| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.318 | | leniency | 0.636 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.26% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1055 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 47.87% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1055 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "flickered" | | 1 | "weight" | | 2 | "unreadable" | | 3 | "flicker" | | 4 | "stomach" | | 5 | "pounding" |
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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 | 89 | | matches | (empty) | |
| 78.65% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 0 | | narrationSentences | 89 | | filterMatches | | 0 | "listen" | | 1 | "feel" | | 2 | "feel feel" |
| | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 103 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 5 | | totalWords | 1052 | | ratio | 0.005 | | matches | | 0 | "The Raven’s Nest" | | 1 | "in trouble" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 955 | | uniqueNames | 8 | | maxNameDensity | 1.68 | | worstName | "Silas" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Carter | 1 | | Rory | 9 | | London | 1 | | Blackwood | 1 | | Silas | 16 | | Eva | 2 | | Aurora | 3 |
| | persons | | 0 | "Raven" | | 1 | "Carter" | | 2 | "Rory" | | 3 | "Blackwood" | | 4 | "Silas" | | 5 | "Eva" | | 6 | "Aurora" |
| | places | | | globalScore | 0.662 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | 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 | 1052 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 103 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 23.91 | | std | 21 | | cv | 0.878 | | sampleLengths | | 0 | 96 | | 1 | 50 | | 2 | 3 | | 3 | 43 | | 4 | 41 | | 5 | 76 | | 6 | 5 | | 7 | 22 | | 8 | 35 | | 9 | 6 | | 10 | 12 | | 11 | 5 | | 12 | 16 | | 13 | 12 | | 14 | 14 | | 15 | 7 | | 16 | 34 | | 17 | 3 | | 18 | 16 | | 19 | 4 | | 20 | 28 | | 21 | 9 | | 22 | 29 | | 23 | 37 | | 24 | 9 | | 25 | 37 | | 26 | 8 | | 27 | 34 | | 28 | 8 | | 29 | 38 | | 30 | 4 | | 31 | 37 | | 32 | 28 | | 33 | 3 | | 34 | 7 | | 35 | 42 | | 36 | 30 | | 37 | 4 | | 38 | 54 | | 39 | 42 | | 40 | 4 | | 41 | 51 | | 42 | 5 | | 43 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 89 | | matches | (empty) | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 177 | | matches | | 0 | "were talking" | | 1 | "were shaking" | | 2 | "were burning" | | 3 | "were burning" | | 4 | "was going" | | 5 | "were being" | | 6 | "was running" | | 7 | "was running" |
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| 87.38% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 103 | | ratio | 0.019 | | matches | | 0 | "Aurora Carter—Rory, to those who knew her—paused outside the entrance, her fingers brushing the scar on her wrist, the one she’d earned from a childhood accident." | | 1 | "A flicker of something passed over his face—amusement, maybe." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 958 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.03549060542797495 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003131524008350731 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 103 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 103 | | mean | 10.21 | | std | 7.69 | | cv | 0.752 | | sampleLengths | | 0 | 26 | | 1 | 24 | | 2 | 26 | | 3 | 6 | | 4 | 14 | | 5 | 24 | | 6 | 3 | | 7 | 3 | | 8 | 20 | | 9 | 3 | | 10 | 13 | | 11 | 14 | | 12 | 8 | | 13 | 8 | | 14 | 12 | | 15 | 18 | | 16 | 3 | | 17 | 5 | | 18 | 3 | | 19 | 9 | | 20 | 5 | | 21 | 20 | | 22 | 42 | | 23 | 5 | | 24 | 5 | | 25 | 15 | | 26 | 2 | | 27 | 23 | | 28 | 4 | | 29 | 5 | | 30 | 3 | | 31 | 6 | | 32 | 9 | | 33 | 3 | | 34 | 5 | | 35 | 9 | | 36 | 7 | | 37 | 6 | | 38 | 6 | | 39 | 4 | | 40 | 7 | | 41 | 3 | | 42 | 7 | | 43 | 12 | | 44 | 15 | | 45 | 7 | | 46 | 3 | | 47 | 13 | | 48 | 3 | | 49 | 4 |
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| 34.47% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.23300970873786409 | | totalSentences | 103 | | uniqueOpeners | 24 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 52.10% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 81 | | matches | | 0 | "She hadn’t been here in" | | 1 | "He didn’t turn." | | 2 | "She stepped inside." | | 3 | "His beard was longer now," | | 4 | "He didn’t smile." | | 5 | "He just waited." | | 6 | "She’d been waiting for this." | | 7 | "She’d been waiting for the" | | 8 | "He poured two fingers of" | | 9 | "She didn’t need the noise." | | 10 | "She needed this." | | 11 | "She laughed, but it was" | | 12 | "He just watched her, his" | | 13 | "His grip was firm, his" | | 14 | "She pulled back, her fingers" | | 15 | "She just stared at them," | | 16 | "She just looked at Silas," | | 17 | "He just looked at her," | | 18 | "He pulled her closer, his" | | 19 | "She remembered the way his" |
| | ratio | 0.42 | |
| 15.56% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 72 | | totalSentences | 81 | | matches | | 0 | "The neon sign of *The" | | 1 | "The air smelled of aged" | | 2 | "Aurora Carter—Rory, to those who" | | 3 | "She hadn’t been here in" | | 4 | "Silas Blackwood stood behind the" | | 5 | "He didn’t turn." | | 6 | "The way his shoulders hunched" | | 7 | "She stepped inside." | | 8 | "The moment the door clicked" | | 9 | "The kind of quiet that" | | 10 | "The kind of quiet that" | | 11 | "The kind of quiet that" | | 12 | "Silas finally turned, his hazel" | | 13 | "His beard was longer now," | | 14 | "He didn’t smile." | | 15 | "He just waited." | | 16 | "Aurora exhaled, the breath curling" | | 17 | "She’d been waiting for this." | | 18 | "She’d been waiting for the" | | 19 | "Silas didn’t answer right away." |
| | ratio | 0.889 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 69.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 4 | | matches | | 0 | "The air smelled of aged whiskey and damp wool, the kind of scent that clung to a place long after its last customer left." | | 1 | "She’d been waiting for the way his eyes would burn into hers like they used to, like they had when they were younger, when they were still two people who could …" | | 2 | "Rory’s breath came fast, her fingers digging into the door handle, her heart pounding in her chest." | | 3 | "The air smelled of aged whiskey and damp wool, the kind of scent that clung to a place long after its last customer left." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.318 | | leniency | 0.636 | | rawRatio | 0 | | effectiveRatio | 0 | |