| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 115 | | tagDensity | 0.191 | | leniency | 0.383 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.30% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2136 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "sharply" | | 1 | "carefully" | | 2 | "really" | | 3 | "quickly" | | 4 | "very" |
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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) | |
| 76.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2136 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "gloom" | | 1 | "eyebrow" | | 2 | "could feel" | | 3 | "unreadable" | | 4 | "familiar" | | 5 | "sense of" | | 6 | "charm" | | 7 | "silence" |
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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 | 154 | | matches | (empty) | |
| 77.92% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 6 | | narrationSentences | 154 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 247 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2136 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 31 | | unquotedAttributions | 1 | | matches | | 0 | "When Eva finished, Rory asked what Mara looked like." |
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| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 110 | | wordCount | 1514 | | uniqueNames | 10 | | maxNameDensity | 3.24 | | worstName | "Rory" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 49 | | Raven | 1 | | Nest | 1 | | Eva | 45 | | London | 1 | | Come | 1 | | Golden | 1 | | Empress | 1 | | Mara | 2 | | Silas | 8 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Eva" | | 3 | "Mara" | | 4 | "Silas" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 97.37% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 95 | | glossingSentenceCount | 2 | | matches | | 0 | "tiredness that seemed to have become part of her posture" | | 1 | "looked like" |
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| 12.73% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 4 | | per1kWords | 1.873 | | wordCount | 2136 | | matches | | 0 | "Not in the usual arithmetic of years, but as if some private weather had passed over her" | | 1 | "not a wall exactly, but a stack of unopened letters" | | 2 | "not in the short hair or the coat, but in the way Eva had begun speaking as if every sentence neede" | | 3 | "not the woman she remembered, but it was not a stranger either" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 4 | | totalSentences | 247 | | matches | | 0 | "said that she" | | 1 | "recognized that stubbornness" | | 2 | "insisted that rain" | | 3 | "pretended that an" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 138 | | mean | 15.48 | | std | 19.02 | | cv | 1.229 | | sampleLengths | | 0 | 41 | | 1 | 52 | | 2 | 4 | | 3 | 35 | | 4 | 3 | | 5 | 7 | | 6 | 10 | | 7 | 1 | | 8 | 56 | | 9 | 5 | | 10 | 23 | | 11 | 5 | | 12 | 93 | | 13 | 3 | | 14 | 21 | | 15 | 1 | | 16 | 18 | | 17 | 10 | | 18 | 11 | | 19 | 30 | | 20 | 3 | | 21 | 2 | | 22 | 4 | | 23 | 2 | | 24 | 49 | | 25 | 4 | | 26 | 2 | | 27 | 9 | | 28 | 8 | | 29 | 3 | | 30 | 4 | | 31 | 50 | | 32 | 6 | | 33 | 1 | | 34 | 10 | | 35 | 11 | | 36 | 6 | | 37 | 13 | | 38 | 25 | | 39 | 2 | | 40 | 4 | | 41 | 3 | | 42 | 11 | | 43 | 8 | | 44 | 36 | | 45 | 9 | | 46 | 3 | | 47 | 2 | | 48 | 94 | | 49 | 10 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 154 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 282 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 247 | | ratio | 0.004 | | matches | | 0 | "It had not erased the old language; it had made them speak it with accents." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1516 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 51 | | adverbRatio | 0.033641160949868076 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.008575197889182058 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 247 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 247 | | mean | 8.65 | | std | 7.52 | | cv | 0.87 | | sampleLengths | | 0 | 18 | | 1 | 23 | | 2 | 6 | | 3 | 14 | | 4 | 16 | | 5 | 16 | | 6 | 4 | | 7 | 8 | | 8 | 8 | | 9 | 19 | | 10 | 3 | | 11 | 7 | | 12 | 7 | | 13 | 3 | | 14 | 1 | | 15 | 21 | | 16 | 9 | | 17 | 11 | | 18 | 15 | | 19 | 5 | | 20 | 9 | | 21 | 4 | | 22 | 10 | | 23 | 5 | | 24 | 7 | | 25 | 23 | | 26 | 7 | | 27 | 15 | | 28 | 14 | | 29 | 3 | | 30 | 2 | | 31 | 22 | | 32 | 3 | | 33 | 21 | | 34 | 1 | | 35 | 5 | | 36 | 3 | | 37 | 10 | | 38 | 4 | | 39 | 6 | | 40 | 5 | | 41 | 6 | | 42 | 17 | | 43 | 8 | | 44 | 5 | | 45 | 3 | | 46 | 2 | | 47 | 4 | | 48 | 2 | | 49 | 10 |
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| 43.52% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.242914979757085 | | totalSentences | 247 | | uniqueOpeners | 60 | |
| 51.28% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 130 | | matches | | 0 | "Then, three days before Rory’s" | | 1 | "Then not at all." |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 130 | | matches | | 0 | "She left her delivery bag" | | 1 | "Her black hair clung damply" | | 2 | "She sat at the corner" | | 3 | "She wrapped both hands around" | | 4 | "Her coat was expensive and" | | 5 | "She looked thinner." | | 6 | "He said nothing." | | 7 | "She looked back at Eva." | | 8 | "She set her umbrella down" | | 9 | "They were still narrow, the" | | 10 | "He gave Rory a small," | | 11 | "It was a familiar sound," | | 12 | "She had carried the absence" | | 13 | "You can stay with me." | | 14 | "We’ll sort it out." | | 15 | "It was the answer people" | | 16 | "It was the first time" | | 17 | "She imagined a small girl" | | 18 | "She imagined all the years" | | 19 | "Her crescent scar showed pale" |
| | ratio | 0.223 | |
| 33.08% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 111 | | totalSentences | 130 | | matches | | 0 | "The rain had followed Rory" | | 1 | "She left her delivery bag" | | 2 | "The Raven’s Nest was nearly" | | 3 | "The green neon sign outside" | | 4 | "Silas stood behind the bar," | | 5 | "Rory shook rain from her" | | 6 | "Her black hair clung damply" | | 7 | "Silas set a glass on" | | 8 | "She sat at the corner" | | 9 | "Silas poured her a measure" | | 10 | "She wrapped both hands around" | | 11 | "The door opened behind her." | | 12 | "A gust of wet air" | | 13 | "Someone shook an umbrella." | | 14 | "Rory glanced over, expecting a" | | 15 | "Eva stood on the threshold." | | 16 | "Rory recognized the angle of" | | 17 | "Eva’s hair, once a dark" | | 18 | "Her coat was expensive and" | | 19 | "She looked thinner." |
| | ratio | 0.854 | |
| 38.46% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 130 | | matches | | 0 | "Now she sat beside Rory" |
| | ratio | 0.008 | |
| 59.52% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 7 | | matches | | 0 | "Not in the usual arithmetic of years, but as if some private weather had passed over her and left the landscape altered." | | 1 | "It was a familiar sound, but thinner than Rory remembered, as if it had been used sparingly." | | 2 | "Eva had sent the message that brought her here: Come." | | 3 | "Rory remembered it from school corridors and bus stops, from Eva planting herself between Rory and anyone who thought a cruel joke could pass for charm." | | 4 | "But Eva was looking at her with the careful attention of someone who had finally stopped rehearsing a defense." | | 5 | "There it was: the change Rory had sensed, not in the short hair or the coat, but in the way Eva had begun speaking as if every sentence needed to be lifted over…" | | 6 | "Eva smiled, and for a moment there she was: the girl who used to lie beside Rory on the grass behind the school and read horoscopes aloud in a solemn voice, inv…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 1 | | fancyTags | | 0 | "Rory continued (continue)" |
| | dialogueSentences | 115 | | tagDensity | 0.139 | | leniency | 0.278 | | rawRatio | 0.063 | | effectiveRatio | 0.017 | |