| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 30 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 82.31% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 848 | | totalAiIsmAdverbs | 3 | | found | | 0 | | | 1 | | | 2 | | adverb | "barely above a whisper" | | count | 1 |
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| | highlights | | 0 | "really" | | 1 | "lazily" | | 2 | "barely above a whisper" |
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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) | |
| 17.45% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 848 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "chill" | | 1 | "warmth" | | 2 | "measured" | | 3 | "unreadable" | | 4 | "flicked" | | 5 | "weight" | | 6 | "unspoken" | | 7 | "tension" | | 8 | "footsteps" | | 9 | "silence" | | 10 | "whisper" | | 11 | "flickered" |
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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 | 53 | | matches | (empty) | |
| 88.95% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 53 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 78 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 29 | | markdownWords | 149 | | totalWords | 840 | | ratio | 0.177 | | matches | | 0 | "\"Aurora? Are you really here?\"" | | 1 | "\"You shouldn’t have come,\"" | | 2 | "\"I had to.\"" | | 3 | "\"You were supposed to be safe. But you’re not.\"" | | 4 | "\"I’m not safe anywhere anymore.\"" | | 5 | "\"You look like hell,\"" | | 6 | "\"You look like you’ve been waiting for this.\"" | | 7 | "\"I have.\"" | | 8 | "\"You came because you think I’m in danger.\"" | | 9 | "\"I came because I can’t let you walk away.\"" | | 10 | "\"Why now?\"" | | 11 | "\"Because you’re not the same person who left London.\"" | | 12 | "\"I’m not.\"" | | 13 | "\"You’re still Rory.\"" | | 14 | "\"I’m not Rory anymore.\"" | | 15 | "\"You were Rory once. And you’re still Rory.\"" | | 16 | "\"I don’t need you to remind me.\"" | | 17 | "\"Eva said you were here.\"" | | 18 | "\"She didn’t have to.\"" | | 19 | "\"She did.\"" | | 20 | "\"You’re shaking.\"" | | 21 | "\"I don’t know what I’m doing here.\"" | | 22 | "\"You’re here because you’re afraid.\"" | | 23 | "\"I’m afraid of everything.\"" | | 24 | "\"Then let me help.\"" | | 25 | "\"I don’t know if I can.\"" | | 26 | "\"Then let’s find out.\"" | | 27 | "\"What do you want from me?\"" | | 28 | "\"The same thing I always want. Your truth.\"" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 84.59% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 688 | | uniqueNames | 6 | | maxNameDensity | 1.31 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Eva | 3 | | Carter | 2 | | Moreau | 2 | | Aurora | 9 | | Ptolemy | 2 | | Lucien | 8 |
| | persons | | 0 | "Eva" | | 1 | "Carter" | | 2 | "Moreau" | | 3 | "Aurora" | | 4 | "Ptolemy" | | 5 | "Lucien" |
| | places | (empty) | | globalScore | 0.846 | | windowScore | 1 | |
| 21.79% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | glossingSentenceCount | 2 | | matches | | 0 | "as if sensing her distress" | | 1 | "felt like the first time" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 840 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 78 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 24 | | std | 22.35 | | cv | 0.931 | | sampleLengths | | 0 | 101 | | 1 | 15 | | 2 | 29 | | 3 | 70 | | 4 | 8 | | 5 | 31 | | 6 | 16 | | 7 | 64 | | 8 | 10 | | 9 | 26 | | 10 | 6 | | 11 | 26 | | 12 | 9 | | 13 | 44 | | 14 | 9 | | 15 | 28 | | 16 | 3 | | 17 | 11 | | 18 | 8 | | 19 | 24 | | 20 | 36 | | 21 | 7 | | 22 | 2 | | 23 | 62 | | 24 | 9 | | 25 | 12 | | 26 | 5 | | 27 | 12 | | 28 | 4 | | 29 | 35 | | 30 | 20 | | 31 | 56 | | 32 | 14 | | 33 | 13 | | 34 | 15 |
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| 98.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 53 | | matches | | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 121 | | matches | | 0 | "were measuring" | | 1 | "wasn’t looking" | | 2 | "was falling" | | 3 | "was waiting" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 78 | | ratio | 0.064 | | matches | | 0 | "The scar on her wrist—small but vivid, the mark of a childhood accident—twitched as she remembered the way her father had always called it her \"little dragon mark,\" though she’d never told him the truth about what had happened that day." | | 1 | "His suit was immaculate—charcoal gray, tailored to perfection—but his face was unreadable, the usual smirk absent." | | 2 | "Eva’s flat was a labyrinth of books and scrolls, the air thick with the scent of old paper and something faintly metallic—like old coins or the faintest trace of blood." | | 3 | "But the way he stood there, the way his cane tapped against the floor when he wasn’t looking, the way his eyes—one amber, one black—burned with something she hadn’t seen in years, made her hesitate." | | 4 | "But the way he looked at her—one eye black, one amber, burning with something she didn’t understand—made her feel like she was being seen for the first time in years." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 696 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.035919540229885055 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005747126436781609 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 78 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 78 | | mean | 10.77 | | std | 8.6 | | cv | 0.798 | | sampleLengths | | 0 | 27 | | 1 | 19 | | 2 | 41 | | 3 | 14 | | 4 | 10 | | 5 | 5 | | 6 | 3 | | 7 | 4 | | 8 | 22 | | 9 | 23 | | 10 | 16 | | 11 | 31 | | 12 | 8 | | 13 | 22 | | 14 | 9 | | 15 | 11 | | 16 | 5 | | 17 | 30 | | 18 | 15 | | 19 | 19 | | 20 | 10 | | 21 | 18 | | 22 | 8 | | 23 | 4 | | 24 | 2 | | 25 | 9 | | 26 | 9 | | 27 | 8 | | 28 | 9 | | 29 | 4 | | 30 | 3 | | 31 | 35 | | 32 | 2 | | 33 | 9 | | 34 | 7 | | 35 | 19 | | 36 | 2 | | 37 | 3 | | 38 | 5 | | 39 | 2 | | 40 | 4 | | 41 | 8 | | 42 | 8 | | 43 | 9 | | 44 | 7 | | 45 | 3 | | 46 | 28 | | 47 | 5 | | 48 | 3 | | 49 | 4 |
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| 42.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.21794871794871795 | | totalSentences | 78 | | uniqueOpeners | 17 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 81.54% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 52 | | matches | | 0 | "She clutched the doorframe, her" | | 1 | "She didn’t have to." | | 2 | "His suit was immaculate—charcoal gray," | | 3 | "His heterochromatic eyes flicked between" | | 4 | "she said, voice tight" | | 5 | "His voice was smooth, but" | | 6 | "He didn’t move when Lucien" | | 7 | "He didn’t deny it." | | 8 | "She should have left." | | 9 | "She knew that." | | 10 | "He always knew exactly what" | | 11 | "She turned away, her fingers" | | 12 | "He just stood there, the" | | 13 | "She pressed her back against" | | 14 | "She exhaled, her fingers stilling" | | 15 | "She should have left." | | 16 | "She knew that." | | 17 | "she asked, her voice barely" |
| | ratio | 0.346 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 48 | | totalSentences | 52 | | matches | | 0 | "The brass knocker scraped against" | | 1 | "Aurora Carter stood just inside" | | 2 | "The scar on her wrist—small" | | 3 | "She clutched the doorframe, her" | | 4 | "Eva’s voice came from the" | | 5 | "Aurora didn’t answer." | | 6 | "She didn’t have to." | | 7 | "The way the door creaked" | | 8 | "Lucien Moreau stood there, his" | | 9 | "His suit was immaculate—charcoal gray," | | 10 | "His heterochromatic eyes flicked between" | | 11 | "she said, voice tight" | | 12 | "His voice was smooth, but" | | 13 | "Aurora exhaled through her nose," | | 14 | "Eva’s flat was a labyrinth" | | 15 | "The cat, Ptolemy, watched from" | | 16 | "He didn’t move when Lucien" | | 17 | "Lucien said, not looking at" | | 18 | "Aurora turned to face him," | | 19 | "He didn’t deny it." |
| | ratio | 0.923 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 28.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 4 | | matches | | 0 | "Lucien Moreau stood there, his cane resting against the wall as if it were a crutch, though it was more like a weapon." | | 1 | "His heterochromatic eyes flicked between her and the door, as if he were measuring the room, the weight of the past, the unspoken tension hanging between them l…" | | 2 | "The door swung shut behind her, the deadbolts clicking into place with a finality that made her chest ache." | | 3 | "The cat, Ptolemy, padded over, his tail curling around her ankles as if sensing her distress." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 3 | | matches | | 0 | "she said, voice tight" | | 1 | "Lucien said, not looking at her" | | 2 | "she asked, her voice barely above a whisper" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 30 | | tagDensity | 0.1 | | leniency | 0.2 | | rawRatio | 0 | | effectiveRatio | 0 | |