| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said slowly [slowly]" |
| | dialogueSentences | 46 | | tagDensity | 0.391 | | leniency | 0.783 | | rawRatio | 0.056 | | effectiveRatio | 0.043 | |
| 87.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1176 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "very" | | 1 | "slowly" | | 2 | "suddenly" |
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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) | |
| 91.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1176 | | totalAiIsms | 2 | | found | | | highlights | | |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 59 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 59 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 87 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1183 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 610 | | uniqueNames | 7 | | maxNameDensity | 0.98 | | worstName | "Lucien" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Lucien" | | discoveredNames | | Lucien | 6 | | Ptolemy | 5 | | Eva | 2 | | Avarosi | 1 | | Wrong | 1 | | Swallowed | 1 | | Rory | 2 |
| | persons | | 0 | "Lucien" | | 1 | "Ptolemy" | | 2 | "Eva" | | 3 | "Rory" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 34 | | 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 | 1183 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 87 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 27.51 | | std | 23.09 | | cv | 0.839 | | sampleLengths | | 0 | 15 | | 1 | 32 | | 2 | 1 | | 3 | 75 | | 4 | 5 | | 5 | 6 | | 6 | 42 | | 7 | 3 | | 8 | 44 | | 9 | 3 | | 10 | 49 | | 11 | 53 | | 12 | 30 | | 13 | 42 | | 14 | 3 | | 15 | 2 | | 16 | 50 | | 17 | 4 | | 18 | 54 | | 19 | 4 | | 20 | 1 | | 21 | 14 | | 22 | 15 | | 23 | 55 | | 24 | 39 | | 25 | 14 | | 26 | 49 | | 27 | 11 | | 28 | 31 | | 29 | 78 | | 30 | 56 | | 31 | 23 | | 32 | 36 | | 33 | 5 | | 34 | 30 | | 35 | 7 | | 36 | 5 | | 37 | 6 | | 38 | 73 | | 39 | 26 | | 40 | 8 | | 41 | 66 | | 42 | 18 |
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| 99.32% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 59 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 105 | | matches | | |
| 11.49% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 87 | | ratio | 0.046 | | matches | | 0 | "The charcoal suit had a crease where a pocket should've been smooth — he'd been carrying something there and removed it." | | 1 | "Not his height, not the suit, not the cane — the way he occupied every room like he was cataloguing it for future leverage, and the way that cataloguing stopped entirely when he looked at her." | | 2 | "\"I wrote half the marginalia Eva copied.\" He said it flatly, without pride, and studied her wrist — the crescent scar, the one she'd gotten the night they ended." | | 3 | "Genuine surprise — she'd earned maybe three of those in two years." |
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| 91.68% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 606 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.04950495049504951 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.01485148514851485 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 87 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 87 | | mean | 13.6 | | std | 12.19 | | cv | 0.896 | | sampleLengths | | 0 | 15 | | 1 | 18 | | 2 | 7 | | 3 | 7 | | 4 | 1 | | 5 | 19 | | 6 | 21 | | 7 | 16 | | 8 | 19 | | 9 | 5 | | 10 | 6 | | 11 | 7 | | 12 | 35 | | 13 | 3 | | 14 | 38 | | 15 | 6 | | 16 | 3 | | 17 | 41 | | 18 | 8 | | 19 | 11 | | 20 | 6 | | 21 | 36 | | 22 | 5 | | 23 | 20 | | 24 | 5 | | 25 | 27 | | 26 | 2 | | 27 | 13 | | 28 | 3 | | 29 | 2 | | 30 | 29 | | 31 | 6 | | 32 | 2 | | 33 | 3 | | 34 | 10 | | 35 | 4 | | 36 | 4 | | 37 | 18 | | 38 | 32 | | 39 | 4 | | 40 | 1 | | 41 | 14 | | 42 | 3 | | 43 | 12 | | 44 | 18 | | 45 | 36 | | 46 | 1 | | 47 | 20 | | 48 | 19 | | 49 | 6 |
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| 69.35% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4367816091954023 | | totalSentences | 87 | | uniqueOpeners | 38 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 51 | | matches | (empty) | | ratio | 0 | |
| 0.39% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 51 | | matches | | 0 | "He held an umbrella despite" | | 1 | "His cane tapped once against" | | 2 | "She unlatched the chain and" | | 3 | "He straightened, and his mismatched" | | 4 | "He moved a stack of" | | 5 | "She sat on the couch." | | 6 | "He took the armchair across" | | 7 | "She gestured at the table," | | 8 | "She saw him register it," | | 9 | "He said it flatly, without" | | 10 | "She covered it with her" | | 11 | "His jaw tightened." | | 12 | "she repeated, quieter" | | 13 | "His eyebrows lifted." | | 14 | "She pulled her sleeve back" | | 15 | "He said it like a" | | 16 | "Her voice cracked" | | 17 | "She hated it." | | 18 | "She pushed through." | | 19 | "He set the cat aside" |
| | ratio | 0.549 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 51 | | matches | | 0 | "The third deadbolt gave with" | | 1 | "Eva's tabby cat beat her" | | 2 | "Ptolemy had a talent for" | | 3 | "Rory looked past him and" | | 4 | "He held an umbrella despite" | | 5 | "The charcoal suit had a" | | 6 | "His cane tapped once against" | | 7 | "She unlatched the chain and" | | 8 | "Ptolemy wound between Lucien's ankles" | | 9 | "He straightened, and his mismatched" | | 10 | "He moved a stack of" | | 11 | "The flat was small, and" | | 12 | "That had always been the" | | 13 | "She sat on the couch." | | 14 | "He took the armchair across" | | 15 | "She gestured at the table," | | 16 | "She saw him register it," | | 17 | "He said it flatly, without" | | 18 | "She covered it with her" | | 19 | "His jaw tightened." |
| | ratio | 0.922 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 51 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 15 | | technicalSentenceCount | 3 | | matches | | 0 | "Ptolemy wound between Lucien's ankles the moment he crossed the threshold, the traitor, and Lucien bent to scratch behind his ears with the unhurried ease of a …" | | 1 | "Not his height, not the suit, not the cane — the way he occupied every room like he was cataloguing it for future leverage, and the way that cataloguing stopped…" | | 2 | "Amber eye, black eye, both of them wide open and unarmored in a way that cost him something visible." |
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| 97.22% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 1 | | matches | | 0 | "she repeated, quieter," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 2 | | fancyTags | | 0 | "He moved (move)" | | 1 | "she repeated (repeat)" |
| | dialogueSentences | 46 | | tagDensity | 0.152 | | leniency | 0.304 | | rawRatio | 0.286 | | effectiveRatio | 0.087 | |