| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said softly [softly]" |
| | dialogueSentences | 65 | | tagDensity | 0.277 | | leniency | 0.554 | | rawRatio | 0.056 | | effectiveRatio | 0.031 | |
| 81.77% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1371 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "softly" | | 1 | "really" | | 2 | "slightly" | | 3 | "slowly" |
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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) | |
| 59.88% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1371 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "warmth" | | 1 | "methodical" | | 2 | "flicker" | | 3 | "familiar" | | 4 | "weight" | | 5 | "charm" | | 6 | "silence" | | 7 | "trembled" |
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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 | 127 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 127 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 172 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 60 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 8 | | markdownWords | 28 | | totalWords | 1355 | | ratio | 0.021 | | matches | | 0 | "Laila" | | 1 | "months" | | 2 | "MI6" | | 3 | "another" | | 4 | "could" | | 5 | "For Laila, who walks like the sea rolls—quiet, but never still." | | 6 | "If I forget your face, let this be the map back." | | 7 | "sorry" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 29 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 847 | | uniqueNames | 15 | | maxNameDensity | 1.18 | | worstName | "Ethan" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Ethan" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Chet | 1 | | Baker | 1 | | Carter | 1 | | Silas | 8 | | Cardiff | 1 | | Evan | 3 | | Vale | 1 | | Barry | 1 | | Island | 1 | | Ethan | 10 | | Aurora | 6 | | Laila | 2 | | Knew | 4 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Chet" | | 3 | "Baker" | | 4 | "Carter" | | 5 | "Silas" | | 6 | "Evan" | | 7 | "Vale" | | 8 | "Ethan" | | 9 | "Aurora" | | 10 | "Laila" |
| | places | | 0 | "Cardiff" | | 1 | "Barry" | | 2 | "Island" |
| | globalScore | 0.91 | | windowScore | 0.5 | |
| 98.98% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared, silent offering a glass of bourbon" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1355 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 172 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 86 | | mean | 15.76 | | std | 16.07 | | cv | 1.02 | | sampleLengths | | 0 | 78 | | 1 | 65 | | 2 | 50 | | 3 | 4 | | 4 | 27 | | 5 | 62 | | 6 | 11 | | 7 | 3 | | 8 | 5 | | 9 | 59 | | 10 | 9 | | 11 | 23 | | 12 | 2 | | 13 | 1 | | 14 | 12 | | 15 | 11 | | 16 | 22 | | 17 | 3 | | 18 | 32 | | 19 | 6 | | 20 | 12 | | 21 | 5 | | 22 | 12 | | 23 | 7 | | 24 | 5 | | 25 | 69 | | 26 | 6 | | 27 | 5 | | 28 | 9 | | 29 | 4 | | 30 | 5 | | 31 | 17 | | 32 | 5 | | 33 | 22 | | 34 | 3 | | 35 | 15 | | 36 | 4 | | 37 | 8 | | 38 | 6 | | 39 | 12 | | 40 | 6 | | 41 | 39 | | 42 | 17 | | 43 | 21 | | 44 | 9 | | 45 | 29 | | 46 | 17 | | 47 | 17 | | 48 | 8 | | 49 | 7 |
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| 94.21% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 127 | | matches | | 0 | "being seen" | | 1 | "was gone" | | 2 | "was buried" | | 3 | "being asked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 168 | | matches | | 0 | "was thinking" | | 1 | "was looking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 172 | | ratio | 0.052 | | matches | | 0 | "A jazz trio played low and smoky on the stereo—Chet Baker, something slow, something aching." | | 1 | "Rain, cold, traffic—the city was punishing anyone still stupid enough to ride through it." | | 2 | "Not surprise, never that with Silas—more like confirmation." | | 3 | "A scar—thin, pale—ran along his jawline, something new." | | 4 | "Not until he turned, and his eyes skimmed the room like he was looking for someone—or avoiding." | | 5 | "There was a weight to his movements now, a deliberation—the kind you picked up carrying things no one talked about." | | 6 | "She looked at him—really looked." | | 7 | "The boy who used to toss pebbles at her window at midnight, who’d sneak her out to the cliffs above Barry Island to watch the sun rise, who’d kissed her for the first time behind the library and called her *Laila* like it was a secret only he knew—that boy was buried somewhere beneath the lines around his eyes." | | 8 | "> *For Laila, who walks like the sea rolls—quiet, but never still.*" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 860 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.037209302325581395 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.009302325581395349 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 172 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 172 | | mean | 7.88 | | std | 7.73 | | cv | 0.982 | | sampleLengths | | 0 | 25 | | 1 | 26 | | 2 | 15 | | 3 | 12 | | 4 | 9 | | 5 | 13 | | 6 | 11 | | 7 | 11 | | 8 | 3 | | 9 | 4 | | 10 | 14 | | 11 | 18 | | 12 | 15 | | 13 | 3 | | 14 | 6 | | 15 | 8 | | 16 | 4 | | 17 | 14 | | 18 | 13 | | 19 | 11 | | 20 | 5 | | 21 | 15 | | 22 | 11 | | 23 | 10 | | 24 | 10 | | 25 | 9 | | 26 | 2 | | 27 | 3 | | 28 | 5 | | 29 | 12 | | 30 | 1 | | 31 | 1 | | 32 | 18 | | 33 | 17 | | 34 | 8 | | 35 | 2 | | 36 | 6 | | 37 | 3 | | 38 | 6 | | 39 | 17 | | 40 | 2 | | 41 | 1 | | 42 | 10 | | 43 | 1 | | 44 | 1 | | 45 | 3 | | 46 | 7 | | 47 | 1 | | 48 | 2 | | 49 | 2 |
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| 43.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.3313953488372093 | | totalSentences | 172 | | uniqueOpeners | 57 | |
| 37.04% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 90 | | matches | | | ratio | 0.011 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 90 | | matches | | 0 | "Her black hair clung damply" | | 1 | "She pulled off her gloves," | | 2 | "She spotted Silas behind the" | | 3 | "His signet ring glinted under" | | 4 | "He glanced up." | | 5 | "she said, dropping into her" | | 6 | "He knew her too well." | | 7 | "She stirred the tea, steam" | | 8 | "He didn’t see her at" | | 9 | "Her name on his tongue" | | 10 | "She didn’t move." | | 11 | "Her hands curled around the" | | 12 | "she said softly" | | 13 | "She looked at him—really looked." | | 14 | "He leaned forward." | | 15 | "she said, voice flat" | | 16 | "She laughed, brittle" | | 17 | "she said, quieter now" | | 18 | "He trailed off" | | 19 | "He met her eyes." |
| | ratio | 0.333 | |
| 98.89% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 90 | | matches | | 0 | "Rain tapped a dull rhythm" | | 1 | "A jazz trio played low" | | 2 | "The kind of night that" | | 3 | "Aurora Carter stepped inside, shaking" | | 4 | "Her black hair clung damply" | | 5 | "She pulled off her gloves," | | 6 | "The delivery bag slumped against" | | 7 | "She spotted Silas behind the" | | 8 | "His signet ring glinted under" | | 9 | "He glanced up." | | 10 | "A flicker in his hazel" | | 11 | "she said, dropping into her" | | 12 | "Silas brought her a hot" | | 13 | "He knew her too well." | | 14 | "She stirred the tea, steam" | | 15 | "A gust of cold air," | | 16 | "A tailored coat, worn just" | | 17 | "A scar—thin, pale—ran along his" | | 18 | "Aurora’s spoon clinked against the" | | 19 | "He didn’t see her at" |
| | ratio | 0.722 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 90 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 1 | | matches | | 0 | "The boy who used to toss pebbles at her window at midnight, who’d sneak her out to the cliffs above Barry Island to watch the sun rise, who’d kissed her for the…" |
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| 97.22% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 65 | | tagDensity | 0.246 | | leniency | 0.492 | | rawRatio | 0.063 | | effectiveRatio | 0.031 | |