| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 119 | | tagDensity | 0.109 | | leniency | 0.218 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1994 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 89.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1994 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "footsteps" | | 1 | "grave" | | 2 | "remarkable" | | 3 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 126 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 126 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 232 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1994 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 56.88% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 69 | | wordCount | 1235 | | uniqueNames | 9 | | maxNameDensity | 1.86 | | worstName | "Aurora" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Aurora" | | discoveredNames | | Moreau | 1 | | Eva | 12 | | Ptolemy | 5 | | Aurora | 23 | | Lucien | 22 | | Silas | 3 | | East | 1 | | London | 1 | | Avaros | 1 |
| | persons | | 0 | "Moreau" | | 1 | "Eva" | | 2 | "Ptolemy" | | 3 | "Aurora" | | 4 | "Lucien" | | 5 | "Silas" |
| | places | | 0 | "East" | | 1 | "London" | | 2 | "Avaros" |
| | globalScore | 0.569 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 99 | | 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 | 1994 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 232 | | matches | | 0 | "spent that night" | | 1 | "saw that the" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 139 | | mean | 14.35 | | std | 14.82 | | cv | 1.033 | | sampleLengths | | 0 | 10 | | 1 | 41 | | 2 | 26 | | 3 | 3 | | 4 | 5 | | 5 | 5 | | 6 | 30 | | 7 | 5 | | 8 | 5 | | 9 | 52 | | 10 | 4 | | 11 | 4 | | 12 | 6 | | 13 | 5 | | 14 | 13 | | 15 | 61 | | 16 | 34 | | 17 | 12 | | 18 | 48 | | 19 | 6 | | 20 | 6 | | 21 | 64 | | 22 | 4 | | 23 | 2 | | 24 | 8 | | 25 | 31 | | 26 | 2 | | 27 | 1 | | 28 | 2 | | 29 | 4 | | 30 | 11 | | 31 | 43 | | 32 | 26 | | 33 | 2 | | 34 | 7 | | 35 | 9 | | 36 | 6 | | 37 | 49 | | 38 | 5 | | 39 | 35 | | 40 | 4 | | 41 | 12 | | 42 | 9 | | 43 | 4 | | 44 | 7 | | 45 | 8 | | 46 | 2 | | 47 | 41 | | 48 | 25 | | 49 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 126 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 212 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 3 | | flaggedSentences | 3 | | totalSentences | 232 | | ratio | 0.013 | | matches | | 0 | "His amber eye held hers; the black one caught the landing bulb without giving it back." | | 1 | "The third caught halfway; she lifted the handle until it slid home." | | 2 | "Her wrist brushed his skin; the little scar grazed the open edge of his shirt." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1239 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.01775625504439064 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0008071025020177562 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 232 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 232 | | mean | 8.59 | | std | 5.74 | | cv | 0.667 | | sampleLengths | | 0 | 10 | | 1 | 17 | | 2 | 8 | | 3 | 16 | | 4 | 15 | | 5 | 11 | | 6 | 3 | | 7 | 5 | | 8 | 5 | | 9 | 18 | | 10 | 3 | | 11 | 9 | | 12 | 5 | | 13 | 5 | | 14 | 15 | | 15 | 8 | | 16 | 18 | | 17 | 11 | | 18 | 4 | | 19 | 4 | | 20 | 6 | | 21 | 5 | | 22 | 9 | | 23 | 4 | | 24 | 8 | | 25 | 16 | | 26 | 18 | | 27 | 19 | | 28 | 7 | | 29 | 15 | | 30 | 12 | | 31 | 12 | | 32 | 5 | | 33 | 23 | | 34 | 8 | | 35 | 12 | | 36 | 6 | | 37 | 6 | | 38 | 7 | | 39 | 11 | | 40 | 31 | | 41 | 15 | | 42 | 4 | | 43 | 2 | | 44 | 8 | | 45 | 8 | | 46 | 16 | | 47 | 7 | | 48 | 2 | | 49 | 1 |
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| 44.83% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.25 | | totalSentences | 232 | | uniqueOpeners | 58 | |
| 27.78% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 120 | | matches | | 0 | "Instead, she turned her hand" |
| | ratio | 0.008 | |
| 76.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 43 | | totalSentences | 120 | | matches | | 0 | "He held his ivory-handled cane" | | 1 | "She looked at the wet" | | 2 | "His amber eye held hers;" | | 3 | "She remembered those eyes across" | | 4 | "She remembered them in the" | | 5 | "He stopped on the strip" | | 6 | "he told her" | | 7 | "He looked down, then moved" | | 8 | "He unbuttoned the jacket and" | | 9 | "She took the jacket from" | | 10 | "She withdrew her hand." | | 11 | "He gave her enough to" | | 12 | "He glanced at the books" | | 13 | "She set the mug down" | | 14 | "She had spent that night" | | 15 | "His plain answer left her" | | 16 | "She gripped the edge of" | | 17 | "His face pinched before he" | | 18 | "He took the chair beside" | | 19 | "She carried it over and" |
| | ratio | 0.358 | |
| 10.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 108 | | totalSentences | 120 | | matches | | 0 | "Aurora opened the door as" | | 1 | "Lucien Moreau stood beneath the" | | 2 | "He held his ivory-handled cane" | | 3 | "A drop slid from his" | | 4 | "None of it survived the" | | 5 | "Lucien looked down." | | 6 | "The cat withdrew with a" | | 7 | "Aurora told him" | | 8 | "The curry house below sent" | | 9 | "Aurora kept one hand on" | | 10 | "The little crescent scar caught" | | 11 | "She looked at the wet" | | 12 | "Lucien rested both hands on" | | 13 | "His amber eye held hers;" | | 14 | "She remembered those eyes across" | | 15 | "She remembered them in the" | | 16 | "A door opened on the" | | 17 | "Someone called an apology into" | | 18 | "Aurora shut the door, slipped" | | 19 | "Lucien stepped across the threshold." |
| | ratio | 0.9 | |
| 41.67% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 120 | | matches | | 0 | "Now he stood with rain" |
| | ratio | 0.008 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 1 | | matches | | 0 | "Lucien had once walked into her flat above Silas’s bar as though he belonged there, had set his cane beside her chipped kitchen table and known which cupboard h…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 2 | | fancyTags | | 0 | "She pressed (press)" | | 1 | "she added (add)" |
| | dialogueSentences | 119 | | tagDensity | 0.076 | | leniency | 0.151 | | rawRatio | 0.222 | | effectiveRatio | 0.034 | |