| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 67 | | tagDensity | 0.149 | | leniency | 0.299 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1243 | | 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) | |
| 87.93% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1243 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "weight" | | 1 | "eyebrow" | | 2 | "flickered" |
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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 | 102 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 102 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 159 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1243 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 72 | | wordCount | 884 | | uniqueNames | 11 | | maxNameDensity | 3.17 | | worstName | "Silas" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Thomas" | | discoveredNames | | Raven | 1 | | Nest | 2 | | Carter | 1 | | Golden | 1 | | Empress | 1 | | Blackwood | 1 | | Aurora | 10 | | Silas | 28 | | Thomas | 25 | | Prague | 1 | | Cardiff | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Blackwood" | | 4 | "Aurora" | | 5 | "Silas" | | 6 | "Thomas" |
| | places | | 0 | "Golden" | | 1 | "Prague" | | 2 | "Cardiff" |
| | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | 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 | 1243 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 159 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 85 | | mean | 14.62 | | std | 16.79 | | cv | 1.148 | | sampleLengths | | 0 | 79 | | 1 | 3 | | 2 | 81 | | 3 | 4 | | 4 | 15 | | 5 | 9 | | 6 | 16 | | 7 | 47 | | 8 | 4 | | 9 | 43 | | 10 | 8 | | 11 | 3 | | 12 | 19 | | 13 | 48 | | 14 | 13 | | 15 | 4 | | 16 | 2 | | 17 | 2 | | 18 | 29 | | 19 | 11 | | 20 | 14 | | 21 | 4 | | 22 | 4 | | 23 | 20 | | 24 | 7 | | 25 | 3 | | 26 | 3 | | 27 | 3 | | 28 | 10 | | 29 | 19 | | 30 | 9 | | 31 | 46 | | 32 | 31 | | 33 | 8 | | 34 | 4 | | 35 | 7 | | 36 | 8 | | 37 | 2 | | 38 | 6 | | 39 | 29 | | 40 | 2 | | 41 | 10 | | 42 | 33 | | 43 | 5 | | 44 | 6 | | 45 | 22 | | 46 | 52 | | 47 | 6 | | 48 | 1 | | 49 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 102 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 152 | | matches | | 0 | "was watching" | | 1 | "was watching" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 159 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 893 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 23 | | adverbRatio | 0.025755879059350503 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0022396416573348264 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 159 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 159 | | mean | 7.82 | | std | 6.34 | | cv | 0.811 | | sampleLengths | | 0 | 15 | | 1 | 36 | | 2 | 9 | | 3 | 19 | | 4 | 3 | | 5 | 19 | | 6 | 12 | | 7 | 7 | | 8 | 24 | | 9 | 19 | | 10 | 4 | | 11 | 5 | | 12 | 10 | | 13 | 9 | | 14 | 16 | | 15 | 11 | | 16 | 21 | | 17 | 15 | | 18 | 4 | | 19 | 8 | | 20 | 20 | | 21 | 10 | | 22 | 5 | | 23 | 8 | | 24 | 3 | | 25 | 6 | | 26 | 12 | | 27 | 1 | | 28 | 12 | | 29 | 27 | | 30 | 3 | | 31 | 6 | | 32 | 9 | | 33 | 4 | | 34 | 4 | | 35 | 2 | | 36 | 2 | | 37 | 2 | | 38 | 20 | | 39 | 2 | | 40 | 5 | | 41 | 11 | | 42 | 5 | | 43 | 6 | | 44 | 3 | | 45 | 4 | | 46 | 4 | | 47 | 7 | | 48 | 5 | | 49 | 8 |
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| 46.23% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.1949685534591195 | | totalSentences | 159 | | uniqueOpeners | 31 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 89 | | matches | (empty) | | ratio | 0 | |
| 85.17% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 89 | | matches | | 0 | "She was twenty-five, five foot" | | 1 | "His grey-streaked auburn hair was" | | 2 | "He did not look up" | | 3 | "He set the glass down" | | 4 | "His left leg gave a" | | 5 | "He had not changed since" | | 6 | "He was older than Silas," | | 7 | "He stopped inside the doorway" | | 8 | "His eyes found Silas first." | | 9 | "He looked at the maps," | | 10 | "She had seen Silas with" | | 11 | "He did not offer a" | | 12 | "He kept his hands in" | | 13 | "She had told Silas once," | | 14 | "He had not asked more." | | 15 | "He had listened." | | 16 | "He looked away." | | 17 | "He set it down hard." | | 18 | "She had never used it." | | 19 | "She had only ever heard" |
| | ratio | 0.337 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 89 | | totalSentences | 89 | | matches | | 0 | "The green neon sign above" | | 1 | "Aurora Carter pushed through the" | | 2 | "Rain had slicked her black" | | 3 | "She was twenty-five, five foot" | | 4 | "The bell jingled." | | 5 | "Silas Blackwood stood behind the" | | 6 | "His grey-streaked auburn hair was" | | 7 | "He did not look up" | | 8 | "The walls around them were" | | 9 | "A draft moved the sign" | | 10 | "Aurora set the bag down." | | 11 | "He set the glass down" | | 12 | "His left leg gave a" | | 13 | "He had not changed since" | | 14 | "The door opened again." | | 15 | "A man came in, coat" | | 16 | "He was older than Silas," | | 17 | "He stopped inside the doorway" | | 18 | "His eyes found Silas first." | | 19 | "Silas froze with his hand" |
| | ratio | 1 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 89 | | matches | (empty) | | ratio | 0 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 3 | | matches | | 0 | "The walls around them were covered in old maps and black-and-white photographs, the kind that made the dim room feel smaller than it was." | | 1 | "He was older than Silas, maybe sixty-five, with a thin face and a scar that pulled at his left eyebrow." | | 2 | "Thomas looked at her then, a quick glance, and his gaze lingered on the black hair that fell past her shoulders, on the bright blue of her eyes." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 67 | | tagDensity | 0.149 | | leniency | 0.299 | | rawRatio | 0 | | effectiveRatio | 0 | |