| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "He moved finally [finally]" |
| | dialogueSentences | 77 | | tagDensity | 0.208 | | leniency | 0.416 | | rawRatio | 0.063 | | effectiveRatio | 0.026 | |
| 87.06% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1545 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "perfectly" | | 1 | "quickly" | | 2 | "slightly" | | 3 | "very" |
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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) | |
| 54.69% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1545 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "gleaming" | | 1 | "throbbed" | | 2 | "etched" | | 3 | "intensity" | | 4 | "weight" | | 5 | "charged" | | 6 | "electric" | | 7 | "could feel" | | 8 | "flickered" | | 9 | "implication" | | 10 | "eyebrow" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 108 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 108 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 168 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1544 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.17% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1014 | | uniqueNames | 8 | | maxNameDensity | 1.68 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Lucien | 13 | | Moreau | 1 | | Rory | 17 | | Ptolemy | 5 | | Greek | 2 | | Eva | 4 | | Aurora | 1 | | Evan | 1 |
| | persons | | 0 | "Lucien" | | 1 | "Moreau" | | 2 | "Rory" | | 3 | "Ptolemy" | | 4 | "Eva" | | 5 | "Evan" |
| | places | (empty) | | globalScore | 0.662 | | windowScore | 0.667 | |
| 81.51% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like he'd been carved from somethi" | | 1 | "looked like a man who'd been holding up a" |
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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 | 1544 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 168 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 91 | | mean | 16.97 | | std | 14.83 | | cv | 0.874 | | sampleLengths | | 0 | 64 | | 1 | 5 | | 2 | 21 | | 3 | 2 | | 4 | 46 | | 5 | 6 | | 6 | 25 | | 7 | 45 | | 8 | 7 | | 9 | 22 | | 10 | 5 | | 11 | 3 | | 12 | 14 | | 13 | 30 | | 14 | 17 | | 15 | 10 | | 16 | 5 | | 17 | 58 | | 18 | 7 | | 19 | 6 | | 20 | 13 | | 21 | 21 | | 22 | 24 | | 23 | 54 | | 24 | 23 | | 25 | 1 | | 26 | 16 | | 27 | 8 | | 28 | 12 | | 29 | 54 | | 30 | 7 | | 31 | 20 | | 32 | 4 | | 33 | 4 | | 34 | 48 | | 35 | 7 | | 36 | 14 | | 37 | 4 | | 38 | 7 | | 39 | 2 | | 40 | 26 | | 41 | 46 | | 42 | 4 | | 43 | 6 | | 44 | 31 | | 45 | 16 | | 46 | 18 | | 47 | 5 | | 48 | 23 | | 49 | 14 |
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| 98.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 108 | | matches | | 0 | "been carved" | | 1 | "been etched" |
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| 53.48% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 182 | | matches | | 0 | "were avoiding" | | 1 | "was licking" | | 2 | "was handling" | | 3 | "were starting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 168 | | ratio | 0.006 | | matches | | 0 | "Then Rory heard it—a soft scrape against the brickwork outside the window, barely there, almost lost beneath the low hum of the curry house's extractor fan." |
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| 93.74% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1018 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 48 | | adverbRatio | 0.047151277013752456 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.014734774066797643 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 168 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 168 | | mean | 9.19 | | std | 6.41 | | cv | 0.698 | | sampleLengths | | 0 | 24 | | 1 | 3 | | 2 | 16 | | 3 | 21 | | 4 | 5 | | 5 | 13 | | 6 | 8 | | 7 | 2 | | 8 | 30 | | 9 | 16 | | 10 | 6 | | 11 | 13 | | 12 | 2 | | 13 | 1 | | 14 | 9 | | 15 | 5 | | 16 | 23 | | 17 | 8 | | 18 | 9 | | 19 | 7 | | 20 | 2 | | 21 | 6 | | 22 | 12 | | 23 | 2 | | 24 | 5 | | 25 | 3 | | 26 | 3 | | 27 | 5 | | 28 | 6 | | 29 | 11 | | 30 | 10 | | 31 | 3 | | 32 | 6 | | 33 | 6 | | 34 | 11 | | 35 | 10 | | 36 | 5 | | 37 | 11 | | 38 | 3 | | 39 | 33 | | 40 | 4 | | 41 | 1 | | 42 | 6 | | 43 | 7 | | 44 | 6 | | 45 | 7 | | 46 | 6 | | 47 | 21 | | 48 | 9 | | 49 | 15 |
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| 47.42% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.30952380952380953 | | totalSentences | 168 | | uniqueOpeners | 52 | |
| 68.03% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 98 | | matches | | 0 | "Then Rory heard it—a soft" | | 1 | "Then the knock came again," |
| | ratio | 0.02 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 98 | | matches | | 0 | "Her heart hammered an obnoxious" | | 1 | "He said it flat, clinical" | | 2 | "He didn't smile." | | 3 | "She let him." | | 4 | "He stood perfectly still in" | | 5 | "His posture was immaculate." | | 6 | "He tilted his chin toward" | | 7 | "He shifted his weight" | | 8 | "He said it without accusation," | | 9 | "Her breath caught." | | 10 | "She could feel the heat" | | 11 | "He lowered his head slightly," | | 12 | "He moved finally, crossing to" | | 13 | "His cane tapped a slow" | | 14 | "His voice was quieter now," | | 15 | "He turned fully, the full" | | 16 | "He ran a hand through" | | 17 | "He nodded stiffly, like the" | | 18 | "He turned toward the door," | | 19 | "Her hand lifted, caught the" |
| | ratio | 0.276 | |
| 11.02% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 88 | | totalSentences | 98 | | matches | | 0 | "The door swung open before" | | 1 | "Platinum hair slicked back like" | | 2 | "The rain had stopped hours" | | 3 | "Rory wiped curry sauce from" | | 4 | "The paper bag in her" | | 5 | "Lucien's mismatched eyes, one amber" | | 6 | "The tabby cat, Ptolemy, mewled" | | 7 | "Rory stepped forward, forcing him" | | 8 | "The flat swallowed them both." | | 9 | "Books stacked on every surface," | | 10 | "Rory dumped the bag on" | | 11 | "Her heart hammered an obnoxious" | | 12 | "He said it flat, clinical" | | 13 | "A shallow gash across her" | | 14 | "He didn't smile." | | 15 | "That was something, at least." | | 16 | "The old Lucien would have" | | 17 | "Rory grabbed a dish towel" | | 18 | "Ptolemy leapt onto the counter" | | 19 | "She let him." |
| | ratio | 0.898 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 98 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 2 | | matches | | 0 | "Lucien's mismatched eyes, one amber and one black, dropped to the delivery bag in her grip, then climbed back to her face with a slowness that made her skin pri…" | | 1 | "Rory had watched Eva stare at her mobile all through the lunch rush, its screen lighting up with that particular intensity reserved for people you were avoiding…" |
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| 93.75% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 2 | | fancyTags | | 0 | "he breathed (breathe)" | | 1 | "he agreed (agree)" |
| | dialogueSentences | 77 | | tagDensity | 0.104 | | leniency | 0.208 | | rawRatio | 0.25 | | effectiveRatio | 0.052 | |