | "The cat—tabby, with stripes like a map of the world—blinked up at them from his perch on the windowsill." | | 4 | "Aurora’s flatmate, Eva, had a way of collecting things—things that told stories, things that whispered secrets." | | 5 | "The first one was blank, the rest filled with sketches—portraits, half-finished, of people she didn’t recognize." | | 6 | "Aurora looked at him—really looked at him—for the first time in years." | | 7 | "He looked at her—really looked at her—and for the first time in a long time, she saw the man she’d fallen in love with." |
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| 89.63% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 689 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, leather-bound journal." |
| | adverbCount | 31 | | adverbRatio | 0.04499274310595065 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.011611030478955007 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 8.74 | | std | 6.28 | | cv | 0.719 | | sampleLengths | | 0 | 20 | | 1 | 22 | | 2 | 30 | | 3 | 4 | | 4 | 2 | | 5 | 4 | | 6 | 23 | | 7 | 17 | | 8 | 4 | | 9 | 27 | | 10 | 10 | | 11 | 6 | | 12 | 12 | | 13 | 17 | | 14 | 5 | | 15 | 8 | | 16 | 14 | | 17 | 12 | | 18 | 7 | | 19 | 3 | | 20 | 19 | | 21 | 7 | | 22 | 5 | | 23 | 19 | | 24 | 3 | | 25 | 2 | | 26 | 14 | | 27 | 19 | | 28 | 16 | | 29 | 9 | | 30 | 1 | | 31 | 8 | | 32 | 3 | | 33 | 3 | | 34 | 5 | | 35 | 14 | | 36 | 5 | | 37 | 9 | | 38 | 6 | | 39 | 18 | | 40 | 18 | | 41 | 8 | | 42 | 4 | | 43 | 2 | | 44 | 7 | | 45 | 16 | | 46 | 3 | | 47 | 9 | | 48 | 8 | | 49 | 3 |
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| 46.88% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.2604166666666667 | | totalSentences | 96 | | uniqueOpeners | 25 | |
| 52.91% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 63 | | matches | | 0 | "Maybe he’d always known." |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 63 | | matches | | 0 | "She hadn’t expected him." | | 1 | "His heterochromatic eyes—one amber, one" | | 2 | "He didn’t speak first." | | 3 | "She exhaled through her nose," | | 4 | "She rolled her eyes, but" | | 5 | "He didn’t move." | | 6 | "He hesitated, then reached into" | | 7 | "He handed it to her." | | 8 | "She opened it, turning the" | | 9 | "He didn’t deny it." | | 10 | "She turned back to him," | | 11 | "He hissed, then padded over," | | 12 | "She bent down, scratching behind" | | 13 | "she said softly" | | 14 | "He looked at her—really looked" |
| | ratio | 0.238 | |
| 7.62% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 63 | | matches | | 0 | "The brass knocker scraped against" | | 1 | "Aurora Carter stood in the" | | 2 | "The scar on her left" | | 3 | "She hadn’t expected him." | | 4 | "Lucien Moreau stood just inside" | | 5 | "His heterochromatic eyes—one amber, one" | | 6 | "He didn’t speak first." | | 7 | "That was always how it" | | 8 | "Aurora said, her voice quieter" | | 9 | "Lucien’s lips twitched, just a" | | 10 | "She exhaled through her nose," | | 11 | "She rolled her eyes, but" | | 12 | "Lucien’s expression softened, just for" | | 13 | "The flat smelled of dust" | | 14 | "Aurora stepped back, gesturing toward" | | 15 | "The cat—tabby, with stripes like" | | 16 | "He didn’t move." | | 17 | "Lucien followed her inside, his" | | 18 | "The flat was small but" | | 19 | "Aurora’s flatmate, Eva, had a" |
| | ratio | 0.905 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 5.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 5 | | matches | | 0 | "The scar on her left wrist—small but vivid—pulled at her skin, a reminder of the accident that had left her with a habit of gripping things when she was nervous…" | | 1 | "The flat smelled of dust and old paper, the kind of place that held secrets like a well-worn book." | | 2 | "Aurora’s flatmate, Eva, had a way of collecting things—things that told stories, things that whispered secrets." | | 3 | "But there was still that flicker of something in his eyes, something that made her breath catch." | | 4 | "Ptolemy let out a low, satisfied growl, as if he understood something she didn’t." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "Aurora said, her voice quieter than she intended" | | 1 | "Aurora said, her voice low" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 32 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0.167 | | effectiveRatio | 0.063 | |