| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 123 | | tagDensity | 0.089 | | leniency | 0.179 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2285 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 82.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2285 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "calculating" | | 1 | "silence" | | 2 | "weight" | | 3 | "warmth" | | 4 | "flickered" | | 5 | "comforting" | | 6 | "charm" |
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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 | 164 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 164 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 276 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 56 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2285 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 25 | | unquotedAttributions | 1 | | matches | | 0 | "At the door, Elias spoke behind her." |
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| 40.49% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 70 | | wordCount | 1461 | | uniqueNames | 11 | | maxNameDensity | 2.19 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Underground | 1 | | Aurora | 32 | | Vaughan | 1 | | Wales | 1 | | Cardiff | 2 | | Don | 1 | | Prague | 1 | | Elias | 17 | | Silas | 12 |
| | persons | | 0 | "Aurora" | | 1 | "Vaughan" | | 2 | "Elias" | | 3 | "Silas" |
| | places | | 0 | "Raven" | | 1 | "Wales" | | 2 | "Cardiff" | | 3 | "Prague" |
| | globalScore | 0.405 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 106 | | 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 | 2285 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 276 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 214 | | mean | 10.68 | | std | 12.41 | | cv | 1.162 | | sampleLengths | | 0 | 44 | | 1 | 18 | | 2 | 22 | | 3 | 14 | | 4 | 4 | | 5 | 10 | | 6 | 25 | | 7 | 8 | | 8 | 7 | | 9 | 7 | | 10 | 6 | | 11 | 6 | | 12 | 19 | | 13 | 22 | | 14 | 66 | | 15 | 12 | | 16 | 1 | | 17 | 1 | | 18 | 7 | | 19 | 2 | | 20 | 2 | | 21 | 3 | | 22 | 4 | | 23 | 47 | | 24 | 3 | | 25 | 29 | | 26 | 8 | | 27 | 59 | | 28 | 3 | | 29 | 14 | | 30 | 1 | | 31 | 7 | | 32 | 12 | | 33 | 17 | | 34 | 4 | | 35 | 5 | | 36 | 5 | | 37 | 18 | | 38 | 12 | | 39 | 3 | | 40 | 3 | | 41 | 15 | | 42 | 4 | | 43 | 10 | | 44 | 7 | | 45 | 19 | | 46 | 4 | | 47 | 4 | | 48 | 3 | | 49 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 164 | | matches | | 0 | "been banned" | | 1 | "was clipped" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 258 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 276 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1465 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 40 | | adverbRatio | 0.027303754266211604 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0020477815699658703 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 276 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 276 | | mean | 8.28 | | std | 7.93 | | cv | 0.957 | | sampleLengths | | 0 | 11 | | 1 | 33 | | 2 | 7 | | 3 | 11 | | 4 | 22 | | 5 | 14 | | 6 | 4 | | 7 | 10 | | 8 | 4 | | 9 | 8 | | 10 | 13 | | 11 | 8 | | 12 | 7 | | 13 | 7 | | 14 | 6 | | 15 | 6 | | 16 | 19 | | 17 | 6 | | 18 | 16 | | 19 | 43 | | 20 | 8 | | 21 | 15 | | 22 | 12 | | 23 | 1 | | 24 | 1 | | 25 | 7 | | 26 | 2 | | 27 | 2 | | 28 | 3 | | 29 | 4 | | 30 | 6 | | 31 | 22 | | 32 | 8 | | 33 | 11 | | 34 | 3 | | 35 | 29 | | 36 | 8 | | 37 | 12 | | 38 | 13 | | 39 | 5 | | 40 | 7 | | 41 | 22 | | 42 | 3 | | 43 | 14 | | 44 | 1 | | 45 | 7 | | 46 | 12 | | 47 | 17 | | 48 | 4 | | 49 | 5 |
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| 45.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.2536231884057971 | | totalSentences | 276 | | uniqueOpeners | 70 | |
| 69.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 144 | | matches | | 0 | "Then he removed it and" | | 1 | "Then he had said, Don’t" | | 2 | "Instead, he sat there with" |
| | ratio | 0.021 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 144 | | matches | | 0 | "She unzipped the delivery bag" | | 1 | "He turned towards the shelves," | | 2 | "He poured a short measure" | | 3 | "She sat on the stool" | | 4 | "His hair had once fallen" | | 5 | "He wore a dark wool" | | 6 | "He saw her." | | 7 | "He let out a sound" | | 8 | "It died before it reached" | | 9 | "His hazel eyes held still." | | 10 | "His fingers shook once, then" | | 11 | "He had not always done" | | 12 | "He crossed the room, hooked" | | 13 | "He remained outside." | | 14 | "His hands looked older than" | | 15 | "His mouth tightened." | | 16 | "She remembered the final call." | | 17 | "His voice had been distant," | | 18 | "He had asked where she" | | 19 | "She had told him." |
| | ratio | 0.278 | |
| 25.97% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 125 | | totalSentences | 144 | | matches | | 0 | "Rain worked the pavement into" | | 1 | "Aurora stood beneath the green" | | 2 | "The door opened before she" | | 3 | "Silas leaned in the doorway," | | 4 | "Aurora slipped past him." | | 5 | "Water darkened the shoulders of" | | 6 | "She unzipped the delivery bag" | | 7 | "Silas lifted the packet with" | | 8 | "Silas’s mouth twitched beneath his" | | 9 | "He turned towards the shelves," | | 10 | "The bar held its usual" | | 11 | "A low trumpet number leaked" | | 12 | "Smoke had been banned years" | | 13 | "Aurora shrugged out of her" | | 14 | "Silas stopped with a glass" | | 15 | "He poured a short measure" | | 16 | "Aurora carried it to the" | | 17 | "She sat on the stool" | | 18 | "The door opened." | | 19 | "A man stepped in out" |
| | ratio | 0.868 | |
| 34.72% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 144 | | matches | | 0 | "Now it was clipped close" |
| | ratio | 0.007 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 2 | | matches | | 0 | "Aurora had prepared for the polished version of him to deny everything, to offer neat reasons and foreign cities, to act as if the years had happened in a seale…" | | 1 | "There was no trace of the eighteen-year-old who had shared a room with three other students and eaten cereal from a saucepan because he owned no bowls." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 123 | | tagDensity | 0.081 | | leniency | 0.163 | | rawRatio | 0 | | effectiveRatio | 0 | |