| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 54 | | tagDensity | 0.148 | | leniency | 0.296 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 81.41% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1076 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "really" | | 1 | "very" | | 2 | "quickly" |
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| 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) | |
| 81.41% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1076 | | totalAiIsms | 4 | | found | | | highlights | | |
| 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 | 52 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 52 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1076 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.55% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 687 | | uniqueNames | 10 | | maxNameDensity | 2.33 | | worstName | "Maeve" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Maeve" | | discoveredNames | | Rory | 9 | | Donnelly | 1 | | Maeve | 16 | | Raven | 1 | | Nest | 1 | | Silas | 5 | | Cathays | 1 | | Golden | 1 | | Empress | 1 | | Bakelite | 1 |
| | persons | | 0 | "Rory" | | 1 | "Donnelly" | | 2 | "Maeve" | | 3 | "Nest" | | 4 | "Silas" |
| | places | | 0 | "Raven" | | 1 | "Cathays" | | 2 | "Golden" |
| | globalScore | 0.336 | | windowScore | 0.5 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 36 | | glossingSentenceCount | 3 | | matches | | 0 | "felt like the only mercy the night had" | | 1 | "looked like the cover of a magazine nobod" | | 2 | "something like understanding, or the beginni" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.929 | | wordCount | 1076 | | matches | | 0 | "not quickly, he never moved quickly, but with" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 64 | | mean | 16.81 | | std | 19.98 | | cv | 1.188 | | sampleLengths | | 0 | 19 | | 1 | 2 | | 2 | 51 | | 3 | 80 | | 4 | 1 | | 5 | 29 | | 6 | 59 | | 7 | 28 | | 8 | 4 | | 9 | 1 | | 10 | 9 | | 11 | 1 | | 12 | 6 | | 13 | 2 | | 14 | 37 | | 15 | 9 | | 16 | 7 | | 17 | 11 | | 18 | 63 | | 19 | 4 | | 20 | 9 | | 21 | 1 | | 22 | 5 | | 23 | 4 | | 24 | 7 | | 25 | 2 | | 26 | 86 | | 27 | 6 | | 28 | 11 | | 29 | 7 | | 30 | 51 | | 31 | 38 | | 32 | 5 | | 33 | 1 | | 34 | 3 | | 35 | 50 | | 36 | 25 | | 37 | 8 | | 38 | 3 | | 39 | 41 | | 40 | 3 | | 41 | 4 | | 42 | 11 | | 43 | 1 | | 44 | 27 | | 45 | 5 | | 46 | 1 | | 47 | 3 | | 48 | 11 | | 49 | 22 |
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| 78.27% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 52 | | matches | | 0 | "were studded" | | 1 | "was unchanged" | | 2 | "being asked" | | 3 | "being asked" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 115 | | matches | | 0 | "was deciding" | | 1 | "was tasting" | | 2 | "was lying" | | 3 | "was holding" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 98 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 689 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.030478955007256895 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.00725689404934688 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 10.98 | | std | 10.95 | | cv | 0.998 | | sampleLengths | | 0 | 19 | | 1 | 2 | | 2 | 7 | | 3 | 20 | | 4 | 24 | | 5 | 4 | | 6 | 5 | | 7 | 40 | | 8 | 7 | | 9 | 9 | | 10 | 15 | | 11 | 1 | | 12 | 25 | | 13 | 4 | | 14 | 21 | | 15 | 18 | | 16 | 20 | | 17 | 7 | | 18 | 21 | | 19 | 4 | | 20 | 1 | | 21 | 7 | | 22 | 2 | | 23 | 1 | | 24 | 6 | | 25 | 2 | | 26 | 20 | | 27 | 17 | | 28 | 9 | | 29 | 7 | | 30 | 6 | | 31 | 5 | | 32 | 5 | | 33 | 37 | | 34 | 4 | | 35 | 2 | | 36 | 15 | | 37 | 4 | | 38 | 9 | | 39 | 1 | | 40 | 5 | | 41 | 4 | | 42 | 6 | | 43 | 1 | | 44 | 2 | | 45 | 34 | | 46 | 52 | | 47 | 6 | | 48 | 11 | | 49 | 7 |
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| 68.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.46938775510204084 | | totalSentences | 98 | | uniqueOpeners | 46 | |
| 72.46% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 46 | | matches | | 0 | "Somewhere behind her, Silas had" |
| | ratio | 0.022 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 46 | | matches | | 0 | "She knew the voice before" | | 1 | "Her ears were studded with" | | 2 | "Her nails were the same" | | 3 | "She looked like the cover" | | 4 | "He had the instinct of" | | 5 | "He moved one stool down," | | 6 | "She lifted her wine" | | 7 | "She took a sip, a" | | 8 | "He remembered everything, Silas, and" | | 9 | "She kept her face flat." | | 10 | "He crossed to the far" |
| | ratio | 0.239 | |
| 36.09% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 39 | | totalSentences | 46 | | matches | | 0 | "The glass slipped from Rory's" | | 1 | "She knew the voice before" | | 2 | "Maeve Donnelly stood two stools" | | 3 | "This Maeve wore a camel" | | 4 | "Her ears were studded with" | | 5 | "Her nails were the same" | | 6 | "She looked like the cover" | | 7 | "Maeve laughed, and that, at" | | 8 | "He had the instinct of" | | 9 | "He moved one stool down," | | 10 | "Maeve slid onto the stool" | | 11 | "The perfume hit first, something" | | 12 | "She lifted her wine" | | 13 | "Maeve's mouth did the thing" | | 14 | "A small pinch at the" | | 15 | "The wine glass paused halfway" | | 16 | "Rory looked at her properly." | | 17 | "The coat, yes, and the" | | 18 | "Platinum, unshowy, the kind of" | | 19 | "Maeve's laugh again, thinner this" |
| | ratio | 0.848 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 46 | | matches | (empty) | | ratio | 0 | |
| 12.99% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 4 | | matches | | 0 | "This Maeve wore a camel coat that cost more than a month of deliveries, and her hair had gone from the tangle of copper wire Rory used to braid in lectures to s…" | | 1 | "He moved one stool down, polishing a glass that didn't need polishing, placing himself within earshot without quite being there." | | 2 | "Platinum, unshowy, the kind of unshowy that cost a great deal of money to achieve." | | 3 | "Silas was moving now, not quickly, he never moved quickly, but with that quiet reassignment of weight that meant he'd decided something." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 54 | | tagDensity | 0.074 | | leniency | 0.148 | | rawRatio | 0.25 | | effectiveRatio | 0.037 | |